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Remote Sens. 2018, 10(9), 1396; https://doi.org/10.3390/rs10091396

Sensitivity of Sentinel-1 Backscatter to Vegetation Dynamics: An Austrian Case Study

1
Department of Geodesy and Geoinformation, TU Wien, 1040 Vienna, Austria
2
Department of Civil Engineering, Monash University, 3800 Clayton, Australia
3
Institute for Land and Water Management Research (IKT), Federal Agency of Water Management, 3252 Petzenkirchen, Austria
*
Author to whom correspondence should be addressed.
Received: 20 July 2018 / Revised: 20 August 2018 / Accepted: 29 August 2018 / Published: 1 September 2018
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Abstract

Crop monitoring is of great importance for e.g., yield prediction and increasing water use efficiency. The Copernicus Sentinel-1 mission operated by the European Space Agency provides the opportunity to monitor Earth’s surface using radar at high spatial and temporal resolution. Sentinel-1’s Synthetic Aperture Radar provides co- and cross-polarized backscatter, enabling the calculation of microwave indices. In this study, we assess the potential of Sentinel-1 VV and VH backscatter and their ratio VH/VV, the cross ratio (CR), to monitor crop conditions. A quantitative assessment is provided based on in situ reference data of vegetation variables for different crops under varying meteorological conditions. Vegetation Water Content (VWC), biomass, Leaf Area Index (LAI) and height are measured in situ for oilseed-rape, corn and winter cereals at different fields during two growing seasons. To quantify the sensitivity of backscatter and microwave indices to vegetation dynamics, linear and exponential models and machine learning methods have been applied to the Sentinel-1 data and in situ measurements. Using an exponential model, the CR can account for 87% and 63% of the variability in VWC for corn and winter cereals. In oilseed-rape, the coefficient of determination ( R 2 ) is lower ( R 2 = 0.34) due to the large difference in VWC between the two growing seasons and changes in vegetation structure that affect backscatter. Findings from the Random Forest analysis, which uses backscatter, microwave indices and soil moisture as input variables, show that CR is by and large the most important variable to estimate VWC. This study demonstrates, based on a quantitative analysis, the large potential of microwave indices for vegetation monitoring of VWC and phenology. View Full-Text
Keywords: Sentinel-1; vegetation water content; microwave indices; crops Sentinel-1; vegetation water content; microwave indices; crops
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Vreugdenhil, M.; Wagner, W.; Bauer-Marschallinger, B.; Pfeil, I.; Teubner, I.; Rüdiger, C.; Strauss, P. Sensitivity of Sentinel-1 Backscatter to Vegetation Dynamics: An Austrian Case Study. Remote Sens. 2018, 10, 1396.

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