Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-8799
Main Title: Analyzing Temporal and Spatial Characteristics of Crop Parameters Using Sentinel-1 Backscatter Data
Author(s): Harfenmeister, Katharina
Spengler, Daniel
Weltzien, Cornelia
Type: Article
Language Code: en
Abstract: The knowledge about heterogeneity on agricultural fields is essential for a sustainable and effective field management. This study investigates the performance of Synthetic Aperture Radar (SAR) data of the Sentinel-1 satellites to detect variability between and within agricultural fields in two test sites in Germany. For this purpose, the temporal profiles of the SAR backscatter in VH and VV polarization as well as their ratio VH/VV of multiple wheat and barley fields are illustrated and interpreted considering differences between acquisition settings, years, crop types and fields. Within-field variability is examined by comparing the SAR backscatter with several crop parameters measured at multiple points in 2017 and 2018. Structural changes, particularly before and after heading, as well as moisture and crop cover differences are expressed in the backscatter development. Furthermore, the crop parameters wet and dry biomass, absolute and relative vegetation water content, leaf area index (LAI) and plant height are related to SAR backscatter parameters using linear and exponential as well as multiple regression. The regression performance is evaluated using the coefficient of determination (R 2 ) and the root mean square error (RMSE) and is strongly dependent on the phenological growth stage. Wheat shows R 2 values around 0.7 for VV backscatter and multiple regression and most crop parameters before heading. Single fields even reach R 2 values above 0.9 for VV backscatter and for multiple regression related to plant height with RMSE values around 10 cm. The formulation of clear rules remains challenging, as there are multiple influencing factors and uncertainties and a lack of conformity.
URI: https://depositonce.tu-berlin.de/handle/11303/9766
http://dx.doi.org/10.14279/depositonce-8799
Issue Date: 2-Jul-2019
Date Available: 12-Aug-2019
DDC Class: 630 Landwirtschaft und verwandte Bereiche
Subject(s): precision agriculture
crop monitoring
Sentinel-1
backscatter
field variability
biomass
Sponsor/Funder: BMEL, 2815710715, Verbundprojekt: Erzeugung von landwirtschaftlichen Ertragspotenzialkarten durch Fusion von Ertragskartierungen, Fernerkundungsdaten, digitaler Reliefauswer-tung und Bewirtschaftungsdaten (AgriFusion) - Teilprojekt 1
License: https://creativecommons.org/licenses/by/4.0/
Journal Title: Remote Sensing
Publisher: MDPI
Publisher Place: Basel
Volume: 11
Issue: 13
Article Number: 1569
Publisher DOI: 10.3390/rs11131569
EISSN: 2072-4292
Appears in Collections:FG Agromechatronik » Publications

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