Skipt to content

M.Sc. Johannes Löw

Profile Picture: M.Sc. Johannes Löw JL

M.Sc. Johannes Löw Fellow

Research assistant Geoecology

Mail: johannes.loew@geo.uni-halle.de Tel: +49 (0)345 55-26045 Room: H4 1.37 Consultation hours: by arrangement(during the semester break only by appointment)

Focus Areas:

Earth observation, Land Surface Dynamics, Radar, Crop Phenology

Research

  • Remote sensing
  • Radar time series
  • Ecosystem monitoring
  • Land surface dynamics

Biography

  • since 07/2022
    Research assistant at the Chair of Geoecology, University of Halle-Wittenberg
  • 09/2020 – 06/2022
    Research Assistant at the Chair of Remote Sensing, University of Würzburg, seconded to: Chair of Geoecology, University of Halle-Wittenberg
  • 06/2019 – 06/2020
    Research assistant at the Chair of Remote Sensing, University of Würzburg in the project MedWater
  • 04/2019 – 06/2019
    Research Assistant at the Chair of Remote Sensing, University of Würzburg
  • 10/2016 – 03/2019
    Study of Earth Observation and Geoanalysis “EAGLE” (M.Sc.), University of Würzburg
    Master thesis: “Interferometric and polarimetric signatures of agricultural crops using multi-temporal dual-polarimetric Sentinel-1 Imagery: a case study in north-eastern Germany”
  • 11/2017 – 12/2017
    Intern at the WASCAL Competence Centre Ouagadougou, Burkina Faso
  • 12/2016 – 12/2017
    Research assistant at the Chair of Remote Sensing, University of Würzburg
  • 10/2012 – 09/2016
    Study of Geography (B.Sc.) with focus on Human Geography and Remote Sensing, University of Würzburg
    Bachelor thesis: Analysis of soil moisture development in Central Asian irrigation systems using CCI Soil moisture time series
  • 07/2015 – 08/2015
    Intern, Department of Land Surface Dynamics, German Remote Sensing Data Centre (DFD), German Aerospace Center (DLR), Oberpfaffenhofen, Germany

Publications

2355391MDLREVTXPeerReview,JLLöw american-journal-of-plant-sciences50datedesc Löw, J. 12628https://geo.uni-halle.de/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A0%2C%22request_next%22%3A0%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%22E79NMBHK%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222025-08-25%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Hill%2C%20S.%2C%20Otte%2C%20I.%2C%20Friedrich%2C%20C.%2C%20Thiel%2C%20M.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282025%29%20Integrating%20the%20Landscape%20Scale%20Supports%20SAR-Based%20Detection%20and%20Assessment%20of%20the%20Phenological%20Development%20at%20the%20Field%20Level.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Remote%20Sensing%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B6%26lt%3B%5C%2Fb%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffrsen.2025.1610005%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffrsen.2025.1610005%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Integrating%20the%20landscape%20scale%20supports%20SAR-based%20detection%20and%20assessment%20of%20the%20phenological%20development%20at%20the%20field%20level%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Insa%22%2C%22lastName%22%3A%22Otte%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christoph%22%2C%22lastName%22%3A%22Friedrich%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22Climate%20change%20and%20increasing%20weather%20and%20seasonal%20dynamics%20challenge%20agricultural%20landscapes.%20To%20cope%20with%20this%20challenge%20information%20on%20crop%20performance%20is%20key.%20This%20study%20presents%20a%20novel%20framework%20for%20bridging%20landscape-scale%20vegetation%20dynamics%20with%20field-level%20crop%20phenology%20using%20Sentinel-1%20radar%20time%20series.%20Unlike%20previous%20approaches%20that%20focus%20on%20local%20algorithm%20optimisation%20or%20SAR%20feature%20selection%2C%20this%20work%20integrates%20two%20scales%3A%20%281%29%20landscape%20patterns%20derived%20from%20annual%20distributions%20of%20time%20series%20metrics%20%28TSMs%29%20and%20%282%29%20field-level%20phenology%2C%20both%20linked%20to%20growing%20degree%20days%20%28GDD%29.%20TSMs%20were%20generated%20through%20breakpoint%20analyses%20over%20different%20smoothing%20intensities%20for%20Sentinel-1%20polarisation%20%28PolSAR%29%20and%20interferometric%20coherence%20%28InSAR%29%20features%2C%20capturing%20crop%2C%20orbit%20and%20sensor-specific%20responses.%20The%20framework%20quantifies%20uncertainties%20inherent%20in%20both%20remote%20sensing%20and%20ground%20observations%2C%20and%20evaluates%20trackable%20progress%20%28phenological%20stage%20detectability%29%20and%20tracking%20range%20%28GDD%20variance%20around%20stages%29%20to%20assess%20accuracy%20under%20variable%20acquisition%20geometries%2C%20weather%20and%20smoothing%20parameters.%20Applied%20to%20the%20DEMMIN%20site%20%28Germany%29%2C%20the%20analysis%20revealed%20consistent%20TSM-GDD%20relationships%20for%20wheat%2C%20rape%2C%20and%20sugar%20beet%2C%20with%20descriptors%20such%20as%20soil%20fertility%20and%20water%20availability%20explaining%20spatial%20patterns%20%28R2%20%5Cu2248%200.8%29.%20Key%20novelties%20include%20the%20identification%20of%20low%20tracking%20ranges%20in%20drought%20years%2C%20the%20demonstration%20of%20the%20impact%20of%20orbit-specific%20incidence%20angles%20on%20monitoring%20fidelity%2C%20and%20the%20highlighting%20of%20Sentinel-1%5Cu2019s%20ability%20to%20resolve%20phenological%20variance%20across%20fragmented%20landscapes.%20By%20harmonising%20multi-scale%20SAR%20time%20series%20with%20agro-meteorological%20data%2C%20this%20approach%20advances%20transferable%20methods%20for%20operational%20crop%20monitoring%2C%20supporting%20precision%20agriculture%20and%20regional%20yield%20assessment%20beyond%20localised%20models.%22%2C%22date%22%3A%222025-08-25%22%2C%22language%22%3A%22English%22%2C%22DOI%22%3A%2210.3389%5C%2Ffrsen.2025.1610005%22%2C%22ISSN%22%3A%222673-6187%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Fjournals%5C%2Fremote-sensing%5C%2Farticles%5C%2F10.3389%5C%2Ffrsen.2025.1610005%5C%2Ffull%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-29T08%3A44%3A38Z%22%7D%7D%2C%7B%22key%22%3A%224B362AC5%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Mahmood%20et%20al.%22%2C%22parsedDate%22%3A%222024-08-19%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BMahmood%2C%20T.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20P%26%23xF6%3Bhlitz%2C%20J.%2C%20Wenzel%2C%20J.L.%20and%20Conrad%2C%20C.%20%282024%29%20Estimation%20of%20100%20m%20Root%20Zone%20Soil%20Moisture%20by%20Downscaling%201%20Km%20Soil%20Water%20Index%20with%20Machine%20Learning%20and%20Multiple%20Geodata.%20%26lt%3Bi%26gt%3BEnvironmental%20Monitoring%20and%20Assessment%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B196%26lt%3B%5C%2Fb%26gt%3B%2C%20823.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2Fhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10661-024-12969-5%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2Fhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10661-024-12969-5%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Estimation%20of%20100%20m%20root%20zone%20soil%20moisture%20by%20downscaling%201%20km%20soil%20water%20index%20with%20machine%20learning%20and%20multiple%20geodata%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Talha%22%2C%22lastName%22%3A%22Mahmood%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22P%5Cu00f6hlitz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%20Lukas%22%2C%22lastName%22%3A%22Wenzel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-08-19%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10661-024-12969-5%22%2C%22ISSN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-14T12%3A02%3A55Z%22%7D%7D%2C%7B%22key%22%3A%22X5MM3YCI%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222024-07-30%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Hill%2C%20S.%2C%20Otte%2C%20I.%2C%20Thiel%2C%20M.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282024%29%20How%20Phenology%20Shapes%20Crop-Specific%20Sentinel-1%20PolSAR%20Features%20and%20InSAR%20Coherence%20across%20Multiple%20Years%20and%20Orbits.%20%26lt%3Bi%26gt%3BRemote%20Sensing%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B16%26lt%3B%5C%2Fb%26gt%3B%2C%202791.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs16152791%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs16152791%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22How%20Phenology%20Shapes%20Crop-Specific%20Sentinel-1%20PolSAR%20Features%20and%20InSAR%20Coherence%20across%20Multiple%20Years%20and%20Orbits%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Insa%22%2C%22lastName%22%3A%22Otte%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22Spatial%20information%20about%20plant%20health%20and%20productivity%20are%20essential%20when%20assessing%20the%20progress%20towards%20Sustainable%20Development%20Goals%20such%20as%20life%20on%20land%20and%20zero%20hunger.%20Plant%20health%20and%20productivity%20are%20strongly%20linked%20to%20a%20plant%5Cu2019s%20phenological%20progress.%20Remote%20sensing%2C%20and%20since%20the%20launch%20of%20Sentinel-1%20%28S1%29%2C%20specifically%2C%20radar-based%20frameworks%20have%20been%20studied%20for%20the%20purpose%20of%20monitoring%20phenological%20development.%20This%20study%20produces%20insights%20into%20how%20crop%20phenology%20shapes%20S1%20signatures%20of%20PolSAR%20features%20and%20InSAR%20coherence%20of%20wheat%2C%20canola%2C%20sugar%20beet.%20and%20potato%20across%20multiple%20years%20and%20orbits.%20Hereby%2C%20differently%20smoothed%20time%20series%20and%20a%20base%20line%20of%20growing%20degree%20days%20are%20stacked%20to%20estimate%20the%20patterns%20of%20occurrence%20of%20extreme%20values%20and%20break%20points.%20These%20patterns%20are%20then%20linked%20to%20in%20situ%20observations%20of%20phenological%20developments.%20The%20comparison%20of%20patterns%20across%20multiple%20orbits%20and%20years%20reveals%20that%20a%20single%20optimized%20fit%20hampers%20the%20tracking%20capacities%20of%20an%20entire%20season%20monitoring%20framework%2C%20as%20does%20the%20sole%20reliance%20on%20extreme%20values.%20VV%20and%20VH%20backscatter%20intensities%20outperform%20all%20other%20features%2C%20but%20certain%20combinations%20of%20phenological%20stage%20and%20crop%20type%20are%20better%20covered%20by%20a%20complementary%20set%20of%20PolSAR%20features%20and%20coherence.%20With%20regard%20to%20PolSAR%20features%2C%20alpha%20and%20entropy%20can%20be%20replaced%20by%20the%20cross-polarization%20ratio%20for%20tracking%20certain%20stages.%20Moreover%2C%20a%20range%20of%20moderate%20incidence%20angles%20is%20better%20suited%20for%20monitoring%20crop%20phenology.%20Also%2C%20wheat%20and%20canola%20are%20favored%20by%20a%20late%20afternoon%20overpass.%20In%20sum%2C%20this%20study%20provides%20insights%20into%20phenological%20developments%20at%20the%20landscape%20level%20that%20can%20be%20of%20further%20use%20when%20investigating%20spatial%20and%20temporal%20variations%20within%20the%20landscape.%22%2C%22date%22%3A%222024-07-30%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.3390%5C%2Frs16152791%22%2C%22ISSN%22%3A%222072-4292%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.mdpi.com%5C%2F2072-4292%5C%2F16%5C%2F15%5C%2F2791%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-14T12%3A03%3A20Z%22%7D%7D%2C%7B%22key%22%3A%22CKIYB3NF%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Lobert%20et%20al.%22%2C%22parsedDate%22%3A%222023-12-01%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BLobert%2C%20F.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20Schwieder%2C%20M.%2C%20Gocht%2C%20A.%2C%20Schlund%2C%20M.%2C%20Hostert%2C%20P.%20and%20Erasmi%2C%20S.%20%282023%29%20A%20Deep%20Learning%20Approach%20for%20Deriving%20Winter%20Wheat%20Phenology%20from%20Optical%20and%20SAR%20Time%20Series%20at%20Field%20Level.%20%26lt%3Bi%26gt%3BRemote%20Sensing%20of%20Environment%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B298%26lt%3B%5C%2Fb%26gt%3B%2C%20113800.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.rse.2023.113800%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.rse.2023.113800%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22A%20deep%20learning%20approach%20for%20deriving%20winter%20wheat%20phenology%20from%20optical%20and%20SAR%20time%20series%20at%20field%20level%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Felix%22%2C%22lastName%22%3A%22Lobert%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marcel%22%2C%22lastName%22%3A%22Schwieder%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexander%22%2C%22lastName%22%3A%22Gocht%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Schlund%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Patrick%22%2C%22lastName%22%3A%22Hostert%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stefan%22%2C%22lastName%22%3A%22Erasmi%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222023-12-01%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.rse.2023.113800%22%2C%22ISSN%22%3A%2200344257%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Flinkinghub.elsevier.com%5C%2Fretrieve%5C%2Fpii%5C%2FS0034425723003516%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A02Z%22%7D%7D%2C%7B%22key%22%3A%22IGM6TEHD%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222021-07-01%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282021%29%20The%20Impact%20of%20Phenological%20Developments%20on%20Interferometric%20and%20Polarimetric%20Crop%20Signatures%20Derived%20from%20Sentinel-1%3A%20Examples%20from%20the%20DEMMIN%20Study%20Site%20%28Germany%29.%20%26lt%3Bi%26gt%3BRemote%20Sensing%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B13%26lt%3B%5C%2Fb%26gt%3B%2C%202951.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs13152951%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs13152951%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22The%20Impact%20of%20Phenological%20Developments%20on%20Interferometric%20and%20Polarimetric%20Crop%20Signatures%20Derived%20from%20Sentinel-1%3A%20Examples%20from%20the%20DEMMIN%20Study%20Site%20%28Germany%29%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22This%20study%20explores%20the%20potential%20of%20Sentinel-1%20Synthetic%20Aperture%20Radar%20%28SAR%29%20to%20identify%20phenological%20phases%20of%20wheat%2C%20sugar%20beet%2C%20and%20canola.%20Breakpoint%20and%20extreme%20value%20analyses%20were%20applied%20to%20a%20dense%20time%20series%20of%20interferometric%20%28InSAR%29%20and%20polarimetric%20%28PolSAR%29%20features%20recorded%20during%20the%20growing%20season%20of%202017%20at%20the%20JECAM%20site%20DEMMIN%20%28Germany%29.%20The%20analyses%20of%20breakpoints%20and%20extrema%20allowed%20for%20the%20distinction%20of%20vegetative%20and%20reproductive%20stages%20for%20wheat%20and%20canola.%20Certain%20phenological%20stages%2C%20measured%20in%20situ%20using%20the%20BBCH-scale%2C%20such%20as%20leaf%20development%20and%20rosette%20growth%20of%20sugar%20beet%20or%20stem%20elongation%20and%20ripening%20of%20wheat%2C%20were%20detectable%20by%20a%20combination%20of%20InSAR%20coherence%2C%20polarimetric%20Alpha%20and%20Entropy%2C%20and%20backscatter%20%28VV%5C%2FVH%29.%20Except%20for%20some%20fringe%20cases%2C%20the%20temporal%20difference%20between%20in%20situ%20observations%20and%20breakpoints%20or%20extrema%20ranged%20from%20zero%20to%20five%20days.%20Backscatter%20produced%20the%20signature%20that%20generated%20the%20most%20breakpoints%20and%20extrema.%20However%2C%20certain%20micro%20stadia%2C%20such%20as%20leaf%20development%20of%20BBCH%2010%20of%20sugar%20beet%20or%20flowering%20BBCH%2069%20of%20wheat%2C%20were%20only%20identifiable%20by%20the%20InSAR%20coherence%20and%20Alpha.%20Hence%2C%20it%20is%20concluded%20that%20combining%20PolSAR%20and%20InSAR%20features%20increases%20the%20number%20of%20detectable%20phenological%20events%20in%20the%20phenological%20cycles%20of%20crops.%22%2C%22date%22%3A%222021-07-01%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.3390%5C%2Frs13152951%22%2C%22ISSN%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.mdpi.com%5C%2F2072-4292%5C%2F13%5C%2F15%5C%2F2951%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A54Z%22%7D%7D%5D%7D
1
Löw, J., Hill, S., Otte, I., Friedrich, C., Thiel, M., Ullmann, T. and Conrad, C. (2025) Integrating the Landscape Scale Supports SAR-Based Detection and Assessment of the Phenological Development at the Field Level. Frontiers in Remote Sensing, 6. https://doi.org/10.3389/frsen.2025.1610005.
1
Mahmood, T., Löw, J., Pöhlitz, J., Wenzel, J.L. and Conrad, C. (2024) Estimation of 100 m Root Zone Soil Moisture by Downscaling 1 Km Soil Water Index with Machine Learning and Multiple Geodata. Environmental Monitoring and Assessment, 196, 823. https://doi.org/https://doi.org/10.1007/s10661-024-12969-5.
1
Löw, J., Hill, S., Otte, I., Thiel, M., Ullmann, T. and Conrad, C. (2024) How Phenology Shapes Crop-Specific Sentinel-1 PolSAR Features and InSAR Coherence across Multiple Years and Orbits. Remote Sensing, 16, 2791. https://doi.org/10.3390/rs16152791.
1
Lobert, F., Löw, J., Schwieder, M., Gocht, A., Schlund, M., Hostert, P. and Erasmi, S. (2023) A Deep Learning Approach for Deriving Winter Wheat Phenology from Optical and SAR Time Series at Field Level. Remote Sensing of Environment, 298, 113800. https://doi.org/10.1016/j.rse.2023.113800.
1
Löw, J., Ullmann, T. and Conrad, C. (2021) The Impact of Phenological Developments on Interferometric and Polarimetric Crop Signatures Derived from Sentinel-1: Examples from the DEMMIN Study Site (Germany). Remote Sensing, 13, 2951. https://doi.org/10.3390/rs13152951.

 

2355391MDLREVTXConferencePaper,JLLöw american-journal-of-plant-sciences50datedesc1 Löw, J. 12628https://geo.uni-halle.de/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A0%2C%22request_next%22%3A0%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%22M3HEFZB5%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222024-03-15%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Hill%2C%20S.%2C%20Thiel%2C%20M.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282024%29%20Tracking%20Crop%20Phenology%20across%20Different%20Sentinel-1%20Orbits%20by%20Combining%20PolSAR%20Features%20with%20Growing%20Degree%20Data.%20Remagen.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22Tracking%20crop%20phenology%20across%20different%20Sentinel-1%20orbits%20by%20combining%20PolSAR%20features%20with%20Growing%20Degree%20data%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-03-15%22%2C%22proceedingsTitle%22%3A%22%22%2C%22conferenceName%22%3A%22DGPF%20Jahrestagung%202024%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22ISBN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A40%3A31Z%22%7D%7D%2C%7B%22key%22%3A%224GUCAK39%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Friedrich%20et%20al.%22%2C%22parsedDate%22%3A%222024-02-28%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BFriedrich%2C%20C.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20Otte%2C%20I.%2C%20Hill%2C%20S.%2C%20F%26%23xF6%3Brtsch%2C%20S.%2C%20Schwalb-Willmann%2C%20J.%2C%20Gessner%2C%20U.%2C%20Schierghofer%2C%20C.%2C%20Piernecke%2C%20T.%2C%20Truckenbrodt%2C%20S.%2C%20Schonert%2C%20E.%2C%20Assmann%2C%20D.%2C%20B%26%23xF6%3Bttcher%2C%20F.%2C%20Conrad%2C%20C.%20and%20Thiel%2C%20M.%20%282024%29%20A%20Multi-Talented%20Datacube%3A%20Integrating%2C%20Processing%20and%20Presenting%20Big%20Geodata%20for%20the%5Cnagricultural%20End%20User.%20Informatik%20in%20Der%20Land-%2C%20Forstund%5CnErn%26%23xE4%3Bhrungswirtschaft%5CnFokus%3A%20Biodiversit%26%23xE4%3Bt%20F%26%23xF6%3Brdern%20Durch%20Digitale%20Landwirtschaft%2C%20Stuttgart-Hohenheim.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22A%20multi-talented%20datacube%3A%20integrating%2C%20processing%20and%20presenting%20big%20geodata%20for%20the%5Cnagricultural%20end%20user%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christoph%22%2C%22lastName%22%3A%22Friedrich%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Insa%22%2C%22lastName%22%3A%22Otte%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sebastian%22%2C%22lastName%22%3A%22F%5Cu00f6rtsch%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jakob%22%2C%22lastName%22%3A%22Schwalb-Willmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ursula%22%2C%22lastName%22%3A%22Gessner%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christoph%22%2C%22lastName%22%3A%22Schierghofer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Piernecke%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sina%22%2C%22lastName%22%3A%22Truckenbrodt%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Eric%22%2C%22lastName%22%3A%22Schonert%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Denise%22%2C%22lastName%22%3A%22Assmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Falk%22%2C%22lastName%22%3A%22B%5Cu00f6ttcher%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-02-28%22%2C%22proceedingsTitle%22%3A%22Informatik%20in%20der%20Land-%2C%20Forstund%5CnErn%5Cu00e4hrungswirtschaft%5CnFokus%3A%20Biodiversit%5Cu00e4t%20f%5Cu00f6rdern%20durch%20digitale%20Landwirtschaft%22%2C%22conferenceName%22%3A%2244.%20GIL-Jahrestagung%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22ISBN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A40%3A53Z%22%7D%7D%2C%7B%22key%22%3A%2294IK4ZUN%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Conrad%20et%20al.%22%2C%22parsedDate%22%3A%222023-06-12%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BConrad%2C%20C.%2C%20Schlaak%2C%20J.%2C%20Schmelzer%2C%20J.%20and%20L%26%23xF6%3Bw%2C%20J.%20%282023%29%20Downscaling%20and%20Validation%20of%201km%20ESA%20Soil%20Water%20Index%20for%20Soil%20Moisture%20Monitoring%20on%20Agricultural%20Land%20in%20Temperate%20Climate%20Conditions.%20EGU%2C%20Naples.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2Fhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.5194%5C%2Fegusphere-gc8-hydro-97%2C%202023%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2Fhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.5194%5C%2Fegusphere-gc8-hydro-97%2C%202023%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22Downscaling%20and%20validation%20of%201km%20ESA%20Soil%20Water%20Index%20for%20soil%20moisture%20monitoring%20on%20agricultural%20land%20in%20temperate%20climate%20conditions%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julian%22%2C%22lastName%22%3A%22Schlaak%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22Schmelzer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%5D%2C%22abstractNote%22%3A%22Near-surface%20soil%20moisture%20is%20an%20important%20parameter%20for%20estimating%20the%20water%20balance%20of%20ecosystems%2C%20especially%20for%20the%20exchange%20of%20water%20between%20atmosphere%20and%20soil.%20In%20the%20past%20decades%2C%20global%20and%20continental%20products%2C%20e.g.%20the%20Soil%20Water%20Index%20%28SWI%29%20of%20ESA%2C%20have%20been%20developed%20for%20large-scale%20monitoring%20from%20passive%20and%20active%20microwave%20data.%20ESA%20SWI%20was%20developed%20for%20Europe%20based%20on%20the%20surface%20soil%20moisture%20product%20derived%20from%20Sentinel-1%20C-band%20SAR%20data%20%281km%20resolution%29%20and%20Metop%20ASCAT%20surface%20soil%20moisture%20%2812.5km%29.%20However%2C%20for%20practical%2C%20small-scale%20applications%20on%20the%20local%20level%2C%20there%20is%20currently%20little%20data%20available.%20This%20contribution%20elaborates%20on%20the%20validation%20of%20the%20SWI%20for%20temperate%20agricultural%20regions%20at%20the%20example%20of%20the%20agrometeorological%20network%20of%20the%20JECAM%20test%20site%20DEMMIN%20in%20Northeast%20Germany.%20For%20this%20purpose%2C%20two%20resampling%20methods%2C%20a%20bilinear%20interpolation%20and%20a%20statistical%20downscaling%20approach%20using%20Random%20Forest%20were%20tested%20on%20SWI%20data%20from%202019.%20The%20statistical%20downscaling%20approach%20integrates%20Sentinel%20satellite%20data%20and%20the%20Topographical%20Wetness%20Index%20based%20on%20a%2010m%20resolved%20elevation%20model.%20Both%20resampling%20methods%20showed%20similar%20results.%20Over%20time%2C%20the%20SWI%20significantly%20overestimates%20the%20in%20situ%20data%20before%20and%20after%20the%20crop%20growing%20season.%20A%20higher%20agreement%20is%20observed%20in%20the%20summer%20months.%20For%2019%20of%20the%2029%20investigated%20agrometeorological%20stations%20a%20statistically%20positive%20correlation%20with%20R%26gt%3B0.5%20was%20found.%20The%20remaining%20stations%20showed%20little%20to%20no%20correlation%2C%20most%20likely%20due%20influences%20of%20various%20crops%20types%20on%20the%20remote%20sensing%20data.%20The%20results%20suggest%20a%20temporally%20limited%20applicability%20of%20the%20SWI%201km%20data%20for%20local%20assessments%20of%20soil%20moisture.%22%2C%22date%22%3A%222023-06-12%22%2C%22proceedingsTitle%22%3A%22%22%2C%22conferenceName%22%3A%22A%20European%20vision%20for%20hydrological%20observations%20and%20experimentation%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.5194%5C%2Fegusphere-gc8-hydro-97%2C%202023%22%2C%22ISBN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A30Z%22%7D%7D%5D%7D
1
Löw, J., Hill, S., Thiel, M., Ullmann, T. and Conrad, C. (2024) Tracking Crop Phenology across Different Sentinel-1 Orbits by Combining PolSAR Features with Growing Degree Data. Remagen.
1
Friedrich, C., Löw, J., Otte, I., Hill, S., Förtsch, S., Schwalb-Willmann, J., Gessner, U., Schierghofer, C., Piernecke, T., Truckenbrodt, S., Schonert, E., Assmann, D., Böttcher, F., Conrad, C. and Thiel, M. (2024) A Multi-Talented Datacube: Integrating, Processing and Presenting Big Geodata for the agricultural End User. Informatik in Der Land-, Forstund Ernährungswirtschaft Fokus: Biodiversität Fördern Durch Digitale Landwirtschaft, Stuttgart-Hohenheim.
1
Conrad, C., Schlaak, J., Schmelzer, J. and Löw, J. (2023) Downscaling and Validation of 1km ESA Soil Water Index for Soil Moisture Monitoring on Agricultural Land in Temperate Climate Conditions. EGU, Naples. https://doi.org/https://doi.org/10.5194/egusphere-gc8-hydro-97, 2023.

2355391MDLREVTXLöw 1american-journal-of-plant-sciences50datedesc1 Löw, J. 12628https://geo.uni-halle.de/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A50%2C%22request_next%22%3A50%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%22886GXTZ5%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Conrad%20et%20al.%22%2C%22parsedDate%22%3A%222025-08-29%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BConrad%2C%20C.%2C%20Teucher%2C%20M.%2C%20Wenzel%2C%20J.L.%2C%20L%26%23xF6%3Bw%2C%20J.%20and%20P%26%23xF6%3Bhlitz%2C%20J.%20%282025%2C%20August%2029%29%20Verbundprojekt%3A%20Einsatz%20von%20Fernerkundungstechnologien%20f%26%23xFC%3Br%20die%20Digitalisierung%20im%20Pflanzenbau%20%28AgriSens-DEMMIN4.0%29%20-%20Teilprojekt%205%3A%20Sachbericht%20zum%20Verwendungsnachweis.%20Technische%20Informationsbibliothek%20%28TIB%29.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.34657%5C%2F23043%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.34657%5C%2F23043%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22preprint%22%2C%22title%22%3A%22Verbundprojekt%3A%20Einsatz%20von%20Fernerkundungstechnologien%20f%5Cu00fcr%20die%20Digitalisierung%20im%20Pflanzenbau%20%28AgriSens-DEMMIN4.0%29%20-%20Teilprojekt%205%3A%20Sachbericht%20zum%20Verwendungsnachweis%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mike%22%2C%22lastName%22%3A%22Teucher%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%20Lukas%22%2C%22lastName%22%3A%22Wenzel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22P%5Cu00f6hlitz%22%7D%2C%7B%22creatorType%22%3A%22contributor%22%2C%22name%22%3A%22Technische%20Informationsbibliothek%20%28TIB%29%22%7D%5D%2C%22abstractNote%22%3A%22Das%20Verbundvorhaben%20AgriSens-DEMMIN%204.0%20%282020%5Cu20132025%29%20zielt%20auf%20die%20praxisnahe%20Nutzung%20digitaler%20Technologien%20im%20Pflanzenbau.%20Die%20Martin-Luther-Universit%5Cu00e4t%20Halle-Wittenberg%20%28MLU%29%20bearbeitete%20im%20Teilprojekt%205%20zentrale%20Aufgaben%20in%20den%20Bereichen%20UAV-gest%5Cu00fctzte%20Datenerhebung%2C%20Satellitendatenfusion%2C%20Boden-%20und%20Vegetationsanalyse%20sowie%20Emissionsschutz.%20In%20Phase%20I%20wurden%20multisensorische%20UAV-Strategien%20zur%20Steindetektion%20und%20Grundlagen%20f%5Cu00fcr%20teilfl%5Cu00e4chenspezifische%20Bew%5Cu00e4sserung%20im%20Kartoffelanbau%20entwickelt.%20Phase%20II%20fokussierte%20auf%20Praxistransfer%20und%20r%5Cu00e4umliche%20Skalierung%2C%20u.a.%20durch%20Radarfernerkundung%20zur%20Ph%5Cu00e4nologieerfassung%20und%20Bodenfeuchtemodellierung.%20Die%20MLU%20entwickelte%20einen%20Sentinel-1-Prozessor%20f%5Cu00fcr%20den%20Smart%20Open%20Data%20Cube.%20Ergebnisse%20wurden%20in%20Fachzeitschriften%20publiziert%2C%20auf%20Konferenzen%20vorgestellt%20und%20in%20prototypischen%20Anwendungen%20umgesetzt.%20Die%20Zusammenarbeit%20mit%20Forschungseinrichtungen%2C%20Agrarbetrieben%20und%20Technologieunternehmen%20f%5Cu00f6rderte%20die%20Integration%20digitaler%20L%5Cu00f6sungen%20in%20die%20landwirtschaftliche%20Praxis.%22%2C%22genre%22%3A%22%22%2C%22repository%22%3A%22Technische%20Informationsbibliothek%20%28TIB%29%22%2C%22archiveID%22%3A%22%22%2C%22date%22%3A%222025-08-29%22%2C%22DOI%22%3A%2210.34657%5C%2F23043%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Foa.tib.eu%5C%2Frenate%5C%2Fhandle%5C%2F123456789%5C%2F24026%22%2C%22language%22%3A%22de%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-10-17T06%3A29%3A45Z%22%7D%7D%2C%7B%22key%22%3A%22E79NMBHK%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222025-08-25%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Hill%2C%20S.%2C%20Otte%2C%20I.%2C%20Friedrich%2C%20C.%2C%20Thiel%2C%20M.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282025%29%20Integrating%20the%20Landscape%20Scale%20Supports%20SAR-Based%20Detection%20and%20Assessment%20of%20the%20Phenological%20Development%20at%20the%20Field%20Level.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Remote%20Sensing%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B6%26lt%3B%5C%2Fb%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffrsen.2025.1610005%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffrsen.2025.1610005%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Integrating%20the%20landscape%20scale%20supports%20SAR-based%20detection%20and%20assessment%20of%20the%20phenological%20development%20at%20the%20field%20level%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Insa%22%2C%22lastName%22%3A%22Otte%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christoph%22%2C%22lastName%22%3A%22Friedrich%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22Climate%20change%20and%20increasing%20weather%20and%20seasonal%20dynamics%20challenge%20agricultural%20landscapes.%20To%20cope%20with%20this%20challenge%20information%20on%20crop%20performance%20is%20key.%20This%20study%20presents%20a%20novel%20framework%20for%20bridging%20landscape-scale%20vegetation%20dynamics%20with%20field-level%20crop%20phenology%20using%20Sentinel-1%20radar%20time%20series.%20Unlike%20previous%20approaches%20that%20focus%20on%20local%20algorithm%20optimisation%20or%20SAR%20feature%20selection%2C%20this%20work%20integrates%20two%20scales%3A%20%281%29%20landscape%20patterns%20derived%20from%20annual%20distributions%20of%20time%20series%20metrics%20%28TSMs%29%20and%20%282%29%20field-level%20phenology%2C%20both%20linked%20to%20growing%20degree%20days%20%28GDD%29.%20TSMs%20were%20generated%20through%20breakpoint%20analyses%20over%20different%20smoothing%20intensities%20for%20Sentinel-1%20polarisation%20%28PolSAR%29%20and%20interferometric%20coherence%20%28InSAR%29%20features%2C%20capturing%20crop%2C%20orbit%20and%20sensor-specific%20responses.%20The%20framework%20quantifies%20uncertainties%20inherent%20in%20both%20remote%20sensing%20and%20ground%20observations%2C%20and%20evaluates%20trackable%20progress%20%28phenological%20stage%20detectability%29%20and%20tracking%20range%20%28GDD%20variance%20around%20stages%29%20to%20assess%20accuracy%20under%20variable%20acquisition%20geometries%2C%20weather%20and%20smoothing%20parameters.%20Applied%20to%20the%20DEMMIN%20site%20%28Germany%29%2C%20the%20analysis%20revealed%20consistent%20TSM-GDD%20relationships%20for%20wheat%2C%20rape%2C%20and%20sugar%20beet%2C%20with%20descriptors%20such%20as%20soil%20fertility%20and%20water%20availability%20explaining%20spatial%20patterns%20%28R2%20%5Cu2248%200.8%29.%20Key%20novelties%20include%20the%20identification%20of%20low%20tracking%20ranges%20in%20drought%20years%2C%20the%20demonstration%20of%20the%20impact%20of%20orbit-specific%20incidence%20angles%20on%20monitoring%20fidelity%2C%20and%20the%20highlighting%20of%20Sentinel-1%5Cu2019s%20ability%20to%20resolve%20phenological%20variance%20across%20fragmented%20landscapes.%20By%20harmonising%20multi-scale%20SAR%20time%20series%20with%20agro-meteorological%20data%2C%20this%20approach%20advances%20transferable%20methods%20for%20operational%20crop%20monitoring%2C%20supporting%20precision%20agriculture%20and%20regional%20yield%20assessment%20beyond%20localised%20models.%22%2C%22date%22%3A%222025-08-25%22%2C%22language%22%3A%22English%22%2C%22DOI%22%3A%2210.3389%5C%2Ffrsen.2025.1610005%22%2C%22ISSN%22%3A%222673-6187%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Fjournals%5C%2Fremote-sensing%5C%2Farticles%5C%2F10.3389%5C%2Ffrsen.2025.1610005%5C%2Ffull%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-29T08%3A44%3A38Z%22%7D%7D%2C%7B%22key%22%3A%224B362AC5%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Mahmood%20et%20al.%22%2C%22parsedDate%22%3A%222024-08-19%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BMahmood%2C%20T.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20P%26%23xF6%3Bhlitz%2C%20J.%2C%20Wenzel%2C%20J.L.%20and%20Conrad%2C%20C.%20%282024%29%20Estimation%20of%20100%20m%20Root%20Zone%20Soil%20Moisture%20by%20Downscaling%201%20Km%20Soil%20Water%20Index%20with%20Machine%20Learning%20and%20Multiple%20Geodata.%20%26lt%3Bi%26gt%3BEnvironmental%20Monitoring%20and%20Assessment%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B196%26lt%3B%5C%2Fb%26gt%3B%2C%20823.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2Fhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10661-024-12969-5%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2Fhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10661-024-12969-5%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Estimation%20of%20100%20m%20root%20zone%20soil%20moisture%20by%20downscaling%201%20km%20soil%20water%20index%20with%20machine%20learning%20and%20multiple%20geodata%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Talha%22%2C%22lastName%22%3A%22Mahmood%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22P%5Cu00f6hlitz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jan%20Lukas%22%2C%22lastName%22%3A%22Wenzel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-08-19%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10661-024-12969-5%22%2C%22ISSN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-14T12%3A02%3A55Z%22%7D%7D%2C%7B%22key%22%3A%22X5MM3YCI%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222024-07-30%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Hill%2C%20S.%2C%20Otte%2C%20I.%2C%20Thiel%2C%20M.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282024%29%20How%20Phenology%20Shapes%20Crop-Specific%20Sentinel-1%20PolSAR%20Features%20and%20InSAR%20Coherence%20across%20Multiple%20Years%20and%20Orbits.%20%26lt%3Bi%26gt%3BRemote%20Sensing%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B16%26lt%3B%5C%2Fb%26gt%3B%2C%202791.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs16152791%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs16152791%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22How%20Phenology%20Shapes%20Crop-Specific%20Sentinel-1%20PolSAR%20Features%20and%20InSAR%20Coherence%20across%20Multiple%20Years%20and%20Orbits%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Insa%22%2C%22lastName%22%3A%22Otte%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22Spatial%20information%20about%20plant%20health%20and%20productivity%20are%20essential%20when%20assessing%20the%20progress%20towards%20Sustainable%20Development%20Goals%20such%20as%20life%20on%20land%20and%20zero%20hunger.%20Plant%20health%20and%20productivity%20are%20strongly%20linked%20to%20a%20plant%5Cu2019s%20phenological%20progress.%20Remote%20sensing%2C%20and%20since%20the%20launch%20of%20Sentinel-1%20%28S1%29%2C%20specifically%2C%20radar-based%20frameworks%20have%20been%20studied%20for%20the%20purpose%20of%20monitoring%20phenological%20development.%20This%20study%20produces%20insights%20into%20how%20crop%20phenology%20shapes%20S1%20signatures%20of%20PolSAR%20features%20and%20InSAR%20coherence%20of%20wheat%2C%20canola%2C%20sugar%20beet.%20and%20potato%20across%20multiple%20years%20and%20orbits.%20Hereby%2C%20differently%20smoothed%20time%20series%20and%20a%20base%20line%20of%20growing%20degree%20days%20are%20stacked%20to%20estimate%20the%20patterns%20of%20occurrence%20of%20extreme%20values%20and%20break%20points.%20These%20patterns%20are%20then%20linked%20to%20in%20situ%20observations%20of%20phenological%20developments.%20The%20comparison%20of%20patterns%20across%20multiple%20orbits%20and%20years%20reveals%20that%20a%20single%20optimized%20fit%20hampers%20the%20tracking%20capacities%20of%20an%20entire%20season%20monitoring%20framework%2C%20as%20does%20the%20sole%20reliance%20on%20extreme%20values.%20VV%20and%20VH%20backscatter%20intensities%20outperform%20all%20other%20features%2C%20but%20certain%20combinations%20of%20phenological%20stage%20and%20crop%20type%20are%20better%20covered%20by%20a%20complementary%20set%20of%20PolSAR%20features%20and%20coherence.%20With%20regard%20to%20PolSAR%20features%2C%20alpha%20and%20entropy%20can%20be%20replaced%20by%20the%20cross-polarization%20ratio%20for%20tracking%20certain%20stages.%20Moreover%2C%20a%20range%20of%20moderate%20incidence%20angles%20is%20better%20suited%20for%20monitoring%20crop%20phenology.%20Also%2C%20wheat%20and%20canola%20are%20favored%20by%20a%20late%20afternoon%20overpass.%20In%20sum%2C%20this%20study%20provides%20insights%20into%20phenological%20developments%20at%20the%20landscape%20level%20that%20can%20be%20of%20further%20use%20when%20investigating%20spatial%20and%20temporal%20variations%20within%20the%20landscape.%22%2C%22date%22%3A%222024-07-30%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.3390%5C%2Frs16152791%22%2C%22ISSN%22%3A%222072-4292%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.mdpi.com%5C%2F2072-4292%5C%2F16%5C%2F15%5C%2F2791%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-14T12%3A03%3A20Z%22%7D%7D%2C%7B%22key%22%3A%22I4M7JI6D%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222024-06-20%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Hill%2C%20S.%2C%20Thiel%2C%20M.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282024%2C%20June%2020%29%20How%20Does%20Phenology%20Shape%20Crop-%20And%20Orbit-Specific%20InSAR%20Coherence%20And%20PolSAR-Signatures%20Of%20Sentinel-1.%20Manchester%2C%20UK.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22How%20Does%20Phenology%20Shape%20Crop-%20And%20Orbit-Specific%20InSAR%20Coherence%20And%20PolSAR-Signatures%20Of%20Sentinel-1%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-06-20%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22English%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A40%3A05Z%22%7D%7D%2C%7B%22key%22%3A%22UX89IXJF%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Friedrich%20et%20al.%22%2C%22parsedDate%22%3A%222024-03-21%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BFriedrich%2C%20C.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20Otte%2C%20I.%2C%20Hill%2C%20S.%2C%20Schierghofer%2C%20C.%2C%20Gessner%2C%20U.%2C%20Truckenbrodt%2C%20S.%2C%20Schonert%2C%20E.%2C%20Piernecke%2C%20T.%2C%20Conrad%2C%20C.%20and%20Thiel%2C%20M.%20%282024%2C%20March%2021%29%20DataCube%20Architecture%20for%20Integrating%2C%20Processing%20and%20Presenting%20Big%20Geodata%20to%20End%20Users.%20Berlin.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22DataCube%20Architecture%20for%20Integrating%2C%20Processing%20and%20Presenting%20Big%20Geodata%20to%20End%20Users%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Christoph%22%2C%22lastName%22%3A%22Friedrich%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Insa%22%2C%22lastName%22%3A%22Otte%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Christoph%22%2C%22lastName%22%3A%22Schierghofer%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Ursula%22%2C%22lastName%22%3A%22Gessner%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Sina%22%2C%22lastName%22%3A%22Truckenbrodt%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Erik%22%2C%22lastName%22%3A%22Schonert%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Piernecke%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-03-21%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A40%3A22Z%22%7D%7D%2C%7B%22key%22%3A%22PTSZUXRG%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222024-03-15%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Hill%2C%20S.%2C%20Thiel%2C%20M.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282024%2C%20March%2015%29%20Tracking%20Crop%20Phenology%20across%20Different%20Sentinel-1%20Orbits%20by%20Combining%20PolSAR%20Features%20with%20Growing%20Degree%20Data.%20Remagen.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22Tracking%20crop%20phenology%20across%20different%20Sentinel-1%20orbits%20by%20combining%20PolSAR%20features%20with%20Growing%20Degree%20data%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-03-15%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A40%3A38Z%22%7D%7D%2C%7B%22key%22%3A%22M3HEFZB5%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222024-03-15%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Hill%2C%20S.%2C%20Thiel%2C%20M.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282024%29%20Tracking%20Crop%20Phenology%20across%20Different%20Sentinel-1%20Orbits%20by%20Combining%20PolSAR%20Features%20with%20Growing%20Degree%20Data.%20Remagen.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22Tracking%20crop%20phenology%20across%20different%20Sentinel-1%20orbits%20by%20combining%20PolSAR%20features%20with%20Growing%20Degree%20data%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-03-15%22%2C%22proceedingsTitle%22%3A%22%22%2C%22conferenceName%22%3A%22DGPF%20Jahrestagung%202024%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22ISBN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A40%3A31Z%22%7D%7D%2C%7B%22key%22%3A%224GUCAK39%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Friedrich%20et%20al.%22%2C%22parsedDate%22%3A%222024-02-28%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BFriedrich%2C%20C.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20Otte%2C%20I.%2C%20Hill%2C%20S.%2C%20F%26%23xF6%3Brtsch%2C%20S.%2C%20Schwalb-Willmann%2C%20J.%2C%20Gessner%2C%20U.%2C%20Schierghofer%2C%20C.%2C%20Piernecke%2C%20T.%2C%20Truckenbrodt%2C%20S.%2C%20Schonert%2C%20E.%2C%20Assmann%2C%20D.%2C%20B%26%23xF6%3Bttcher%2C%20F.%2C%20Conrad%2C%20C.%20and%20Thiel%2C%20M.%20%282024%29%20A%20Multi-Talented%20Datacube%3A%20Integrating%2C%20Processing%20and%20Presenting%20Big%20Geodata%20for%20the%5Cnagricultural%20End%20User.%20Informatik%20in%20Der%20Land-%2C%20Forstund%5CnErn%26%23xE4%3Bhrungswirtschaft%5CnFokus%3A%20Biodiversit%26%23xE4%3Bt%20F%26%23xF6%3Brdern%20Durch%20Digitale%20Landwirtschaft%2C%20Stuttgart-Hohenheim.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22A%20multi-talented%20datacube%3A%20integrating%2C%20processing%20and%20presenting%20big%20geodata%20for%20the%5Cnagricultural%20end%20user%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christoph%22%2C%22lastName%22%3A%22Friedrich%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Insa%22%2C%22lastName%22%3A%22Otte%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sebastian%22%2C%22lastName%22%3A%22F%5Cu00f6rtsch%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jakob%22%2C%22lastName%22%3A%22Schwalb-Willmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ursula%22%2C%22lastName%22%3A%22Gessner%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christoph%22%2C%22lastName%22%3A%22Schierghofer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Piernecke%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sina%22%2C%22lastName%22%3A%22Truckenbrodt%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Eric%22%2C%22lastName%22%3A%22Schonert%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Denise%22%2C%22lastName%22%3A%22Assmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Falk%22%2C%22lastName%22%3A%22B%5Cu00f6ttcher%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-02-28%22%2C%22proceedingsTitle%22%3A%22Informatik%20in%20der%20Land-%2C%20Forstund%5CnErn%5Cu00e4hrungswirtschaft%5CnFokus%3A%20Biodiversit%5Cu00e4t%20f%5Cu00f6rdern%20durch%20digitale%20Landwirtschaft%22%2C%22conferenceName%22%3A%2244.%20GIL-Jahrestagung%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22ISBN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A40%3A53Z%22%7D%7D%2C%7B%22key%22%3A%22Q3CR95KZ%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Friedrich%20et%20al.%22%2C%22parsedDate%22%3A%222024-02-28%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BFriedrich%2C%20C.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20Otte%2C%20I.%2C%20Hill%2C%20S.%2C%20F%26%23xF6%3Brtsch%2C%20S.%2C%20Schwalb-Willmann%2C%20J.%2C%20Gessner%2C%20U.%2C%20Schierghofer%2C%20C.%2C%20Piernecke%2C%20T.%2C%20Truckenbrodt%2C%20S.%2C%20Schonert%2C%20E.%2C%20Assmann%2C%20D.%2C%20B%26%23xF6%3Bttcher%2C%20F.%2C%20Conrad%2C%20C.%20and%20Thiel%2C%20M.%20%282024%2C%20February%2028%29%20A%20Multi-Talented%20Datacube%3A%20Integrating%2C%20Processing%20and%20Presenting%20Big%20Geodata%20for%20the%5Cnagricultural%20End%20User.%20Stuttgart-Hohenheim.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22A%20multi-talented%20datacube%3A%20integrating%2C%20processing%20and%20presenting%20big%20geodata%20for%20the%5Cnagricultural%20end%20user%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Christoph%22%2C%22lastName%22%3A%22Friedrich%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Insa%22%2C%22lastName%22%3A%22Otte%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Sebastian%22%2C%22lastName%22%3A%22F%5Cu00f6rtsch%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Jakob%22%2C%22lastName%22%3A%22Schwalb-Willmann%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Ursula%22%2C%22lastName%22%3A%22Gessner%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Christoph%22%2C%22lastName%22%3A%22Schierghofer%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Thomas%22%2C%22lastName%22%3A%22Piernecke%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Sina%22%2C%22lastName%22%3A%22Truckenbrodt%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Eric%22%2C%22lastName%22%3A%22Schonert%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Denise%22%2C%22lastName%22%3A%22Assmann%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Falk%22%2C%22lastName%22%3A%22B%5Cu00f6ttcher%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-02-28%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A40%3A45Z%22%7D%7D%2C%7B%22key%22%3A%22CKIYB3NF%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Lobert%20et%20al.%22%2C%22parsedDate%22%3A%222023-12-01%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BLobert%2C%20F.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20Schwieder%2C%20M.%2C%20Gocht%2C%20A.%2C%20Schlund%2C%20M.%2C%20Hostert%2C%20P.%20and%20Erasmi%2C%20S.%20%282023%29%20A%20Deep%20Learning%20Approach%20for%20Deriving%20Winter%20Wheat%20Phenology%20from%20Optical%20and%20SAR%20Time%20Series%20at%20Field%20Level.%20%26lt%3Bi%26gt%3BRemote%20Sensing%20of%20Environment%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B298%26lt%3B%5C%2Fb%26gt%3B%2C%20113800.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.rse.2023.113800%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.rse.2023.113800%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22A%20deep%20learning%20approach%20for%20deriving%20winter%20wheat%20phenology%20from%20optical%20and%20SAR%20time%20series%20at%20field%20level%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Felix%22%2C%22lastName%22%3A%22Lobert%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marcel%22%2C%22lastName%22%3A%22Schwieder%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexander%22%2C%22lastName%22%3A%22Gocht%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Schlund%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Patrick%22%2C%22lastName%22%3A%22Hostert%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stefan%22%2C%22lastName%22%3A%22Erasmi%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222023-12-01%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.rse.2023.113800%22%2C%22ISSN%22%3A%2200344257%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Flinkinghub.elsevier.com%5C%2Fretrieve%5C%2Fpii%5C%2FS0034425723003516%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A02Z%22%7D%7D%2C%7B%22key%22%3A%22FWJZMKPD%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Wenzel%20et%20al.%22%2C%22parsedDate%22%3A%222023-11-17%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BWenzel%2C%20J.L.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20P%26%23xF6%3Bhlitz%2C%20J.%20and%20Conrad%2C%20C.%20%282023%2C%20November%2017%29%20Neues%20von%20Oben%20-%20Aktuelle%20Entwicklungen%20Satelliten-%20Und%20Drohnenbasierter%20Digitalisierung%20Im%20Pflanzenbau.%20Oral%20Presentation%2C%20Hannover%2C%20Germany.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22Neues%20von%20oben%20-%20aktuelle%20Entwicklungen%20satelliten-%20und%20drohnenbasierter%20Digitalisierung%20im%20Pflanzenbau%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Jan%20Lukas%22%2C%22lastName%22%3A%22Wenzel%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22P%5Cu00f6hlitz%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222023-11-17%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A12Z%22%7D%7D%2C%7B%22key%22%3A%22R7M9Z35Z%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Lobert%20et%20al.%22%2C%22parsedDate%22%3A%222023-07-04%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BLobert%2C%20F.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20Schwieder%2C%20M.%2C%20Gocht%2C%20A.%2C%20Schlund%2C%20M.%2C%20Hosert%2C%20P.%20and%20Erasmi%2C%20S.%20%282023%29%20Deriving%20Winter%20Wheat%20Phenology%20From%20Combined%20Optical%20And%20SAR%20Time%20Series%20With%20Deep%20Learning.%20The%2042nd%20EARSeL%20Symposium%2C%20Bucharest.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22Deriving%20Winter%20Wheat%20Phenology%20From%20Combined%20Optical%20And%20SAR%20Time%20Series%20With%20Deep%20Learning%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Felix%22%2C%22lastName%22%3A%22Lobert%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marcel%22%2C%22lastName%22%3A%22Schwieder%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexander%22%2C%22lastName%22%3A%22Gocht%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Schlund%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Patrick%22%2C%22lastName%22%3A%22Hosert%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stefan%22%2C%22lastName%22%3A%22Erasmi%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222023-07-04%22%2C%22proceedingsTitle%22%3A%22The%2042nd%20EARSeL%20Symposium%22%2C%22conferenceName%22%3A%22%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22ISBN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A18Z%22%7D%7D%2C%7B%22key%22%3A%22CZ2WHVMH%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Lepore%20et%20al.%22%2C%22parsedDate%22%3A%222023-06-15%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BLepore%2C%20D.%2C%20Conrad%2C%20C.%2C%20Allocca%2C%20V.%2C%20Cusano%2C%20D.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20El-Hokayem%2C%20L.%20and%20De%20Vita%2C%20P.%20%282023%29%20Integration%20of%20Remotely%20Sensed%20and%20Field%20Monitoring%20Data%20for%20Characterizing%20the%20Hydrological%20Regime%20of%20Soils%20Covering%20Karst%20Aquifers%20and%20Assessing%20Groundwater%20Recharge.%20EGU%2C%20Naples.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2Fhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.5194%5C%2Fegusphere-gc8-hydro-65%2C%202023%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2Fhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.5194%5C%2Fegusphere-gc8-hydro-65%2C%202023%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22Integration%20of%20remotely%20sensed%20and%20field%20monitoring%20data%20for%20characterizing%20the%20hydrological%20regime%20of%20soils%20covering%20karst%20aquifers%20and%20assessing%20groundwater%20recharge%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Daniele%22%2C%22lastName%22%3A%22Lepore%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vinzenco%22%2C%22lastName%22%3A%22Allocca%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Delia%22%2C%22lastName%22%3A%22Cusano%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22L%5Cu00e9onard%22%2C%22lastName%22%3A%22El-Hokayem%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Pantaleone%22%2C%22lastName%22%3A%22De%20Vita%22%7D%5D%2C%22abstractNote%22%3A%22Remote%20sensing%20is%20recognized%20as%20the%20most%20feasible%20means%20to%20provide%20regional%20information%20on%20land%20surfaces%20and%20monitor%20soil%20parameters%20such%20as%20soil%20moisture%20and%20evapotranspiration.%20The%20use%20of%20satellite-derived%20products%20can%20be%20crucial%20for%20groundwater%20resources%20in%20karst%20aquifers%2C%20particularly%20in%20regions%2C%20such%20as%20southern%20Italy%2C%20where%20groundwater%20availability%20drives%20economic%20and%20social%20development%20and%20there%20is%20a%20lack%20of%20monitored%20data.%20This%20study%20aims%20to%20expand%20the%20classical%20hydrogeological%20approach%2C%20used%20for%20the%20estimation%20of%20groundwater%20recharge%20of%20karst%20aquifers%2C%20to%20the%20understanding%20of%20the%20hydrological%20role%20of%20soil%20coverings%20by%20the%20integration%20of%20field%20monitoring%20and%20products%20derived%20by%20remotely%20sensed%20data.%20The%20research%20was%20conducted%20on%20the%20representative%20Mts.%20Soprano-Vesole-Chianello%20karst%20aquifer%20%28Campania%2C%20southern%20Italy%29.%20Copernicus%20Global%20Land%20Services%20Soil%20Water%20Index%20%28SWI%29%20and%20Moderate%20Resolution%20Imaging%20Spectroradiometer%20%28MODIS%29%20Evapotranspiration%20products%20were%20explored%20to%20assess%20soil%20water%20content%20and%20evapotranspiration%20regimes.%20The%20analysis%20included%20time%20series%20gathered%20by%20a%20monitoring%20network%20consisting%20of%205%20soil%20moisture%20multi-profile%20probes%2C%20working%20since%202021.%20The%20SWI1km%20provides%20daily%20soil%20water%20content%20information%20at%201%20km%20resolution.%20Depending%20on%20the%20uncertain%20calculation%2C%20not%20considering%20evapotranspiration%20and%20soil%20texture%2C%20the%20SWI1km%20product%20provides%208-SWI%20estimations%20and%20the%20related%20quality%20factor%20values.%20Instead%2C%20the%20MOD16A2%20is%20based%20on%20MODIS%20data%20and%20provides%208-day%20evapotranspiration%20estimation%20at%200.5%20km%20resolution.%20The%20product%20collection%20is%20based%20on%20the%20logic%20of%20the%20Penman-Monteith%20equation%2C%20which%20integrates%20inputs%20of%20daily%20meteorological%20re-analysis%20data%20along%20with%20products%20derived%20by%20%28MODIS%29%20including%20vegetation%20property%20dynamics%2C%20albedo%2C%20and%20land%20cover.%5Cn%5CnBoth%20products%20showed%20zones%20of%20no-data%20occurring%20across%20the%20mountain%20areas%20of%20the%20karst%20aquifers.%20This%20limitation%20is%20related%20to%20the%20algorithms%20that%20consider%20several%20parameters%20such%20as%20topography%20%28slope%20aspect%20and%20angle%29%20and%20occurrence%20of%20clouds%20for%20product%20generation.%5Cn%5CnThe%20primary%20outcome%20of%20this%20study%20was%20the%20extraction%20of%20SWI%20values%20and%20the%20calculation%20of%20a%20mean%20value%20for%20the%208-SWI%20values%2C%20weighted%20by%20the%20related%20quality%20factor%20%28SWIw%29.%20SWIw%20showed%20a%20constant%20difference%20of%20about%20-20%25%20in%20comparison%20to%20the%20daily%20average%20values%20obtained%20by%20field%20monitoring.%20Despite%20this%20discrepancy%2C%20the%20annual%20trend%20of%20the%20SWIw%20was%20found%20being%20very%20consistent%20with%20the%20soil%20moisture%20probe%20measurements%20%28corr.%20%26gt%3B%200.68%29%20and%20displaying%20a%20good%20response%20to%20rainfall%20events.%5Cn%5CnMoreover%2C%20the%20MODIS%20ET%20data%20displayed%20the%20expected%20pattern%20of%20evapotranspiration%20with%20a%20temporal%20resolution%20not%20achievable%20in%20other%20ways%20considering%20the%20lack%20of%20local%20meteorological%20data.%5Cn%5CnIn%20order%20to%20cope%20with%20missing%20data%20across%20the%20mountain%20areas%20of%20the%20karst%20aquifer%2C%20a%20spatial%20interpolation%20of%20SWIw%20and%20MODIS%20ET%20was%20carried%20out%20by%20different%20geostatistical%20techniques.%5Cn%5CnThe%20findings%20suggest%20that%20SWI1km%20and%20MODIS16A2%20are%20useful%20in%20monitoring%20soil%20water%20content%20and%20evapotranspiration%20of%20soils%20covering%20karst%20aquifers%20and%20controlling%20groundwater%20recharge.%20Although%20there%20are%20limitations%20due%20to%20missing%20data%2C%20both%20products%20can%20be%20still%20effectively%20utilized%20if%20properly%20interpolated.%20Therefore%2C%20they%20can%20be%20considered%20fundamental%20for%20assessing%20patterns%20of%20groundwater%20recharge%20in%20karst%20aquifers%2C%20especially%20in%20areas%20which%20are%20not%20extensively%20monitored%20as%20in%20the%20case%20of%20southern%20Italy.%22%2C%22date%22%3A%222023-06-15%22%2C%22proceedingsTitle%22%3A%22%22%2C%22conferenceName%22%3A%22A%20European%20vision%20for%20hydrological%20observations%20and%20experimentation%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.5194%5C%2Fegusphere-gc8-hydro-65%2C%202023%22%2C%22ISBN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A24Z%22%7D%7D%2C%7B%22key%22%3A%2294IK4ZUN%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Conrad%20et%20al.%22%2C%22parsedDate%22%3A%222023-06-12%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BConrad%2C%20C.%2C%20Schlaak%2C%20J.%2C%20Schmelzer%2C%20J.%20and%20L%26%23xF6%3Bw%2C%20J.%20%282023%29%20Downscaling%20and%20Validation%20of%201km%20ESA%20Soil%20Water%20Index%20for%20Soil%20Moisture%20Monitoring%20on%20Agricultural%20Land%20in%20Temperate%20Climate%20Conditions.%20EGU%2C%20Naples.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2Fhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.5194%5C%2Fegusphere-gc8-hydro-97%2C%202023%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2Fhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.5194%5C%2Fegusphere-gc8-hydro-97%2C%202023%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22Downscaling%20and%20validation%20of%201km%20ESA%20Soil%20Water%20Index%20for%20soil%20moisture%20monitoring%20on%20agricultural%20land%20in%20temperate%20climate%20conditions%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julian%22%2C%22lastName%22%3A%22Schlaak%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22Schmelzer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%5D%2C%22abstractNote%22%3A%22Near-surface%20soil%20moisture%20is%20an%20important%20parameter%20for%20estimating%20the%20water%20balance%20of%20ecosystems%2C%20especially%20for%20the%20exchange%20of%20water%20between%20atmosphere%20and%20soil.%20In%20the%20past%20decades%2C%20global%20and%20continental%20products%2C%20e.g.%20the%20Soil%20Water%20Index%20%28SWI%29%20of%20ESA%2C%20have%20been%20developed%20for%20large-scale%20monitoring%20from%20passive%20and%20active%20microwave%20data.%20ESA%20SWI%20was%20developed%20for%20Europe%20based%20on%20the%20surface%20soil%20moisture%20product%20derived%20from%20Sentinel-1%20C-band%20SAR%20data%20%281km%20resolution%29%20and%20Metop%20ASCAT%20surface%20soil%20moisture%20%2812.5km%29.%20However%2C%20for%20practical%2C%20small-scale%20applications%20on%20the%20local%20level%2C%20there%20is%20currently%20little%20data%20available.%20This%20contribution%20elaborates%20on%20the%20validation%20of%20the%20SWI%20for%20temperate%20agricultural%20regions%20at%20the%20example%20of%20the%20agrometeorological%20network%20of%20the%20JECAM%20test%20site%20DEMMIN%20in%20Northeast%20Germany.%20For%20this%20purpose%2C%20two%20resampling%20methods%2C%20a%20bilinear%20interpolation%20and%20a%20statistical%20downscaling%20approach%20using%20Random%20Forest%20were%20tested%20on%20SWI%20data%20from%202019.%20The%20statistical%20downscaling%20approach%20integrates%20Sentinel%20satellite%20data%20and%20the%20Topographical%20Wetness%20Index%20based%20on%20a%2010m%20resolved%20elevation%20model.%20Both%20resampling%20methods%20showed%20similar%20results.%20Over%20time%2C%20the%20SWI%20significantly%20overestimates%20the%20in%20situ%20data%20before%20and%20after%20the%20crop%20growing%20season.%20A%20higher%20agreement%20is%20observed%20in%20the%20summer%20months.%20For%2019%20of%20the%2029%20investigated%20agrometeorological%20stations%20a%20statistically%20positive%20correlation%20with%20R%26gt%3B0.5%20was%20found.%20The%20remaining%20stations%20showed%20little%20to%20no%20correlation%2C%20most%20likely%20due%20influences%20of%20various%20crops%20types%20on%20the%20remote%20sensing%20data.%20The%20results%20suggest%20a%20temporally%20limited%20applicability%20of%20the%20SWI%201km%20data%20for%20local%20assessments%20of%20soil%20moisture.%22%2C%22date%22%3A%222023-06-12%22%2C%22proceedingsTitle%22%3A%22%22%2C%22conferenceName%22%3A%22A%20European%20vision%20for%20hydrological%20observations%20and%20experimentation%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.5194%5C%2Fegusphere-gc8-hydro-97%2C%202023%22%2C%22ISBN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A30Z%22%7D%7D%2C%7B%22key%22%3A%22PGJIX2U3%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222022-10-06%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Hill%2C%20S.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282022%29%20Assessing%20the%20Applicability%20of%20Interferometric%20and%20Polarimetric%20Time%20Series%20Derived%20from%20Sentinel-1%20for%20Tracking%20Phenological%20Developments%20of%20Crops%20at%20the%20JECAM%20Site%20DEMMIN%20%28Germany%29.%20Arbeitskreis%20Fernerkundung%2C%20Halle%20%28Saale%29.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22Assessing%20the%20applicability%20of%20interferometric%20and%20polarimetric%20time%20series%20derived%20from%20Sentinel-1%20for%20tracking%20phenological%20developments%20of%20crops%20at%20the%20JECAM%20site%20DEMMIN%20%28Germany%29.%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222022-10-06%22%2C%22proceedingsTitle%22%3A%22Arbeitskreis%20Fernerkundung%22%2C%22conferenceName%22%3A%22Arbeitskreis%20Fernerkundung%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22ISBN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A37Z%22%7D%7D%2C%7B%22key%22%3A%22SAQ3VB47%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222022-05-25%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Hill%2C%20S.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282022%29%20Tracking%20the%20Phenological%20Developments%20of%20Crops%20by%20a%20Complementary%20Set%20of%20Interferometric%20and%20Polarimetric%20Time%20Series%20Derived%20from%20Sentinel-1%20at%20the%20JECAM%20Site%20DEMMIN%20%28Germany%29.%20ESA%20Living%20Planet%20Symposium%2C%20Bonn.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22Tracking%20the%20phenological%20developments%20of%20crops%20by%20a%20complementary%20set%20of%20interferometric%20and%20polarimetric%20time%20series%20derived%20from%20Sentinel-1%20at%20the%20JECAM%20site%20DEMMIN%20%28Germany%29%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Hill%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222022-05-25%22%2C%22proceedingsTitle%22%3A%22ESA%20Living%20Planet%20Symposium%22%2C%22conferenceName%22%3A%22ESA%20Living%20Planet%20Symposium%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22ISBN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A43Z%22%7D%7D%2C%7B%22key%22%3A%22IGM6TEHD%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222021-07-01%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20J.%2C%20Ullmann%2C%20T.%20and%20Conrad%2C%20C.%20%282021%29%20The%20Impact%20of%20Phenological%20Developments%20on%20Interferometric%20and%20Polarimetric%20Crop%20Signatures%20Derived%20from%20Sentinel-1%3A%20Examples%20from%20the%20DEMMIN%20Study%20Site%20%28Germany%29.%20%26lt%3Bi%26gt%3BRemote%20Sensing%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B13%26lt%3B%5C%2Fb%26gt%3B%2C%202951.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs13152951%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs13152951%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22The%20Impact%20of%20Phenological%20Developments%20on%20Interferometric%20and%20Polarimetric%20Crop%20Signatures%20Derived%20from%20Sentinel-1%3A%20Examples%20from%20the%20DEMMIN%20Study%20Site%20%28Germany%29%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tobias%22%2C%22lastName%22%3A%22Ullmann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22This%20study%20explores%20the%20potential%20of%20Sentinel-1%20Synthetic%20Aperture%20Radar%20%28SAR%29%20to%20identify%20phenological%20phases%20of%20wheat%2C%20sugar%20beet%2C%20and%20canola.%20Breakpoint%20and%20extreme%20value%20analyses%20were%20applied%20to%20a%20dense%20time%20series%20of%20interferometric%20%28InSAR%29%20and%20polarimetric%20%28PolSAR%29%20features%20recorded%20during%20the%20growing%20season%20of%202017%20at%20the%20JECAM%20site%20DEMMIN%20%28Germany%29.%20The%20analyses%20of%20breakpoints%20and%20extrema%20allowed%20for%20the%20distinction%20of%20vegetative%20and%20reproductive%20stages%20for%20wheat%20and%20canola.%20Certain%20phenological%20stages%2C%20measured%20in%20situ%20using%20the%20BBCH-scale%2C%20such%20as%20leaf%20development%20and%20rosette%20growth%20of%20sugar%20beet%20or%20stem%20elongation%20and%20ripening%20of%20wheat%2C%20were%20detectable%20by%20a%20combination%20of%20InSAR%20coherence%2C%20polarimetric%20Alpha%20and%20Entropy%2C%20and%20backscatter%20%28VV%5C%2FVH%29.%20Except%20for%20some%20fringe%20cases%2C%20the%20temporal%20difference%20between%20in%20situ%20observations%20and%20breakpoints%20or%20extrema%20ranged%20from%20zero%20to%20five%20days.%20Backscatter%20produced%20the%20signature%20that%20generated%20the%20most%20breakpoints%20and%20extrema.%20However%2C%20certain%20micro%20stadia%2C%20such%20as%20leaf%20development%20of%20BBCH%2010%20of%20sugar%20beet%20or%20flowering%20BBCH%2069%20of%20wheat%2C%20were%20only%20identifiable%20by%20the%20InSAR%20coherence%20and%20Alpha.%20Hence%2C%20it%20is%20concluded%20that%20combining%20PolSAR%20and%20InSAR%20features%20increases%20the%20number%20of%20detectable%20phenological%20events%20in%20the%20phenological%20cycles%20of%20crops.%22%2C%22date%22%3A%222021-07-01%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.3390%5C%2Frs13152951%22%2C%22ISSN%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.mdpi.com%5C%2F2072-4292%5C%2F13%5C%2F15%5C%2F2951%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A54Z%22%7D%7D%2C%7B%22key%22%3A%22TKY8L5JX%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Nu%5Cu00dfbaum%20et%20al.%22%2C%22parsedDate%22%3A%222020-03-23%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BNu%26%23xDF%3Bbaum%2C%20P.%2C%20Somogyv%26%23xE1%3Bri%2C%20M.%2C%20Bresinsky%2C%20L.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20Sch%26%23xF6%3Bnbrodt-Stitt%2C%20S.%2C%20Sauter%2C%20M.%2C%20Conrad%2C%20C.%20and%20Engelhardt%2C%20I.%20%282020%29%20Vulnerability%20Assessment%20of%20Karst%20Aquifers%20under%20Mediterranean%20Climates.%20other%2C%20oral.%20https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.5194%5C%2Fegusphere-egu2020-5112.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22report%22%2C%22title%22%3A%22Vulnerability%20assessment%20of%20karst%20aquifers%20under%20Mediterranean%20climates%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Philipp%22%2C%22lastName%22%3A%22Nu%5Cu00dfbaum%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22M%5Cu00e1rk%22%2C%22lastName%22%3A%22Somogyv%5Cu00e1ri%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lysander%22%2C%22lastName%22%3A%22Bresinsky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sarah%22%2C%22lastName%22%3A%22Sch%5Cu00f6nbrodt-Stitt%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Martin%22%2C%22lastName%22%3A%22Sauter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Irina%22%2C%22lastName%22%3A%22Engelhardt%22%7D%5D%2C%22abstractNote%22%3A%22%26lt%3Bp%26gt%3BCarbonate%20aquifers%20supply%20freshwater%20to%20about%20one-quarter%20of%20the%20world%20population.%20Their%20particular%20hydrodynamic%20behavior%20is%20a%20valuable%20property%20for%20groundwater%20extraction%2C%20on%20the%20downside%2C%20carbonate%20aquifers%20are%20vulnerable%20to%20overexploitation%20and%20pollution.%20Fractures%2C%20fissures%2C%20and%20typical%20karst%20features%2C%20such%20as%26amp%3B%23160%3B%20conduits%20and%20vertical%20shafts%2C%20create%20high%20regional%20hydraulic%20conductivities%20and%20fast%20response%20times%20to%20hydrological%20events%2C%20complicating%20numerical%20modeling%20and%20management%20of%20carbonate%20aquifers%20in%20general.%20Here%2C%20we%20develop%20a%20new%20method%20to%20assess%20the%20vulnerability%20of%20Mediterranean%20karst%20aquifers%20concerning%20shifts%20in%20climate.%20Particularly%2C%20we%20are%20interested%20in%201%29%20which%20types%20of%20karst%20aquifers%20are%20most%20vulnerable%20and%202%29%20which%20factors%20have%20the%20highest%20impact%20on%20their%20climate%20vulnerability.%26lt%3B%5C%2Fp%26gt%3B%26lt%3Bp%26gt%3BOur%20approach%20is%20based%20on%20a%20vulnerability%20index%2C%20which%20is%20calculated%20from%20selected%20indicators%20of%20aquifer%20behavior%20that%20refer%20to%20land%20cover%2C%20soil%20types%2C%20wetlands%2C%20water%20demand%2C%20current%20change%20of%20groundwater%20levels%2C%20total%20water%20volume%2C%20run-off%2C%20water%20exploitation%20index%2C%20and%20freshwater%20production.%20First%2C%20we%20calculate%20vulnerability%20indices%20for%20all%20karst%20aquifers%20%26amp%3B%238211%3B%20as%20identified%20in%20the%20World%20Karst%20Aquifer%20Map%20by%20the%20World-wide%20Hydrogeological%20Mapping%20and%20Assessment%20Programme%20%28WHYMAP%20WOKAM%20v1%20database%3B%20Chen%20et%20al.%2C%202017%29%20%26amp%3B%238211%3B%20that%20have%20at%20least%2090%25%20of%20their%20area%20belonging%20to%20Mediterranean%20climate%20zones%20%28Csa%2C%20Csb%2C%20and%20Csc%29.%20Then%2C%20we%20group%20these%20aquifers%20into%20classes%20representing%20different%20physical%20behaviors%20and%20morphological%20characteristics%20%28e.g.%20highly%20karstified%20systems%20in%20mountainous%20areas%29.%26lt%3B%5C%2Fp%26gt%3B%26lt%3Bp%26gt%3BAn%20evident%20approach%20to%20investigate%20various%20aquifers%20in%20terms%20of%20their%20vulnerability%20is%20the%20development%20of%20numerical%20flow%20models.%20The%20advantage%20is%20that%20the%20boundary%20conditions%2C%20such%20as%20average%20annual%20precipitation%20and%20temperature%2C%20can%20be%20modified%20to%20consider%20different%20climatic%20scenarios.%20Thus%2C%20the%20resulting%20impact%20on%20water%20volumes%20and%20the%20aquifer%20response%20can%20be%20simulated%20accordingly.%20However%2C%20this%20approach%20requires%20large%20amounts%20of%20data%20and%20high%20computational%20costs.%26lt%3B%5C%2Fp%26gt%3B%26lt%3Bp%26gt%3BOur%20method%20uses%20selected%20sets%20of%20karst%20aquifers%20representing%20different%20variations%20of%20Mediterranean%20climates%20%28i.e.%20that%20are%20similar%20in%20terms%20of%20temperature%20and%20precipitation%20patterns%29.%20These%20aquifers%20are%20compared%20by%20analyzing%20and%20plotting%20regional%20climate%20variables%20versus%20previously%20calculated%20vulnerability%20indices.%20By%20identifying%20and%20comparing%20climate-vulnerability%20relations%20within%20aquifer%20sets%2C%20we%20can%20mimic%20changes%20in%20climate%20for%20individual%20aquifers%20in%20line%20with%20the%20RCP4.5%20scenario%20until%202050.%20This%20approach%2C%20which%20relies%20on%20present-day%20observed%20conditions%2C%20allows%20us%20to%20predict%20the%20effect%20of%20a%20changing%20climate%20on%20the%20vulnerability%20of%20an%20aquifer%20class%20without%20the%20need%20to%20develop%20a%20complex%20numerical%20model.%26lt%3B%5C%2Fp%26gt%3B%26lt%3Bp%26gt%3BThe%20results%20are%20visualized%20in%20the%20form%20of%20vulnerability%20maps%20and%20used%20to%20derive%20recommendations%20for%20the%20sustainable%20management%20of%20karst%20aquifers%20under%20Mediterranean%20climates.%26lt%3B%5C%2Fp%26gt%3B%22%2C%22reportNumber%22%3A%22%22%2C%22reportType%22%3A%22other%22%2C%22institution%22%3A%22oral%22%2C%22date%22%3A%222020-03-23%22%2C%22language%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fmeetingorganizer.copernicus.org%5C%2FEGU2020%5C%2FEGU2020-5112.html%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A42%3A29Z%22%7D%7D%2C%7B%22key%22%3A%22ZPLEQ66D%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Sch%5Cu00f6nbrodt-Stitt%20et%20al.%22%2C%22parsedDate%22%3A%222018%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BSch%26%23xF6%3Bnbrodt-Stitt%2C%20S.%2C%20Conrad%2C%20C.%2C%20Dimov%2C%20D.%2C%20Ergashev%2C%20I.%2C%20L%26%23xF6%3Bw%2C%20F.%2C%20Morper-Busch%2C%20L.%2C%20Muminov%2C%20S.%2C%20Ruziev%2C%20I.%2C%20Schorcht%2C%20G.%2C%20Solodky%2C%20G.%2C%20Sorokin%2C%20A.%2C%20Sorokin%2C%20D.%2C%20Stulina%2C%20G.%2C%20Toshpulatov%2C%20R.%2C%20Zaitov%2C%20S.%2C%20Kitapbayev%2C%20A.%20and%20Unger-Shayesteh%2C%20K.%20%282018%29%20The%20WUEMoCA%20Tool%20for%20Monitoring%20Irrigated%20Cropland%20Use%20and%20Water%20Use%20Efficiency%20at%20the%20Landscape%20Level%20of%20the%20Aral%20Sea%20Basin.%20In%3A%20FSBSI%20%26%23x201C%3BPryanishnikov%20Institute%20of%20Agrochemistry%2C%26%23x201D%3B%20Ed.%2C%20Novel%20Methods%20and%20Results%20of%20Landscape%20Research%20in%20Europe%2C%20Central%20Asia%20and%20Siberia%2C%20Vol.%204%20Optimising%20Agricultural%20Landscapes%2C%20Moscow%2C%20351%26%23x2013%3B356.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22bookSection%22%2C%22title%22%3A%22The%20WUEMoCA%20Tool%20for%20Monitoring%20Irrigated%20Cropland%20Use%20and%20Water%20Use%20Efficiency%20at%20the%20Landscape%20Level%20of%20the%20Aral%20Sea%20Basin%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sarah%22%2C%22lastName%22%3A%22Sch%5Cu00f6nbrodt-Stitt%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Dimo%22%2C%22lastName%22%3A%22Dimov%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ikrom%22%2C%22lastName%22%3A%22Ergashev%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lucia%22%2C%22lastName%22%3A%22Morper-Busch%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sherzod%22%2C%22lastName%22%3A%22Muminov%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Islom%22%2C%22lastName%22%3A%22Ruziev%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Gunther%22%2C%22lastName%22%3A%22Schorcht%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Georgy%22%2C%22lastName%22%3A%22Solodky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anatoly%22%2C%22lastName%22%3A%22Sorokin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Denis%22%2C%22lastName%22%3A%22Sorokin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Galina%22%2C%22lastName%22%3A%22Stulina%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rustam%22%2C%22lastName%22%3A%22Toshpulatov%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sherzod%22%2C%22lastName%22%3A%22Zaitov%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Almas%22%2C%22lastName%22%3A%22Kitapbayev%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Katy%22%2C%22lastName%22%3A%22Unger-Shayesteh%22%7D%2C%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22%22%2C%22lastName%22%3A%22FSBSI%20%5C%22Pryanishnikov%20Institute%20of%20Agrochemistry%5C%22%22%7D%5D%2C%22abstractNote%22%3A%22Water%20scarcity%20in%20the%20Aral%20Sea%20Basin%20together%20with%20the%20persistent%20dependency%20from%20agricultural%20production%20as%20well%20as%20with%20the%20effects%20of%20population%20growth%20and%20climate%20change%20is%20supposed%20to%20imply%20future%20conflicts%20in%20all%20water-use%20sectors.%20An%20efficient%20and%20sustainable%20irrigation%20agriculture%20will%20essentially%20contribute%20to%20sustainable%20regional%20development.%20Optical%20satellite%20remote%20sensing%20%28RS%29%20data%20such%20as%20MODIS%20provides%20necessary%20information%20for%20monitoring%20irrigated%20cropland%20use%20on%20the%20regional%2C%20respectively%20landscape%20scale.%20In%20this%20context%2C%20the%20WUEMoCA%20tool%20intends%20to%20provide%20agriculturally%20relevant%2C%20spatio-temporal%20geoinformation%20to%20support%20planning%20in%20the%20water%20resources%20management%20sector.%20Potential%20groups%20of%20end-users%20comprise%20policy%20makers%20and%20advisors%20from%20national%20governments%20but%20also%20regional%20and%20transboundary%20decision%20makers%20and%20specialists%20dealing%20with%20geoinformation%20technology%20and%20RS%20based%20analysis%20for%20sustainable%20land%20and%20water%20resources%20management.%22%2C%22bookTitle%22%3A%22Novel%20Methods%20and%20Results%20of%20Landscape%20Research%20in%20Europe%2C%20Central%20Asia%20and%20Siberia%2C%20Vol.%204%20Optimising%20Agricultural%20Landscapes%22%2C%22date%22%3A%222018%22%2C%22language%22%3A%22%22%2C%22ISBN%22%3A%22978-5-9238-0246-7%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222021-12-02T09%3A34%3A55Z%22%7D%7D%2C%7B%22key%22%3A%22CVV3YJ5Y%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222017%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20F.%2C%20Biradar%2C%20C.%2C%20Fliemann%2C%20E.%2C%20Lamers%2C%20J.P.A.%20and%20Conrad%2C%20C.%20%282017%29%20Assessing%20Gaps%20in%20Irrigated%20Agricultural%20Productivity%20through%20Satellite%20Earth%20Observations%26%23x2014%3BA%20Case%20Study%20of%20the%20Fergana%20Valley%2C%20Central%20Asia.%20%26lt%3Bi%26gt%3BInternational%20Journal%20of%20Applied%20Earth%20Observation%20and%20Geoinformation%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B59%26lt%3B%5C%2Fb%26gt%3B%2C%20118%26%23x2013%3B134.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.jag.2017.02.014%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.jag.2017.02.014%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Assessing%20gaps%20in%20irrigated%20agricultural%20productivity%20through%20satellite%20earth%20observations%5Cu2014A%20case%20study%20of%20the%20Fergana%20Valley%2C%20Central%20Asia%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Chandrashekhar%22%2C%22lastName%22%3A%22Biradar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Elisabeth%22%2C%22lastName%22%3A%22Fliemann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John%20P.%20A.%22%2C%22lastName%22%3A%22Lamers%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22Improving%20crop%20area%20and%5C%2For%20crop%20yields%20in%20agricultural%20regions%20is%20one%20of%20the%20foremost%20scientific%20challenges%20for%20the%20next%20decades.%20This%20is%20especially%20true%20in%20irrigated%20areas%20because%20sustainable%20intensification%20of%20irrigated%20crop%20production%20is%20virtually%20the%20sole%20means%20to%20enhance%20food%20supply%20and%20contribute%20to%20meeting%20food%20demands%20of%20a%20growing%20population.%20Yet%2C%20irrigated%20crop%20production%20worldwide%20is%20suffering%20from%20soil%20degradation%20and%20salinity%2C%20reduced%20soil%20fertility%2C%20and%20water%20scarcity%20rendering%20the%20performance%20of%20irrigation%20schemes%20often%20below%20potential.%20On%20the%20other%20hand%2C%20the%20scope%20for%20improving%20irrigated%20agricultural%20productivity%20remains%20obscure%20also%20due%20to%20the%20lack%20of%20spatial%20data%20on%20agricultural%20production%20%28e.g.%20crop%20acreage%20and%20yield%29.%20To%20fill%20this%20gap%2C%20satellite%20earth%20observations%20and%20a%20replicable%20methodology%20were%20used%20to%20estimate%20crop%20yields%20at%20the%20field%20level%20for%20the%20period%202010%5C%2F2014%20in%20the%20Fergana%20Valley%2C%20Central%20Asia%2C%20to%20understand%20the%20response%20of%20agricultural%20productivity%20to%20factors%20related%20to%20the%20irrigation%20and%20drainage%20infrastructure%20and%20environment.%20The%20results%20showed%20that%20cropping%20pattern%2C%20i.e.%20the%20presence%20or%20absence%20of%20multi-annual%20crop%20rotations%2C%20and%20spatial%20diversity%20of%20crops%20had%20the%20most%20persistent%20effects%20on%20crop%20yields%20across%20observation%20years%20suggesting%20the%20need%20for%20introducing%20sustainable%20cropping%20systems.%20On%20the%20other%20hand%2C%20areas%20with%20a%20lower%20crop%20diversity%20or%20abundance%20of%20crop%20rotation%20tended%20to%20have%20lower%20crop%20yields%2C%20with%20differences%20of%20partly%20more%20than%20one%20t%5C%2Fha%20yield.%20It%20is%20argued%20that%20factors%20related%20to%20the%20infrastructure%2C%20for%20example%2C%20the%20distance%20of%20farms%20to%20the%20next%20settlement%20or%20the%20density%20of%20roads%2C%20had%20a%20persistent%20effect%20on%20crop%20yield%20dynamics%20over%20time.%20The%20improvement%20potential%20of%20cotton%20and%20wheat%20yields%20were%20estimated%20at%205%25%2C%20compared%20to%20crop%20yields%20of%20farms%20in%20the%20direct%20vicinity%20of%20settlements%20or%20roads.%20In%20this%20study%20it%20is%20highlighted%20how%20remotely%20sensed%20estimates%20of%20crop%20production%20in%20combination%20with%20geospatial%20technologies%20provide%20a%20unique%20perspective%20that%2C%20when%20combined%20with%20field%20surveys%2C%20can%20support%20planners%20to%20identify%20management%20priorities%20for%20improving%20regional%20production%20and%5C%2For%20reducing%20environmental%20impacts.%22%2C%22date%22%3A%222017%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.jag.2017.02.014%22%2C%22ISSN%22%3A%2203032434%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A29%3A04Z%22%7D%7D%2C%7B%22key%22%3A%22I2NG2IUT%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Conrad%20et%20al.%22%2C%22parsedDate%22%3A%222017%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BConrad%2C%20C.%2C%20L%26%23xF6%3Bw%2C%20F.%20and%20Lamers%2C%20J.P.A.%20%282017%29%20Mapping%20and%20Assessing%20Crop%20Diversity%20in%20the%20Irrigated%20Fergana%20Valley%2C%20Uzbekistan.%20%26lt%3Bi%26gt%3BApplied%20Geography%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B86%26lt%3B%5C%2Fb%26gt%3B%2C%20102%26%23x2013%3B117.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.apgeog.2017.06.016%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.apgeog.2017.06.016%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Mapping%20and%20assessing%20crop%20diversity%20in%20the%20irrigated%20Fergana%20Valley%2C%20Uzbekistan%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John%20P.%20A.%22%2C%22lastName%22%3A%22Lamers%22%7D%5D%2C%22abstractNote%22%3A%22Crop%20diversity%20%28e.g.%20the%20number%20of%20agricultural%20crop%20types%20and%20the%20level%20of%20evenness%20in%20area%20distribution%29%20in%20the%20agricultural%20systems%20of%20arid%20Central%20Asia%20has%20recently%20been%20increased%20mainly%20to%20achieve%20food%20security%20of%20the%20rural%20population%2C%20however%2C%20not%20throughout%20the%20irrigation%20system.%20Site-specific%20factors%20that%20promote%20or%20hamper%20crop%20diversification%20after%20the%20dissolvent%20of%20the%20Soviet%20Union%20have%20hardly%20been%20assessed%20yet.%20While%20tapping%20the%20potential%20of%20remote%20sensing%2C%20the%20objective%20was%20to%20map%20and%20explain%20spatial%20patterns%20of%20current%20crop%20diversity%20by%20the%20example%20of%20the%20irrigated%20agricultural%20landscapes%20of%20the%20Fergana%20Valley%2C%20Uzbekistan.%20Multi-temporal%20Landsat%20and%20RapidEye%20satellite%20data%20formed%20the%20basis%20for%20creating%20annual%20and%20multi-annual%20crop%20maps%20for%202010%5Cu20132012%20while%20using%20supervised%20classifications.%20Applying%20the%20Simpson%20index%20of%20diversity%20%28SID%29%20to%20circular%20buffers%20with%20radii%20of%201.5%20and%205%20km%20elucidated%20the%20spatial%20distribution%20of%20crop%20diversity%20at%20both%20the%20local%20and%20landscape%20spatial%20scales.%20A%20variable%20importance%20analysis%2C%20rooted%20in%20the%20conditional%20forest%20algorithm%2C%20investigated%20potential%20environmental%20and%20socio-economic%20drivers%20of%20the%20spatial%20patterns%20of%20crop%20diversity.%20Overall%20accuracy%20of%20the%20annual%20crop%20maps%20ranged%20from%200.84%20to%200.86%20whilst%20the%20SID%20varied%20between%200.1%20and%200.85.%20The%20findings%20confirmed%20the%20existence%20of%20areas%20under%20monocultures%20as%20well%20as%20of%20crop%20diverse%20patches.%20Higher%20crop%20diversity%20occurred%20in%20the%20more%20distal%20parts%20of%20the%20irrigation%20system%20and%20sparsely%20settled%20areas%2C%20especially%20due%20to%20orchards.%20In%20contrast%2C%20in%20water-secure%20and%20densely%20settled%20areas%2C%20cotton-wheat%20rotations%20dominated%20due%20to%20the%20state%20interventions%20in%20crop%20cultivation.%20Distances%20to%20irrigation%20infrastructure%2C%20settlements%20and%20the%20road%20network%20influenced%20crop%20diversity%20the%20most.%20Spatial%20explicit%20information%20on%20crop%20diversity%20per%20se%20has%20the%20potential%20to%20support%20policymaking%20and%20spatial%20planning%20towards%20crop%20diversification.%20Driver%20analysis%20as%20exemplified%20at%20the%20study%20region%20in%20Uzbekistan%20can%20help%20reaching%20the%20declared%20policy%20to%20increase%20crop%20diversity%20throughout%20the%20country%20and%20even%20beyond.%22%2C%22date%22%3A%222017%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.apgeog.2017.06.016%22%2C%22ISSN%22%3A%2201436228%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A29%3A00Z%22%7D%7D%2C%7B%22key%22%3A%22IEC93SM5%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Conrad%20et%20al.%22%2C%22parsedDate%22%3A%222016-07-29%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BConrad%2C%20C.%2C%20Sch%26%23xF6%3Bnbrodt-Stitt%2C%20S.%2C%20L%26%23xF6%3Bw%2C%20F.%2C%20Sorokin%2C%20D.%20and%20Paeth%2C%20H.%20%282016%29%20Cropping%20Intensity%20in%20the%20Aral%20Sea%20Basin%20and%20Its%20Dependency%20from%20the%20Runoff%20Formation%202000%26%23x2013%3B2012.%20%26lt%3Bi%26gt%3BRemote%20Sensing%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B8%26lt%3B%5C%2Fb%26gt%3B%2C%20630.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs8080630%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs8080630%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Cropping%20Intensity%20in%20the%20Aral%20Sea%20Basin%20and%20Its%20Dependency%20from%20the%20Runoff%20Formation%202000%5Cu20132012%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sarah%22%2C%22lastName%22%3A%22Sch%5Cu00f6nbrodt-Stitt%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Denis%22%2C%22lastName%22%3A%22Sorokin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Heiko%22%2C%22lastName%22%3A%22Paeth%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222016-07-29%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.3390%5C%2Frs8080630%22%2C%22ISSN%22%3A%222072-4292%22%2C%22url%22%3A%22http%3A%5C%2F%5C%2Fwww.mdpi.com%5C%2F2072-4292%5C%2F8%5C%2F8%5C%2F630%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222022-01-26T17%3A52%3A53Z%22%7D%7D%2C%7B%22key%22%3A%22CUJAV4C4%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Conrad%20et%20al.%22%2C%22parsedDate%22%3A%222016%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BConrad%2C%20C.%2C%20Lamers%2C%20J.P.A.%2C%20Ibragimov%2C%20N.%2C%20L%26%23xF6%3Bw%2C%20F.%20and%20Martius%2C%20C.%20%282016%29%20Analysing%20Irrigated%20Crop%20Rotation%20Patterns%20in%20Arid%20Uzbekistan%20by%20the%20Means%20of%20Remote%20Sensing%3A%20A%20Case%20Study%20on%20Post-Soviet%20Agricultural%20Land%20Use.%20%26lt%3Bi%26gt%3BJournal%20of%20Arid%20Environments%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B124%26lt%3B%5C%2Fb%26gt%3B%2C%20150%26%23x2013%3B159.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.jaridenv.2015.08.008%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.jaridenv.2015.08.008%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Analysing%20irrigated%20crop%20rotation%20patterns%20in%20arid%20Uzbekistan%20by%20the%20means%20of%20remote%20sensing%3A%20A%20case%20study%20on%20post-Soviet%20agricultural%20land%20use%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John%20P.%20A.%22%2C%22lastName%22%3A%22Lamers%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nazar%22%2C%22lastName%22%3A%22Ibragimov%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Martius%22%7D%5D%2C%22abstractNote%22%3A%22In%20Central%20Asia%2C%20actual%20cotton%20rotation%20practices%20are%20repeatedly%20believed%20to%20resemble%20%5Cu201cSoviet%20cropping%20conditions%5Cu201d%20with%20continuous%20cotton%20sequences%20of%20six%20years%20or%20more.%20We%20investigated%20current%20cotton%20growing%20patterns%20in%20Khorezm%2C%20one%20representative%20cotton%20production%20region%20in%20Uzbekistan%20utilizing%20time%20series%20of%20250-m%20MODIS%20satellite%20data.%20A%20Random%20Forest%20model%20was%20established%20using%20reference%20data%20of%202004%5Cu20132007%20to%20generate%20annual%20crop%20maps%20in%202000%5Cu20132009.%20A%20linear%20model%20was%20applied%20to%20assess%20the%20spatial%20distribution%20of%20the%20longest%20observed%20cotton%20sequence%20within%20the%20ten-year%20observation%20period.%20All%20cotton-growing%20sequences%20were%20compared%20to%20the%20national%20crop%20rotation%20recommendations.%20The%20classification%20achieved%20an%20overall%20accuracy%20of%2082%25.%20We%20found%20that%20cotton%20remains%20the%20major%20crop%20in%20the%20region.%20It%20was%20cultivated%20for%20more%20than%20five%20out%20of%20the%20ten%20years%20on%2046.5%25%20of%20the%20cropland.%20But%20%5Cu201cSoviet%20cropping%20conditions%5Cu201d%20on%20less%20than%2020%25%20and%20officially%20recommended%20cotton%20sequences%20on%20more%20than%2050%25%20of%20the%20cropland%20challenge%20the%20notion%20that%20cotton%20mono-crop%20dominates%20Central%20Asia.%20Statistical%20analysis%20revealed%20that%20long%20cotton%20sequences%20preferably%20occur%20on%20fields%20far%20from%20settlements%20and%20under%20reduced%20soil%20suitability%20for%20irrigation.%20The%20results%20enable%20decision%20makers%20to%20better%20explain%20unfavourable%20cotton%20cultivation%20practices%20and%20to%20stimulate%20improvements.%22%2C%22date%22%3A%222016%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.jaridenv.2015.08.008%22%2C%22ISSN%22%3A%2201401963%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A28%3A48Z%22%7D%7D%2C%7B%22key%22%3A%22J4SU7EHS%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Conrad%20et%20al.%22%2C%22parsedDate%22%3A%222015%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BConrad%2C%20C.%2C%20Rudloff%2C%20M.%2C%20Abdullaev%2C%20I.%2C%20Thiel%2C%20M.%2C%20L%26%23xF6%3Bw%2C%20F.%20and%20Lamers%2C%20J.P.A.%20%282015%29%20Measuring%20Rural%20Settlement%20Expansion%20in%20Uzbekistan%20Using%20Remote%20Sensing%20to%20Support%20Spatial%20Planning.%20%26lt%3Bi%26gt%3BApplied%20Geography%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B62%26lt%3B%5C%2Fb%26gt%3B%2C%2029%26%23x2013%3B43.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.apgeog.2015.03.017%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.apgeog.2015.03.017%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Measuring%20rural%20settlement%20expansion%20in%20Uzbekistan%20using%20remote%20sensing%20to%20support%20spatial%20planning%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22C.%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22M.%22%2C%22lastName%22%3A%22Rudloff%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22I.%22%2C%22lastName%22%3A%22Abdullaev%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22M.%22%2C%22lastName%22%3A%22Thiel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22F.%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22J.P.A.%22%2C%22lastName%22%3A%22Lamers%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%2208%5C%2F2015%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.apgeog.2015.03.017%22%2C%22ISSN%22%3A%2201436228%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Flinkinghub.elsevier.com%5C%2Fretrieve%5C%2Fpii%5C%2FS0143622815000831%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222022-01-26T17%3A52%3A17Z%22%7D%7D%2C%7B%22key%22%3A%22ZW3JKFWN%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222015%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20F.%2C%20Duveiller%2C%20G.%2C%20Conrad%2C%20C.%20and%20Michel%2C%20U.%20%282015%29%20Impact%20of%20Categorical%20and%20Spatial%20Scale%20on%20Supervised%20Crop%20Classification%20Using%20Remote%20Sensing.%20%26lt%3Bi%26gt%3BPhotogrammetrie%20-%20Fernerkundung%20-%20Geoinformation%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B2015%26lt%3B%5C%2Fb%26gt%3B%2C%207%26%23x2013%3B20.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1127%5C%2Fpfg%5C%2F2015%5C%2F0252%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1127%5C%2Fpfg%5C%2F2015%5C%2F0252%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Impact%20of%20Categorical%20and%20Spatial%20Scale%20on%20Supervised%20Crop%20Classification%20using%20Remote%20Sensing%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Gr%5Cu00e9gory%22%2C%22lastName%22%3A%22Duveiller%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ulrich%22%2C%22lastName%22%3A%22Michel%22%7D%5D%2C%22abstractNote%22%3A%22High%20temporal%20revisit%20frequency%20over%20vast%20geographic%20areas%20is%20necessary%20to%20properly%20use%20satellite%20earth%20observation%20for%20monitoring%20agricultural%20production.%20However%2C%20this%20often%20limits%20the%20spatial%20resolution%20that%20can%20be%20used.%20The%20challenge%20of%20discriminating%20pixels%20that%20correspond%20to%20a%20particular%20crop%20type%2C%20a%20prerequisite%20for%20crop%20specific%20monitoring%20remains%20daunting%20when%20the%20signal%20encoded%20in%20pixels%20stems%20from%20several%20land%20uses%20%28mixed%20pixels%29.%20Naturally%2C%20the%20concept%20of%20spatial%20scale%20arises%20but%20the%20issue%20of%20selecting%20a%20proper%20class%20legend%20%28the%20categorical%20scale%29%20should%20not%20be%20neglected.%20A%20framework%20is%20presented%20that%20addresses%20these%20issues%20and%20that%20can%20be%20used%20to%20quantitatively%20define%20pixel%20size%20requirements%20for%20crop%20identification%20and%20to%20assess%20the%20effect%20of%20categorical%20scale.%20The%20framework%20was%20applied%20over%20two%20agricultural%20landscapes.%20It%20was%20demonstrated%20that%20there%20was%20no%20unique%20spatial%20resolution%20that%20provided%20the%20best%20classification%20result%20for%20all%20classes%20at%20once%20at%20a%20given%20categorical%20scale.%20The%20suitability%20of%20pixel%20populations%20characterized%20by%20pixel%20size%20and%20purity%20differed%20for%20identifying%20specific%20crops%20within%20tested%20landscapes%2C%20and%20for%20one%20crop%20there%20were%20large%20differences%20among%20the%20landscapes.%20In%20the%20context%20of%20agricultural%20crop%20growth%20monitoring%20the%20framework%20described%20above%20can%20be%20used%20to%20draw%20guidelines%20for%20selecting%20appropriate%20imagery%2C%20e.g.%20suitable%20pixel%20sizes%2C%20and%20for%20selecting%20class%20legends%20suitable%20for%20accurate%20crop%20classification%20when%20the%20interest%20is%20only%20on%20pixels%20covering%20arable%20land%20as%20a%20prerequisite%20for%20crop%20specific%20monitoring.%20The%20framework%20could%20be%20used%20to%20plot%20the%20suitability%20%28or%20accuracy%29%20of%20pixels%20as%20a%20function%20of%20their%20purity%20to%20provide%20a%20spatial%20assessment%20of%20classification%20performance.%22%2C%22date%22%3A%222015%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1127%5C%2Fpfg%5C%2F2015%5C%2F0252%22%2C%22ISSN%22%3A%221432-8364%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A28%3A36Z%22%7D%7D%2C%7B%22key%22%3A%22CQ3UXHFL%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Lex%20et%20al.%22%2C%22parsedDate%22%3A%222015%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BLex%2C%20S.%2C%20Asam%2C%20S.%2C%20L%26%23xF6%3Bw%2C%20F.%20and%20Conrad%2C%20C.%20%282015%29%20Comparison%20of%20Two%20Statistical%20Methods%20for%20the%20Derivation%20of%20the%20Fraction%20of%20Absorbed%20Photosynthetic%20Active%20Radiation%20for%20Cotton.%20%26lt%3Bi%26gt%3BPhotogrammetrie%20-%20Fernerkundung%20-%20Geoinformation%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B2015%26lt%3B%5C%2Fb%26gt%3B%2C%2055%26%23x2013%3B67.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1127%5C%2Fpfg%5C%2F2015%5C%2F0250%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1127%5C%2Fpfg%5C%2F2015%5C%2F0250%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Comparison%20of%20two%20Statistical%20Methods%20for%20the%20Derivation%20of%20the%20Fraction%20of%20Absorbed%20Photosynthetic%20Active%20Radiation%20for%20Cotton%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sylvia%22%2C%22lastName%22%3A%22Lex%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sarah%22%2C%22lastName%22%3A%22Asam%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22The%20fraction%20of%20absorbed%20photosynthetic%20active%20radiation%20%28FAPAR%29%20is%20an%20important%20input%20for%20modelling%20biomass%20increase%20and%20agricultural%20yield%20and%20can%20be%20calculated%20based%20on%20optical%20remote%20sensing%20data.%20In%20this%20study%20two%20remote%20sensing%20based%20approaches%20to%20derive%20the%20FAPAR%20for%20irrigated%20cotton%20in%20Fergana%20valley%2C%20Uzbekistan%2C%20are%20tested%20and%20compared%3A%20%28i%29%20FAPAR%20rescale%20from%20the%20normalized%20difference%20vegetation%20index%20%28NDVI%29%20%28%5Cu201cpercentile%20approach%5Cu201d%29%2C%20and%20%28ii%29%20an%20empirical%20regression%20approach%20based%20on%20NDVI.%20In%20the%20rescaling%20approach%20FAPAR%20was%20derived%20by%20relating%20upper%20and%20lower%20percentiles%20derived%20from%20the%20NDVI%20distribution%20of%20cotton%20fields%20from%20the%20entire%20study%20area%20to%20fixed%20FAPAR%20minima%20%28bare%20soil%29%20and%20maxima.%20NDVI%20was%20derived%20from%20multi-temporal%206.5%20m%20RapidEye%20data%20acquired%20throughout%202011.%20For%20the%20regression%20approach%20FAPAR%20data%20was%20collected%20in%20situ%20from%20cotton%20fields%20during%20the%20vegetation%20season.%20The%20percentile%20approach%20delivered%20an%20RMSE%20of%200.10%20whilst%20regression%20was%20only%20slightly%20better%20with%20an%20RMSE%20of%200.07.%20Hence%2C%20the%20percentile%20approach%20could%20be%20concluded%20as%20being%20a%20fast%20and%20easy%20alternative%20to%20field%20data%20demanding%20empirical%20regressions%20for%20the%20derivation%20of%20FAPAR%20on%20cotton%20fields.%22%2C%22date%22%3A%222015%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1127%5C%2Fpfg%5C%2F2015%5C%2F0250%22%2C%22ISSN%22%3A%221432-8364%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A28%3A29Z%22%7D%7D%2C%7B%22key%22%3A%22FEFZZPSR%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222015%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20F.%2C%20Kn%26%23xF6%3Bfel%2C%20P.%20and%20Conrad%2C%20C.%20%282015%29%20Analysis%20of%20Uncertainty%20in%20Multi-Temporal%20Object-Based%20Classification.%20%26lt%3Bi%26gt%3BISPRS%20Journal%20of%20Photogrammetry%20and%20Remote%20Sensing%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B105%26lt%3B%5C%2Fb%26gt%3B%2C%2091%26%23x2013%3B106.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.isprsjprs.2015.03.004%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.isprsjprs.2015.03.004%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Analysis%20of%20uncertainty%20in%20multi-temporal%20object-based%20classification%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Patrick%22%2C%22lastName%22%3A%22Kn%5Cu00f6fel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22Agricultural%20management%20increasingly%20uses%20crop%20maps%20based%20on%20classification%20of%20remotely%20sensed%20data.%20However%2C%20classification%20errors%20can%20translate%20to%20errors%20in%20model%20outputs%2C%20for%20instance%20agricultural%20production%20monitoring%20%28yield%2C%20water%20demand%29%20or%20crop%20acreage%20calculation.%20Hence%2C%20knowledge%20on%20the%20spatial%20variability%20of%20the%20classier%20performance%20is%20important%20information%20for%20the%20user.%20But%20this%20is%20not%20provided%20by%20traditional%20assessments%20of%20accuracy%2C%20which%20are%20based%20on%20the%20confusion%20matrix.%20In%20this%20study%2C%20classification%20uncertainty%20was%20analyzed%2C%20based%20on%20the%20support%20vector%20machines%20%28SVM%29%20algorithm.%20SVM%20was%20applied%20to%20multi-spectral%20time%20series%20data%20of%20RapidEye%20from%20different%20agricultural%20landscapes%20and%20years.%20Entropy%20was%20calculated%20as%20a%20measure%20of%20classification%20uncertainty%2C%20based%20on%20the%20per-object%20class%20membership%20estimations%20from%20the%20SVM%20algorithm.%20Permuting%20all%20possible%20combinations%20of%20available%20images%20allowed%20investigating%20the%20impact%20of%20the%20image%20acquisition%20frequency%20and%20timing%2C%20respectively%2C%20on%20the%20classification%20uncertainty.%20Results%20show%20that%20multi-temporal%20datasets%20decrease%20classification%20uncertainty%20for%20different%20crops%20compared%20to%20single%20data%20sets%2C%20but%20there%20was%20no%20%5Cu201cone-image-combination-fits-all%5Cu201d%20solution.%20The%20number%20and%20acquisition%20timing%20of%20the%20images%2C%20for%20which%20a%20decrease%20in%20uncertainty%20could%20be%20realized%2C%20proved%20to%20be%20specific%20to%20a%20given%20landscape%2C%20and%20for%20each%20crop%20they%20differed%20across%20different%20landscapes.%20For%20some%20crops%2C%20an%20increase%20of%20uncertainty%20was%20observed%20when%20increasing%20the%20quantity%20of%20images%2C%20even%20if%20classification%20accuracy%20was%20improved.%20Random%20forest%20regression%20was%20employed%20to%20investigate%20the%20impact%20of%20different%20explanatory%20variables%20on%20the%20observed%20spatial%20pattern%20of%20classification%20uncertainty.%20It%20was%20strongly%20influenced%20by%20factors%20related%20with%20the%20agricultural%20management%20and%20training%20sample%20density.%20Lower%20uncertainties%20were%20revealed%20for%20fields%20close%20to%20rivers%20or%20irrigation%20canals.%20This%20study%20demonstrates%20that%20classification%20uncertainty%20estimates%20by%20the%20SVM%20algorithm%20provide%20a%20valuable%20addition%20to%20traditional%20accuracy%20assessments.%20This%20allows%20analyzing%20spatial%20variations%20of%20the%20classifier%20performance%20in%20maps%20and%20also%20differences%20in%20classification%20uncertainty%20within%20the%20growing%20season%20and%20between%20crop%20types%2C%20respectively.%22%2C%22date%22%3A%222015%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.isprsjprs.2015.03.004%22%2C%22ISSN%22%3A%2209242716%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A28%3A39Z%22%7D%7D%2C%7B%22key%22%3A%22IDMB6GKR%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222015%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20F.%2C%20Fliemann%2C%20E.%2C%20Abdullaev%2C%20I.%2C%20Conrad%2C%20C.%20and%20Lamers%2C%20J.P.A.%20%282015%29%20Mapping%20Abandoned%20Agricultural%20Land%20in%20Kyzyl-Orda%2C%20Kazakhstan%20Using%20Satellite%20Remote%20Sensing.%20%26lt%3Bi%26gt%3BApplied%20Geography%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B62%26lt%3B%5C%2Fb%26gt%3B%2C%20377%26%23x2013%3B390.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.apgeog.2015.05.009%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.apgeog.2015.05.009%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Mapping%20abandoned%20agricultural%20land%20in%20Kyzyl-Orda%2C%20Kazakhstan%20using%20satellite%20remote%20sensing%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Elisabeth%22%2C%22lastName%22%3A%22Fliemann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Iskandar%22%2C%22lastName%22%3A%22Abdullaev%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John%20P.%20A.%22%2C%22lastName%22%3A%22Lamers%22%7D%5D%2C%22abstractNote%22%3A%22In%20many%20regions%20worldwide%2C%20cropland%20abandonment%20is%20growing%2C%20which%20has%20strong%20and%20known%20environmental%20and%20socio-economic%20consequences.%20Yet%2C%20spatially%20explicit%20information%20on%20the%20spatial%20pattern%20of%20abandonment%20is%20sparse%2C%20particularly%20in%20post-Soviet%20countries%20of%20Central%20Asia.%20When%20thriving%20reaching%20for%20key%20Millennium%20Development%20Goals%20such%20as%20food%20security%20and%20poverty%20reduction%2C%20the%20issue%20of%20cropland%20abandonment%20is%20critical%20and%20therefore%20must%20be%20monitored%20and%20limited%2C%20or%20land%20use%20transformed%20into%20an%20alternative%20one.%20Central%20Asia%20experienced%20large%20changes%20of%20its%20agricultural%20system%20after%20the%20collapse%20of%20the%20Soviet%20Union%20in%201991.%20Land%20degradation%2C%20which%20started%20already%20before%20independence%2C%20and%20cropland%20abandonment%20is%20growing%20in%20extent%2C%20but%20their%20spatial%20pattern%20remains%20ill-understood.%20The%20objective%20of%20this%20study%20was%20to%20map%20and%20analyse%20agricultural%20land%20use%20in%20the%20irrigated%20areas%20of%20Kyzyl-Orda%2C%20southern%20Kazakhstan%2C%20Central%20Asia.%20For%20mapping%20land%20use%20and%20identifying%20abandoned%20agricultural%20land%2C%20an%20object-based%20classification%20approach%20was%20applied.%20Random%20forest%20%28RF%29%20and%20support%20vector%20machines%20%28SVM%29%20algorithms%20permitted%20classifying%20Landsat%20and%20RapidEye%20data%20from%202009%20to%202014.%20Overlaying%20these%20maps%20with%20information%20about%20irrigated%20land%20parcels%2C%20installed%20during%20the%20Soviet%20period%2C%20allowed%20indicating%20abandoned%20fields.%20Fusing%20the%20results%20of%20the%20two%20approaches%2C%20RF%20and%20SVM%2C%20resulted%20in%20classification%20accuracies%20of%20up%20to%2097%25.%20This%20was%20statistically%20significantly%20higher%20than%20with%20RF%20or%20SVM%20alone.%20Through%20the%20analysis%20of%20the%20land%20use%20trajectories%2C%20abandoned%20agricultural%20fields%20and%20a%20clear%20indication%20of%20abandoned%20land%20were%20identified%20on%20almost%2050%25%20of%20all%20fields%20in%20Kyzyl-Orda%20with%20an%20accuracy%20of%20approximately%2080%25.%20The%20outputs%20of%20this%20study%20may%20provide%20valuable%20information%20for%20planners%2C%20policy-%20and%20decision-makers%20to%20support%20better-informed%20decision-making%20like%20reducing%20possible%20environmental%20impacts%20of%20land%20abandonment%2C%20or%20identifying%20areas%20for%20sustainable%20intensification%20or%20re-cultivation.%22%2C%22date%22%3A%222015%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.apgeog.2015.05.009%22%2C%22ISSN%22%3A%2201436228%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A28%3A37Z%22%7D%7D%2C%7B%22key%22%3A%222TUAIA8I%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222015%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20F.%2C%20Conrad%2C%20C.%20and%20Michel%2C%20U.%20%282015%29%20Decision%20Fusion%20and%20Non-Parametric%20Classifiers%20for%20Land%20Use%20Mapping%20Using%20Multi-Temporal%20RapidEye%20Data.%20%26lt%3Bi%26gt%3BISPRS%20Journal%20of%20Photogrammetry%20and%20Remote%20Sensing%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B108%26lt%3B%5C%2Fb%26gt%3B%2C%20191%26%23x2013%3B204.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.isprsjprs.2015.07.001%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.isprsjprs.2015.07.001%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Decision%20fusion%20and%20non-parametric%20classifiers%20for%20land%20use%20mapping%20using%20multi-temporal%20RapidEye%20data%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ulrich%22%2C%22lastName%22%3A%22Michel%22%7D%5D%2C%22abstractNote%22%3A%22This%20study%20addressed%20the%20classification%20of%20multi-temporal%20satellite%20data%20from%20RapidEye%20by%20considering%20different%20classifier%20algorithms%20and%20decision%20fusion.%20Four%20non-parametric%20classifier%20algorithms%2C%20decision%20tree%20%28DT%29%2C%20random%20forest%20%28RF%29%2C%20support%20vector%20machine%20%28SVM%29%2C%20and%20multilayer%20perceptron%20%28MLP%29%2C%20were%20applied%20to%20map%20crop%20types%20in%20various%20irrigated%20landscapes%20in%20Central%20Asia.%20A%20novel%20decision%20fusion%20strategy%20to%20combine%20the%20outputs%20of%20the%20classifiers%20was%20proposed.%20This%20approach%20is%20based%20on%20randomly%20selecting%20subsets%20of%20the%20input%20dataset%20and%20aggregating%20the%20probabilistic%20outputs%20of%20the%20base%20classifiers%20with%20another%20meta-classifier.%20During%20the%20decision%20fusion%2C%20the%20reliability%20of%20each%20base%20classifier%20algorithm%20was%20considered%20to%20exclude%20less%20reliable%20inputs%20at%20the%20class-basis.%20The%20spatial%20and%20temporal%20transferability%20of%20the%20classifiers%20was%20evaluated%20using%20data%20sets%20from%20four%20different%20agricultural%20landscapes%20with%20different%20spatial%20extents%20and%20from%20different%20years.%20A%20detailed%20accuracy%20assessment%20showed%20that%20none%20of%20the%20stand-alone%20classifiers%20was%20the%20single%20best%20performing.%20Despite%20the%20very%20good%20performance%20of%20the%20base%20classifiers%2C%20there%20was%20still%20up%20to%2050%25%20disagreement%20in%20the%20maps%20produced%20by%20the%20two%20single%20best%20classifiers%2C%20RF%20and%20SVM.%20The%20proposed%20fusion%20strategy%2C%20however%2C%20increased%20overall%20accuracies%20up%20to%206%25.%20In%20addition%2C%20it%20was%20less%20sensitive%20to%20reduced%20training%20set%20sizes%20and%20produced%20more%20realistic%20land%20use%20maps%20with%20less%20speckle.%20The%20proposed%20fusion%20approach%20was%20better%20transferable%20to%20data%20sets%20from%20other%20years%2C%20i.e.%20resulted%20in%20higher%20accuracies%20for%20the%20investigated%20classes.%20The%20fusion%20approach%20is%20computationally%20efficient%20and%20appears%20well%20suited%20for%20mapping%20diverse%20crop%20categories%20based%20on%20sensors%20with%20a%20similar%20high%20repetition%20rate%20and%20spatial%20resolution%20like%20RapidEye%2C%20for%20instance%20the%20upcoming%20Sentinel-2%20mission.%22%2C%22date%22%3A%222015%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.isprsjprs.2015.07.001%22%2C%22ISSN%22%3A%2209242716%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A28%3A34Z%22%7D%7D%2C%7B%22key%22%3A%22U2X4IIR4%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Conrad%20et%20al.%22%2C%22parsedDate%22%3A%222015%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BConrad%2C%20C.%2C%20Rudloff%2C%20M.%2C%20Abdullaev%2C%20I.%2C%20Thiel%2C%20M.%2C%20L%26%23xF6%3Bw%2C%20F.%20and%20Lamers%2C%20J.P.A.%20%282015%29%20Measuring%20Rural%20Settlement%20Expansion%20in%20Uzbekistan%20Using%20Remote%20Sensing%20to%20Support%20Spatial%20Planning.%20%26lt%3Bi%26gt%3BApplied%20Geography%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B62%26lt%3B%5C%2Fb%26gt%3B%2C%2029%26%23x2013%3B43.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.apgeog.2015.03.017%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.apgeog.2015.03.017%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Measuring%20rural%20settlement%20expansion%20in%20Uzbekistan%20using%20remote%20sensing%20to%20support%20spatial%20planning%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Moritz%22%2C%22lastName%22%3A%22Rudloff%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Iskandar%22%2C%22lastName%22%3A%22Abdullaev%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John%20P.%20A.%22%2C%22lastName%22%3A%22Lamers%22%7D%5D%2C%22abstractNote%22%3A%22Population%20growth%20demands%20sustainable%20spatial%20planning%20strategies%20for%20settlements%20in%20Uzbekistan%2C%20Central%20Asia%2C%20especially%20in%20rural%20areas%20that%20are%20inhabited%20by%20approximately%2064%20percent%20of%20the%20country%26%23039%3Bs%20population.%20Where%20can%20settlements%20expand%20in%20rural%20Uzbekistan%20and%20does%20settlement%20growth%20affect%20valuable%20agricultural%20land%3F%20SPOT-5%20data%20with%20a%20resolution%20of%202.5%20m%20was%20utilized%20for%20mapping%20building%20layers%20and%20assessing%20settlement%20growth%20between%202006%20and%202011%20at%20the%20example%20of%2053%20communities%20located%20in%20the%20Khorezm%20province%20in%20North-West%20Uzbekistan.%20Object%20based%20image%20analysis%20was%20conducted%2C%20i.e.%20a%20multi-scale%20segmentation%20for%20the%20derivation%20of%20building%20contours%2C%20followed%20by%20a%20random%20forest%20%28RF%29%20classification%20of%20the%20object%26%23039%3Bs%20spectral%20and%20spatial%20characteristics.%20A%20geographical%20information%20system%20%28GIS%29%20was%20used%20for%20identifying%20settlement%20densification%20and%20expansion%20processes%2C%20and%20for%20quantifying%20agricultural%20land%20parcels%20of%20different%20soil%20quality%20occupied%20during%20settlement%20growth.%20A%20calibration%20routine%20based%20on%20indices%20of%20segmentation%20quality%20enabled%20the%20selection%20of%20optimal%20segmentation%20parameters.%20After%20GIS-based%20refinements%20of%20the%20RF%20classification%20results%2C%20the%20overall%20accuracy%20%28OA%29%20of%20the%20building%20layers%20of%20both%20years%20exceeded%2095%25.%20The%20OA%20of%20the%20change%20map%20was%2092.7%25.%20The%20results%20revealed%20that%20the%20building%20area%20increased%20by%2020%25%2C%20whilst%20settlement%20expansion%20amounted%20to%2010%25%20in%202006%5Cu20132011.%20Settlements%20widely%20expanded%20in%20accordance%20with%20the%20existing%20rules%20prohibiting%20the%20conversion%20of%20agricultural%20land%20to%20housing%20areas.%20Nevertheless%2C%20about%2020%25%20of%20the%20settlement%20growth%20occurred%20on%20agricultural%20production%20areas%2C%20also%20on%20those%20with%20highly%20productive%20soils.%20The%20results%20indicated%20both%2C%20the%20pressure%20on%20land%20resources%20for%20settlement%20growth%20and%20%5Cu2013%20in%20face%20of%20continuous%20population%20growth%20%5Cu2013%20an%20increasing%20demand%20for%20comprehensive%20spatial%20planning%20in%20rural%20Uzbekistan.%20The%20elaborated%20methodological%20approach%20can%20be%20extrapolated%20to%20regions%20throughout%20Central%20Asia%20with%20similar%20environmental%20conditions.%22%2C%22date%22%3A%222015%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.apgeog.2015.03.017%22%2C%22ISSN%22%3A%2201436228%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A28%3A23Z%22%7D%7D%2C%7B%22key%22%3A%22TUQTSQ9B%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Zoungrana%20et%20al.%22%2C%22parsedDate%22%3A%222015%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BZoungrana%2C%20B.J.-B.%2C%20Conrad%2C%20C.%2C%20Amekudzi%2C%20L.K.%2C%20Thiel%2C%20M.%2C%20Da%2C%20E.D.%2C%20Forkuor%2C%20G.%20and%20L%26%23xF6%3Bw%2C%20F.%20%282015%29%20Multi-Temporal%20Landsat%20Images%20and%20Ancillary%20Data%20for%20Land%20Use%5C%2FCover%20Change%20%28LULCC%29%20Detection%20in%20the%20Southwest%20of%20Burkina%20Faso%2C%20West%20Africa.%20%26lt%3Bi%26gt%3BRemote%20Sensing%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B7%26lt%3B%5C%2Fb%26gt%3B%2C%2012076%26%23x2013%3B12102.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs70912076%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Frs70912076%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Multi-Temporal%20Landsat%20Images%20and%20Ancillary%20Data%20for%20Land%20Use%5C%2FCover%20Change%20%28LULCC%29%20Detection%20in%20the%20Southwest%20of%20Burkina%20Faso%2C%20West%20Africa%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Benewinde%20J-B.%22%2C%22lastName%22%3A%22Zoungrana%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Leonard%20K.%22%2C%22lastName%22%3A%22Amekudzi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Thiel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Evariste%20Dapola%22%2C%22lastName%22%3A%22Da%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Gerald%22%2C%22lastName%22%3A%22Forkuor%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%5D%2C%22abstractNote%22%3A%22Accurate%20quantification%20of%20land%20use%5C%2Fcover%20change%20%28LULCC%29%20is%20important%20for%20efficient%20environmental%20management%2C%20especially%20in%20regions%20that%20are%20extremely%20affected%20by%20climate%20variability%20and%20continuous%20population%20growth%20such%20as%20West%20Africa.%20In%20this%20context%2C%20accurate%20LULC%20classification%20and%20statistically%20sound%20change%20area%20estimates%20are%20essential%20for%20a%20better%20understanding%20of%20LULCC%20processes.%20This%20study%20aimed%20at%20comparing%20mono-temporal%20and%20multi-temporal%20LULC%20classifications%20as%20well%20as%20their%20combination%20with%20ancillary%20data%20and%20to%20determine%20LULCC%20across%20the%20heterogeneous%20landscape%20of%20southwest%20Burkina%20Faso%20using%20accurate%20classification%20results.%20Landsat%20data%20%281999%2C%202006%20and%202011%29%20and%20ancillary%20data%20served%20as%20input%20features%20for%20the%20random%20forest%20classifier%20algorithm.%20Five%20LULC%20classes%20were%20identified%3A%20woodland%2C%20mixed%20vegetation%2C%20bare%20surface%2C%20water%20and%20agricultural%20area.%20A%20reference%20database%20was%20established%20using%20different%20sources%20including%20high-resolution%20images%2C%20aerial%20photo%20and%20field%20data.%20LULCC%20and%20LULC%20classification%20accuracies%2C%20area%20and%20area%20uncertainty%20were%20computed%20based%20on%20the%20method%20of%20adjusted%20error%20matrices.%20The%20results%20revealed%20that%20multi-temporal%20classification%20significantly%20outperformed%20those%20solely%20based%20on%20mono-temporal%20data%20in%20the%20study%20area.%20However%2C%20combining%20mono-temporal%20imagery%20and%20ancillary%20data%20for%20LULC%20classification%20had%20the%20same%20accuracy%20level%20as%20multi-temporal%20classification%20which%20is%20an%20indication%20that%20this%20combination%20is%20an%20efficient%20alternative%20to%20multi-temporal%20classification%20in%20the%20study%20region%2C%20where%20cloud%20free%20images%20are%20rare.%20The%20LULCC%20map%20obtained%20had%20an%20overall%20accuracy%20of%2092%25.%20Natural%20vegetation%20loss%20was%20estimated%20to%20be%2017.9%25%20%24%5C%5Cpm%24%202.5%25%20between%201999%20and%202011.%20The%20study%20area%20experienced%20an%20increase%20in%20agricultural%20area%20and%20bare%20surface%20at%20the%20expense%20of%20woodland%20and%20mixed%20vegetation%2C%20which%20attests%20to%20the%20ongoing%20deforestation.%20These%20results%20can%20serve%20as%20means%20of%20regional%20and%20global%20land%20cover%20products%20validation%2C%20as%20they%20provide%20a%20new%20validated%20data%20set%20with%20uncertainty%20estimates%20in%20heterogeneous%20ecosystems%20prone%20to%20classification%20errors.%22%2C%22date%22%3A%222015%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.3390%5C%2Frs70912076%22%2C%22ISSN%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A28%3A45Z%22%7D%7D%2C%7B%22key%22%3A%22TEXRMLPS%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Conrad%20et%20al.%22%2C%22parsedDate%22%3A%222014%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BConrad%2C%20C.%2C%20Dech%2C%20S.W.%2C%20Dubovyk%2C%20O.%2C%20Fritsch%2C%20S.%2C%20Klein%2C%20D.%2C%20L%26%23xF6%3Bw%2C%20F.%2C%20Schorcht%2C%20G.%20and%20Zeidler%2C%20J.%20%282014%29%20Derivation%20of%20Temporal%20Windows%20for%20Accurate%20Crop%20Discrimination%20in%20Heterogeneous%20Croplands%20of%20Uzbekistan%20Using%20Multitemporal%20RapidEye%20Images.%20%26lt%3Bi%26gt%3BComputers%20and%20Electronics%20in%20Agriculture%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B103%26lt%3B%5C%2Fb%26gt%3B%2C%2063%26%23x2013%3B74.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.compag.2014.02.003%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.compag.2014.02.003%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Derivation%20of%20temporal%20windows%20for%20accurate%20crop%20discrimination%20in%20heterogeneous%20croplands%20of%20Uzbekistan%20using%20multitemporal%20RapidEye%20images%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stefan%20W.%22%2C%22lastName%22%3A%22Dech%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olena%22%2C%22lastName%22%3A%22Dubovyk%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sebastian%22%2C%22lastName%22%3A%22Fritsch%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Doris%22%2C%22lastName%22%3A%22Klein%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Gunther%22%2C%22lastName%22%3A%22Schorcht%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julian%22%2C%22lastName%22%3A%22Zeidler%22%7D%5D%2C%22abstractNote%22%3A%22Recently%20launched%20and%20upcoming%20satellite%20systems%20are%20expected%20to%20make%20crop%20mapping%20increasingly%20accurate%20and%20operational.%20This%20study%20aims%20at%20an%20evaluation%20of%20the%20optimum%20number%20of%20acquisition%20dates%20and%20most%20suitable%20temporal%20windows%20for%20the%20discrimination%20of%20crops%20over%20heterogeneous%20agricultural%20landscapes%20utilizing%20multitemporal%20data%20from%20the%20RapidEye%20satellite%20constellation.%20For%20a%20case%20study%20site%20in%20West-Uzbekistan%2C%20which%20covers%20230%2C000%20ha%20of%20irrigated%20land%2C%20nine%206.5%20m%20RapidEye%20mosaics%20were%20obtained%20throughout%20the%20vegetation%20period%20of%202009.%20The%20acquisition%20window%20of%20one%20mosaic%20was%20maximum%20five%20days.%20The%20optimum%20number%20of%20acquisition%20dates%20and%20acquisition%20windows%20relevant%20for%20accurate%20crop%20identification%20was%20assessed%20by%20applying%20a%20random%20forest%20algorithm%20to%20all%20possible%20combinations%20of%20the%20available%20RapidEye%20mosaics.%20Overall%20accuracy%20increased%20with%20the%20number%20of%20acquisition%20dates%20selected%20for%20the%20classification.%20Classifying%20all%20nine%20mosaics%20resulted%20in%20an%20overall%20accuracy%20of%2085.7%25.%20This%20accuracy%20level%20could%20be%20already%20achieved%20by%20using%20five%20or%20more%20acquisitions%20during%20distinctive%20phases%20of%20the%20vegetation%20period%2C%20among%20others%20short%20before%20winter-wheat%20harvest%20and%20in%20initial%20growing%20phases%20of%20summer%20crops.%20It%20could%20be%20shown%20that%20accurate%20early%20season%20crop%20maps%20at%20field%20level%20can%20be%20derived%20enabling%20water%20managers%20to%20update%20water%20distribution%20schedules%20in%20the%20study%20region.%20All%2053%2C302%20fields%20of%20the%20irrigation%20system%20including%20very%20small%20parcels%20with%20a%20size%20of%200.05%20ha%20could%20be%20classified%20due%20to%20the%20high%20geometric%20resolution%20of%20RapidEye.%20Detailed%20NDVI%20temporal%20profiles%20demonstrated%20the%20potential%20of%20RapidEye%20for%20including%20minor%20crops%20into%20classifications%20of%20heterogeneous%20agricultural%20areas.%20Class-wise%20accuracy%20pointed%20to%20the%20challenge%20of%20classifying%20sub-tree%20cultivation%20and%20indicated%20that%20classification%20of%20minor%20crops%20could%20also%20depend%20on%20the%20spatial%20resolution%20of%20satellite%20images.%20The%20case%20study%20suggests%20identifying%20temporal%20windows%20for%20crop%20mapping%20serving%20as%20substantial%20support%20for%20land%20and%20water%20management%20in%20different%20agro-environmental%20settings.%22%2C%22date%22%3A%222014%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.compag.2014.02.003%22%2C%22ISSN%22%3A%2201681699%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A24%3A47Z%22%7D%7D%2C%7B%22key%22%3A%222J3W433K%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A8826471%2C%22username%22%3A%22Geoecology_MLU%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fgeoecology_mlu%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222013%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20F.%2C%20Michel%2C%20U.%2C%20Dech%2C%20S.W.%20and%20Conrad%2C%20C.%20%282013%29%20Impact%20of%20Feature%20Selection%20on%20the%20Accuracy%20and%20Spatial%20Uncertainty%20of%20Per-Field%20Crop%20Classification%20Using%20Support%20Vector%20Machines.%20%26lt%3Bi%26gt%3BISPRS%20Journal%20of%20Photogrammetry%20and%20Remote%20Sensing%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bb%26gt%3B85%26lt%3B%5C%2Fb%26gt%3B%2C%20102%26%23x2013%3B119.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.isprsjprs.2013.08.007%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.isprsjprs.2013.08.007%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Impact%20of%20feature%20selection%20on%20the%20accuracy%20and%20spatial%20uncertainty%20of%20per-field%20crop%20classification%20using%20Support%20Vector%20Machines%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ulrich%22%2C%22lastName%22%3A%22Michel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stefan%20W.%22%2C%22lastName%22%3A%22Dech%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22Crop%20mapping%20is%20one%20major%20component%20of%20agricultural%20resource%20monitoring%20using%20remote%20sensing.%20Yield%20or%20water%20demand%20modeling%20requires%20that%20both%2C%20the%20total%20surface%20that%20is%20cultivated%20and%20the%20accurate%20distribution%20of%20crops%2C%20respectively%20is%20known.%20Map%20quality%20is%20crucial%20and%20influences%20the%20model%20outputs.%20Although%20the%20use%20of%20multi-spectral%20time%20series%20data%20in%20crop%20mapping%20has%20been%20acknowledged%2C%20the%20potentially%20high%20dimensionality%20of%20the%20input%20data%20remains%20an%20issue.%20In%20this%20study%20Support%20Vector%20Machines%20%28SVM%29%20are%20used%20for%20crop%20classification%20in%20irrigated%20landscapes%20at%20the%20object-level.%20Input%20to%20the%20classifications%20is%2071%20multi-seasonal%20spectral%20and%20geostatistical%20features%20computed%20from%20RapidEye%20time%20series.%20The%20random%20forest%20%28RF%29%20feature%20importance%20score%20was%20used%20to%20select%20a%20subset%20of%20features%20that%20achieved%20optimal%20accuracies.%20The%20relationship%20between%20the%20hard%20result%20accuracy%20and%20the%20soft%20output%20from%20the%20SVM%20is%20investigated%20by%20employing%20two%20measures%20of%20uncertainty%2C%20the%20maximum%20a%20posteriori%20probability%20and%20the%20alpha%20quadratic%20entropy.%20Specifically%20the%20effect%20of%20feature%20selection%20on%20map%20uncertainty%20is%20investigated%20by%20looking%20at%20the%20soft%20outputs%20of%20the%20SVM%2C%20in%20addition%20to%20classical%20accuracy%20metrics.%20Overall%20the%20SVMs%20applied%20to%20the%20reduced%20feature%20subspaces%20that%20were%20composed%20of%20the%20most%20informative%20multi-seasonal%20features%20led%20to%20a%20clear%20increase%20in%20classification%20accuracy%20up%20to%204.3%25%2C%20and%20to%20a%20significant%20decline%20in%20thematic%20uncertainty.%20SVM%20was%20shown%20to%20be%20affected%20by%20feature%20space%20size%20and%20could%20benefit%20from%20RF-based%20feature%20selection.%20Uncertainty%20measures%20from%20SVM%20are%20an%20informative%20source%20of%20information%20on%20the%20spatial%20distribution%20of%20error%20in%20the%20crop%20maps.%22%2C%22date%22%3A%222013%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.isprsjprs.2013.08.007%22%2C%22ISSN%22%3A%2209242716%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222019-11-06T08%3A24%3A32Z%22%7D%7D%2C%7B%22key%22%3A%22CQJTFQME%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22L%5Cu00f6w%20et%20al.%22%2C%22parsedDate%22%3A%222012%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%2C%20F.%2C%20Schorcht%2C%20G.%2C%20Michel%2C%20U.%2C%20Dech%2C%20S.%20and%20Conrad%2C%20C.%20%282012%29%20Per-Field%20Crop%20Classification%20in%20Irrigated%20Agricultural%20Regions%20in%20Middle%20Asia%20Using%20Random%20Forest%20and%20Support%20Vector%20Machine%20Ensemble.%20In%3A%20Michel%2C%20U.%2C%20Civco%2C%20D.L.%2C%20Ehlers%2C%20M.%2C%20Schulz%2C%20K.%2C%20Nikolakopoulos%2C%20K.G.%2C%20Habib%2C%20S.%2C%20Messinger%2C%20D.%20and%20Maltese%2C%20A.%2C%20Eds.%2C%20Edinburgh%2C%20United%20Kingdom%2C%2085380R.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20target%3D%26%23039%3B_blank%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1117%5C%2F12.974588%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1117%5C%2F12.974588%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22Per-field%20crop%20classification%20in%20irrigated%20agricultural%20regions%20in%20middle%20Asia%20using%20random%20forest%20and%20support%20vector%20machine%20ensemble%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabian%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Gunther%22%2C%22lastName%22%3A%22Schorcht%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ulrich%22%2C%22lastName%22%3A%22Michel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stefan%22%2C%22lastName%22%3A%22Dech%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22Ulrich%22%2C%22lastName%22%3A%22Michel%22%7D%2C%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22Daniel%20L.%22%2C%22lastName%22%3A%22Civco%22%7D%2C%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22Manfred%22%2C%22lastName%22%3A%22Ehlers%22%7D%2C%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22Karsten%22%2C%22lastName%22%3A%22Schulz%22%7D%2C%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22Konstantinos%20G.%22%2C%22lastName%22%3A%22Nikolakopoulos%22%7D%2C%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22Shahid%22%2C%22lastName%22%3A%22Habib%22%7D%2C%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Messinger%22%7D%2C%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22Antonino%22%2C%22lastName%22%3A%22Maltese%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222012%22%2C%22proceedingsTitle%22%3A%22%22%2C%22conferenceName%22%3A%22SPIE%20Remote%20Sensing%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%2210.1117%5C%2F12.974588%22%2C%22ISBN%22%3A%22%22%2C%22url%22%3A%22http%3A%5C%2F%5C%2Fproceedings.spiedigitallibrary.org%5C%2Fproceeding.aspx%3Fdoi%3D10.1117%5C%2F12.974588%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222021-12-22T10%3A47%3A35Z%22%7D%7D%5D%7D
1
Conrad, C., Teucher, M., Wenzel, J.L., Löw, J. and Pöhlitz, J. (2025, August 29) Verbundprojekt: Einsatz von Fernerkundungstechnologien für die Digitalisierung im Pflanzenbau (AgriSens-DEMMIN4.0) - Teilprojekt 5: Sachbericht zum Verwendungsnachweis. Technische Informationsbibliothek (TIB). https://doi.org/10.34657/23043.
1
Löw, J., Hill, S., Otte, I., Friedrich, C., Thiel, M., Ullmann, T. and Conrad, C. (2025) Integrating the Landscape Scale Supports SAR-Based Detection and Assessment of the Phenological Development at the Field Level. Frontiers in Remote Sensing, 6. https://doi.org/10.3389/frsen.2025.1610005.
1
Mahmood, T., Löw, J., Pöhlitz, J., Wenzel, J.L. and Conrad, C. (2024) Estimation of 100 m Root Zone Soil Moisture by Downscaling 1 Km Soil Water Index with Machine Learning and Multiple Geodata. Environmental Monitoring and Assessment, 196, 823. https://doi.org/https://doi.org/10.1007/s10661-024-12969-5.
1
Löw, J., Hill, S., Otte, I., Thiel, M., Ullmann, T. and Conrad, C. (2024) How Phenology Shapes Crop-Specific Sentinel-1 PolSAR Features and InSAR Coherence across Multiple Years and Orbits. Remote Sensing, 16, 2791. https://doi.org/10.3390/rs16152791.
1
Löw, J., Hill, S., Thiel, M., Ullmann, T. and Conrad, C. (2024, June 20) How Does Phenology Shape Crop- And Orbit-Specific InSAR Coherence And PolSAR-Signatures Of Sentinel-1. Manchester, UK.
1
Friedrich, C., Löw, J., Otte, I., Hill, S., Schierghofer, C., Gessner, U., Truckenbrodt, S., Schonert, E., Piernecke, T., Conrad, C. and Thiel, M. (2024, March 21) DataCube Architecture for Integrating, Processing and Presenting Big Geodata to End Users. Berlin.
1
Löw, J., Hill, S., Thiel, M., Ullmann, T. and Conrad, C. (2024, March 15) Tracking Crop Phenology across Different Sentinel-1 Orbits by Combining PolSAR Features with Growing Degree Data. Remagen.
1
Löw, J., Hill, S., Thiel, M., Ullmann, T. and Conrad, C. (2024) Tracking Crop Phenology across Different Sentinel-1 Orbits by Combining PolSAR Features with Growing Degree Data. Remagen.
1
Friedrich, C., Löw, J., Otte, I., Hill, S., Förtsch, S., Schwalb-Willmann, J., Gessner, U., Schierghofer, C., Piernecke, T., Truckenbrodt, S., Schonert, E., Assmann, D., Böttcher, F., Conrad, C. and Thiel, M. (2024) A Multi-Talented Datacube: Integrating, Processing and Presenting Big Geodata for the agricultural End User. Informatik in Der Land-, Forstund Ernährungswirtschaft Fokus: Biodiversität Fördern Durch Digitale Landwirtschaft, Stuttgart-Hohenheim.
1
Friedrich, C., Löw, J., Otte, I., Hill, S., Förtsch, S., Schwalb-Willmann, J., Gessner, U., Schierghofer, C., Piernecke, T., Truckenbrodt, S., Schonert, E., Assmann, D., Böttcher, F., Conrad, C. and Thiel, M. (2024, February 28) A Multi-Talented Datacube: Integrating, Processing and Presenting Big Geodata for the agricultural End User. Stuttgart-Hohenheim.
1
Lobert, F., Löw, J., Schwieder, M., Gocht, A., Schlund, M., Hostert, P. and Erasmi, S. (2023) A Deep Learning Approach for Deriving Winter Wheat Phenology from Optical and SAR Time Series at Field Level. Remote Sensing of Environment, 298, 113800. https://doi.org/10.1016/j.rse.2023.113800.
1
Wenzel, J.L., Löw, J., Pöhlitz, J. and Conrad, C. (2023, November 17) Neues von Oben - Aktuelle Entwicklungen Satelliten- Und Drohnenbasierter Digitalisierung Im Pflanzenbau. Oral Presentation, Hannover, Germany.
1
Lobert, F., Löw, J., Schwieder, M., Gocht, A., Schlund, M., Hosert, P. and Erasmi, S. (2023) Deriving Winter Wheat Phenology From Combined Optical And SAR Time Series With Deep Learning. The 42nd EARSeL Symposium, Bucharest.
1
Lepore, D., Conrad, C., Allocca, V., Cusano, D., Löw, J., El-Hokayem, L. and De Vita, P. (2023) Integration of Remotely Sensed and Field Monitoring Data for Characterizing the Hydrological Regime of Soils Covering Karst Aquifers and Assessing Groundwater Recharge. EGU, Naples. https://doi.org/https://doi.org/10.5194/egusphere-gc8-hydro-65, 2023.
1
Conrad, C., Schlaak, J., Schmelzer, J. and Löw, J. (2023) Downscaling and Validation of 1km ESA Soil Water Index for Soil Moisture Monitoring on Agricultural Land in Temperate Climate Conditions. EGU, Naples. https://doi.org/https://doi.org/10.5194/egusphere-gc8-hydro-97, 2023.
1
Löw, J., Hill, S., Ullmann, T. and Conrad, C. (2022) Assessing the Applicability of Interferometric and Polarimetric Time Series Derived from Sentinel-1 for Tracking Phenological Developments of Crops at the JECAM Site DEMMIN (Germany). Arbeitskreis Fernerkundung, Halle (Saale).
1
Löw, J., Hill, S., Ullmann, T. and Conrad, C. (2022) Tracking the Phenological Developments of Crops by a Complementary Set of Interferometric and Polarimetric Time Series Derived from Sentinel-1 at the JECAM Site DEMMIN (Germany). ESA Living Planet Symposium, Bonn.
1
Löw, J., Ullmann, T. and Conrad, C. (2021) The Impact of Phenological Developments on Interferometric and Polarimetric Crop Signatures Derived from Sentinel-1: Examples from the DEMMIN Study Site (Germany). Remote Sensing, 13, 2951. https://doi.org/10.3390/rs13152951.
1
Nußbaum, P., Somogyvári, M., Bresinsky, L., Löw, J., Schönbrodt-Stitt, S., Sauter, M., Conrad, C. and Engelhardt, I. (2020) Vulnerability Assessment of Karst Aquifers under Mediterranean Climates. other, oral. https://doi.org/10.5194/egusphere-egu2020-5112.
1
Schönbrodt-Stitt, S., Conrad, C., Dimov, D., Ergashev, I., Löw, F., Morper-Busch, L., Muminov, S., Ruziev, I., Schorcht, G., Solodky, G., Sorokin, A., Sorokin, D., Stulina, G., Toshpulatov, R., Zaitov, S., Kitapbayev, A. and Unger-Shayesteh, K. (2018) The WUEMoCA Tool for Monitoring Irrigated Cropland Use and Water Use Efficiency at the Landscape Level of the Aral Sea Basin. In: FSBSI “Pryanishnikov Institute of Agrochemistry,” Ed., Novel Methods and Results of Landscape Research in Europe, Central Asia and Siberia, Vol. 4 Optimising Agricultural Landscapes, Moscow, 351–356.
1
Löw, F., Biradar, C., Fliemann, E., Lamers, J.P.A. and Conrad, C. (2017) Assessing Gaps in Irrigated Agricultural Productivity through Satellite Earth Observations—A Case Study of the Fergana Valley, Central Asia. International Journal of Applied Earth Observation and Geoinformation, 59, 118–134. https://doi.org/10.1016/j.jag.2017.02.014.
1
Conrad, C., Löw, F. and Lamers, J.P.A. (2017) Mapping and Assessing Crop Diversity in the Irrigated Fergana Valley, Uzbekistan. Applied Geography, 86, 102–117. https://doi.org/10.1016/j.apgeog.2017.06.016.
1
Conrad, C., Schönbrodt-Stitt, S., Löw, F., Sorokin, D. and Paeth, H. (2016) Cropping Intensity in the Aral Sea Basin and Its Dependency from the Runoff Formation 2000–2012. Remote Sensing, 8, 630. https://doi.org/10.3390/rs8080630.
1
Conrad, C., Lamers, J.P.A., Ibragimov, N., Löw, F. and Martius, C. (2016) Analysing Irrigated Crop Rotation Patterns in Arid Uzbekistan by the Means of Remote Sensing: A Case Study on Post-Soviet Agricultural Land Use. Journal of Arid Environments, 124, 150–159. https://doi.org/10.1016/j.jaridenv.2015.08.008.
1
Conrad, C., Rudloff, M., Abdullaev, I., Thiel, M., Löw, F. and Lamers, J.P.A. (2015) Measuring Rural Settlement Expansion in Uzbekistan Using Remote Sensing to Support Spatial Planning. Applied Geography, 62, 29–43. https://doi.org/10.1016/j.apgeog.2015.03.017.
1
Löw, F., Duveiller, G., Conrad, C. and Michel, U. (2015) Impact of Categorical and Spatial Scale on Supervised Crop Classification Using Remote Sensing. Photogrammetrie - Fernerkundung - Geoinformation, 2015, 7–20. https://doi.org/10.1127/pfg/2015/0252.
1
Lex, S., Asam, S., Löw, F. and Conrad, C. (2015) Comparison of Two Statistical Methods for the Derivation of the Fraction of Absorbed Photosynthetic Active Radiation for Cotton. Photogrammetrie - Fernerkundung - Geoinformation, 2015, 55–67. https://doi.org/10.1127/pfg/2015/0250.
1
Löw, F., Knöfel, P. and Conrad, C. (2015) Analysis of Uncertainty in Multi-Temporal Object-Based Classification. ISPRS Journal of Photogrammetry and Remote Sensing, 105, 91–106. https://doi.org/10.1016/j.isprsjprs.2015.03.004.
1
Löw, F., Fliemann, E., Abdullaev, I., Conrad, C. and Lamers, J.P.A. (2015) Mapping Abandoned Agricultural Land in Kyzyl-Orda, Kazakhstan Using Satellite Remote Sensing. Applied Geography, 62, 377–390. https://doi.org/10.1016/j.apgeog.2015.05.009.
1
Löw, F., Conrad, C. and Michel, U. (2015) Decision Fusion and Non-Parametric Classifiers for Land Use Mapping Using Multi-Temporal RapidEye Data. ISPRS Journal of Photogrammetry and Remote Sensing, 108, 191–204. https://doi.org/10.1016/j.isprsjprs.2015.07.001.
1
Conrad, C., Rudloff, M., Abdullaev, I., Thiel, M., Löw, F. and Lamers, J.P.A. (2015) Measuring Rural Settlement Expansion in Uzbekistan Using Remote Sensing to Support Spatial Planning. Applied Geography, 62, 29–43. https://doi.org/10.1016/j.apgeog.2015.03.017.
1
Zoungrana, B.J.-B., Conrad, C., Amekudzi, L.K., Thiel, M., Da, E.D., Forkuor, G. and Löw, F. (2015) Multi-Temporal Landsat Images and Ancillary Data for Land Use/Cover Change (LULCC) Detection in the Southwest of Burkina Faso, West Africa. Remote Sensing, 7, 12076–12102. https://doi.org/10.3390/rs70912076.
1
Conrad, C., Dech, S.W., Dubovyk, O., Fritsch, S., Klein, D., Löw, F., Schorcht, G. and Zeidler, J. (2014) Derivation of Temporal Windows for Accurate Crop Discrimination in Heterogeneous Croplands of Uzbekistan Using Multitemporal RapidEye Images. Computers and Electronics in Agriculture, 103, 63–74. https://doi.org/10.1016/j.compag.2014.02.003.
1
Löw, F., Michel, U., Dech, S.W. and Conrad, C. (2013) Impact of Feature Selection on the Accuracy and Spatial Uncertainty of Per-Field Crop Classification Using Support Vector Machines. ISPRS Journal of Photogrammetry and Remote Sensing, 85, 102–119. https://doi.org/10.1016/j.isprsjprs.2013.08.007.
1
Löw, F., Schorcht, G., Michel, U., Dech, S. and Conrad, C. (2012) Per-Field Crop Classification in Irrigated Agricultural Regions in Middle Asia Using Random Forest and Support Vector Machine Ensemble. In: Michel, U., Civco, D.L., Ehlers, M., Schulz, K., Nikolakopoulos, K.G., Habib, S., Messinger, D. and Maltese, A., Eds., Edinburgh, United Kingdom, 85380R. https://doi.org/10.1117/12.974588.

2355391MDLREVTXOthers,JLLöw american-journal-of-plant-sciences50datedesc1 Löw, J. 12628https://geo.uni-halle.de/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A0%2C%22request_next%22%3A0%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%22FWJZMKPD%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Wenzel%20et%20al.%22%2C%22parsedDate%22%3A%222023-11-17%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BWenzel%2C%20J.L.%2C%20L%26%23xF6%3Bw%2C%20J.%2C%20P%26%23xF6%3Bhlitz%2C%20J.%20and%20Conrad%2C%20C.%20%282023%2C%20November%2017%29%20Neues%20von%20Oben%20-%20Aktuelle%20Entwicklungen%20Satelliten-%20Und%20Drohnenbasierter%20Digitalisierung%20Im%20Pflanzenbau.%20Oral%20Presentation%2C%20Hannover%2C%20Germany.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22Neues%20von%20oben%20-%20aktuelle%20Entwicklungen%20satelliten-%20und%20drohnenbasierter%20Digitalisierung%20im%20Pflanzenbau%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Jan%20Lukas%22%2C%22lastName%22%3A%22Wenzel%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22P%5Cu00f6hlitz%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222023-11-17%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A41%3A12Z%22%7D%7D%5D%7D
1
Wenzel, J.L., Löw, J., Pöhlitz, J. and Conrad, C. (2023, November 17) Neues von Oben - Aktuelle Entwicklungen Satelliten- Und Drohnenbasierter Digitalisierung Im Pflanzenbau. Oral Presentation, Hannover, Germany.

Supervised Theses

23553912XDMJIQCbachelorLöw 1annals-of-hematology50datedesc 12628https://geo.uni-halle.de/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A0%2C%22request_next%22%3A0%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%22C3ZN4654%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Fischer%22%2C%22parsedDate%22%3A%222025-04-16%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1.%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BFischer%20K%20%282025%29%20Erfassung%20r%26%23xE4%3Bumlich-zeitlicher%20Landschaftsdynamiken%20im%5CnNiedermoorstandort%20Nedlitzer%20Niederung%20mittels%5CnSentintel-2%20Zeitserien.%20Martin-Luther-Universit%26%23xE4%3Bt%20Halle-Wittenberg%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22thesis%22%2C%22title%22%3A%22Erfassung%20r%5Cu00e4umlich-zeitlicher%20Landschaftsdynamiken%20im%5CnNiedermoorstandort%20Nedlitzer%20Niederung%20mittels%5CnSentintel-2%20Zeitserien%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Karla%22%2C%22lastName%22%3A%22Fischer%22%7D%2C%7B%22creatorType%22%3A%22contributor%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Denk%22%7D%2C%7B%22creatorType%22%3A%22contributor%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22thesisType%22%3A%22%22%2C%22university%22%3A%22Martin-Luther-Universit%5Cu00e4t%20Halle-Wittenberg%22%2C%22date%22%3A%222025-04-16%22%2C%22language%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%222XDMJIQC%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A43%3A03Z%22%7D%7D%2C%7B%22key%22%3A%228TFDN8TH%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Genau%22%2C%22parsedDate%22%3A%222024-04-02%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1.%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BGenau%20D%20%282024%29%20Erfassung%20von%20Landschaftsdynamiken%20in%20der%20Nedlitzer%5CnNiederung%20mittels%20Sentinel-1%20SAR%20und%20In%20Situ-Daten%20im%5CnZeitraum%202016%20-%202023.%20Martin-Luther-Universit%26%23xE4%3Bt%20Halle-Wittenberg%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22thesis%22%2C%22title%22%3A%22Erfassung%20von%20Landschaftsdynamiken%20in%20der%20Nedlitzer%5CnNiederung%20mittels%20Sentinel-1%20SAR%20und%20In%20Situ-Daten%20im%5CnZeitraum%202016%20-%202023%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Demian%22%2C%22lastName%22%3A%22Genau%22%7D%2C%7B%22creatorType%22%3A%22contributor%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Denk%22%7D%2C%7B%22creatorType%22%3A%22contributor%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22thesisType%22%3A%22%22%2C%22university%22%3A%22Martin-Luther-Universit%5Cu00e4t%20Halle-Wittenberg%22%2C%22date%22%3A%222024-04-02%22%2C%22language%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%222XDMJIQC%22%5D%2C%22dateModified%22%3A%222025-08-01T10%3A59%3A44Z%22%7D%7D%2C%7B%22key%22%3A%22DXFMESM9%22%2C%22library%22%3A%7B%22id%22%3A2355391%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A5869773%2C%22username%22%3A%22mlu-teucher%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fmlu-teucher%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22L%5Cu00f6w%22%2C%22parsedDate%22%3A%222016-01-01%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%20style%3D%26quot%3Bclear%3A%20left%3B%20%26quot%3B%26gt%3B%5Cn%20%20%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-left-margin%26quot%3B%20style%3D%26quot%3Bfloat%3A%20left%3B%20padding-right%3A%200.5em%3B%20text-align%3A%20right%3B%20width%3A%201em%3B%26quot%3B%26gt%3B1.%20%26lt%3B%5C%2Fdiv%26gt%3B%26lt%3Bdiv%20class%3D%26quot%3Bcsl-right-inline%26quot%3B%20style%3D%26quot%3Bmargin%3A%200%20.4em%200%201.5em%3B%26quot%3B%26gt%3BL%26%23xF6%3Bw%20J%20%282016%29%20Analyse%20der%20Bodenfeuchteentwicklung%20in%20zentralasiatischen%20Bew%26%23xE4%3Bsserungssystemen%20anhand%20von%20ASCAT-Zeitserien.%20Julius-Maximilians-Universit%26%23xE4%3Bt%20W%26%23xFC%3Brzburg%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%20%20%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22thesis%22%2C%22title%22%3A%22Analyse%20der%20Bodenfeuchteentwicklung%20in%20zentralasiatischen%20Bew%5Cu00e4sserungssystemen%20anhand%20von%20ASCAT-Zeitserien%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johannes%22%2C%22lastName%22%3A%22L%5Cu00f6w%22%7D%2C%7B%22creatorType%22%3A%22contributor%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Conrad%22%7D%2C%7B%22creatorType%22%3A%22contributor%22%2C%22firstName%22%3A%22%22%2C%22lastName%22%3A%22%3F%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22thesisType%22%3A%22%22%2C%22university%22%3A%22Julius-Maximilians-Universit%5Cu00e4t%20W%5Cu00fcrzburg%22%2C%22date%22%3A%2201.01.2016%22%2C%22language%22%3A%22%22%2C%22url%22%3A%22%22%2C%22collections%22%3A%5B%222XDMJIQC%22%5D%2C%22dateModified%22%3A%222022-01-13T15%3A51%3A34Z%22%7D%7D%5D%7D
1.
Fischer K (2025) Erfassung räumlich-zeitlicher Landschaftsdynamiken im Niedermoorstandort Nedlitzer Niederung mittels Sentintel-2 Zeitserien. Martin-Luther-Universität Halle-Wittenberg
1.
Genau D (2024) Erfassung von Landschaftsdynamiken in der Nedlitzer Niederung mittels Sentinel-1 SAR und In Situ-Daten im Zeitraum 2016 - 2023. Martin-Luther-Universität Halle-Wittenberg
1.
Löw J (2016) Analyse der Bodenfeuchteentwicklung in zentralasiatischen Bewässerungssystemen anhand von ASCAT-Zeitserien. Julius-Maximilians-Universität Würzburg