DiP-ZAZIkI (ZAZIkI)
Projekt: DiP-ZAZIkI
Steckbrief ZAZIkI

Projekt Titel
DiP-ZAZIkI
(Original TitelZukunftsfähige Anbausysteme Zuckerrübe – Innovationen und künstliche Intelligenz)
Projekt-Webseite
Projektlaufzeit
01.04.2024 – 31.12.2028
Projektleitung
Prof. Dr. Christopher Conrad
Projektausrichtung
Forschung & Wissenstransfer
Untersuchungsgebiet
Süd-Sachsen-Anhalt
Kontakt
Projekt-Mitarbeiter*innen
Fördermittelgeber*innen
Partner*innen
Publikationen
2355391MDLREVTXPeerReview, ZAZIKI american-journal-of-plant-sciences50datedesc1 5458https://geo.uni-halle.de/wp-content/plugins/zotpress/
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landscape%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%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffrsen.2025.1610005%22%2C%22citationKey%22%3A%22%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%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-6187%22%2C%22language%22%3A%22English%22%2C%22collections%22%3A%5B%22MDLREVTX%22%5D%2C%22dateModified%22%3A%222025-08-29T08%3A44%3A38Z%22%7D%7D%5D%7D
1
Löw, J., Conrad, C., Hill, S., Thiel, M., Ullmann, T. and Otte, I. (2026) A Novel Approach to Assessing the Tracking Accuracy of Crop Phenology for Multi-Orbit and Multi-Feature Sentinel-1 Time Series. Science of Remote Sensing, 100370. https://doi.org/10.1016/j.srs.2026.100370.
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.
2355391MDLREVTXConferencePaper, ZAZIKI american-journal-of-plant-sciences50datedesc1 5458https://geo.uni-halle.de/wp-content/plugins/zotpress/
2355391MDLREVTXZAZIKI, Presentation american-journal-of-plant-sciences50datedesc1 5458https://geo.uni-halle.de/wp-content/plugins/zotpress/
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Löw, J., Hill, S., Friedrich, C., Otte, I., Ullmann, T. and Conrad, C. (2025, June 23) A Relational Framework for Investigating Phenological Development at Landscape and Field Level via Sentinel-1 Time Series. Vienna.
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Löw, J., Hill, S., Otte, I., Thiel, M., Ullmann, T. and Conrad, C. (2025, May 29) Linking Phenological Development at Landscape And Field Level By Means Of Sentinel-1 Time Series. Prague.
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