Agricultural monitoring from combined optical and SAR data

Vegetation indices derived from optical remote sensing data are a valuable source of information for agricultural monitoring. However, cloud cover over some areas reduces the number of useful observations, which can difficult the detection of changes in crop condition. In this context, synthetic aperture radar (SAR) systems are an interesting alternative due to their low sensitivity to clouds. In this work, we analyze the relationship between SAR backscatter from Sentinel-1 and vegetation indices derived from the Harmonized Landsat-8 Sentinel-2 (HLS) product using data from year 2017 over an agricultural region in Ukraine. Results show a strong relationship between SAR data from Sentinel-1 and optical indices for all the analyzed crop types. In the case of winter crops, the ratio between Gamma-0 VH and VV polarization showed the highest relationship with the Difference Vegetation Index (DVI), while for summer crops the highest relationship was shown by the Gamma-0 VH polarization and DVI. Further work is being developed to exploit more complex SAR models which account for other variables that affect the backscatter signal such as soil moisture.