Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications

Abstract

Crop monitoring information is essential for food security and to improve our understanding of the role of agriculture on climate change, among others. Remotely sensing optical and radar data can help to map crop types and to estimate biophysical parameters, especially with the availability of an unprecedented amount of free Sentinel data within the Copernicus programme. These datasets, whose continuity is guaranteed up to decades, offer a unique opportunity to monitor crops systematically every 5 to 10 days. Before developing operational monitoring methods, it is important to understand the temporal variations of the remote sensing signal of different crop types in a given region. In this study, we analyse the temporal trajectory of remote sensing data for a variety of winter and summer crops that are widely cultivated in the world (wheat, rapeseed, maize, soybean and sunflower). The test region is in southwest France, where Sentinel-1 data have been acquired since 2014. Because Sentinel-2 data were not available for this study, optical satellites similar to Sentinel-2 are used, mainly to derive NDVI, for a comparison between the temporal behaviors with radar data. The SAR backscatter and NDVI temporal profiles of fields with varied management practices and environmental conditions are interpreted physically. Key findings from this analysis, leading to possible applications of Sentinel-1 data, with or without the conjunction of Sentinel-2, are then described. This study points out the interest of SAR data and particularly the VH/VV ratio, which is poorly documented in previous studies.

Crop Monitoring Using Sentinel-1 Data: A Case Study from The Netherlands

“…VV backscatter is dominated by the direct ground and canopy contributions. The decrease in VV during the stem elongation is therefore attributed to the increasing attenuation due to the predominantly vertical structure of the wheat [24,25,[55][56][57][58]. The decrease observed in VH is less severe than in VV.…”

“…VH backscatter is influenced by double-bounce between the wheat stems and the ground [55,59] as well as a volume scattering component [48]. During the tillering and stem elongation periods, the increased attenuation of the double-bounce is countered by an increase in volume scattering from the new biomass [24,48]. The net effect is an increase in the VH/VV ratio, affirming its suitability as a measure of fresh biomass [25].…”

“…The heavy rain events on 9 June, 3 July, 8 August, 13 September and 7 October result in peaks of similar magnitudes in both VV and VH backscatter. The effect of precipitation/soil moisture on the VH/VV ratio is therefore limited, confirming that VH/VV is a good indicator of fresh biomass and vegetation water content [24,25].…”

“…This can be explained by an increase in the double bounce between the vertical stalks and the soil [47,48]. While some studies report an increase in VV backscatter associated with maize biomass [48,49], others have reported no correlation or even an inverse relation between maize biomass and VV backscatter intensity [24,50]. The VV and VH backscatter start to plateau as the maize reaches its maximum height and the grain begins to develop (BBCH 71).…”

“…Harvesting reduces the backscatter, particularly in VH, and increases the spread in VV, VH, and VH/VV backscatter among the parcels. Harvesting the vegetation removes the dense maize canopy which reduced the sensitivity of both VV and VH backscatter to soil moisture signal during the growing season [24,49,53]. However, one reason why the harvest of the maize, sugar beet and potato is more difficult to detect in the autumn months is the elevated soil moisture.…”