The Multi-Temporal Relationship Between Sentinel-1 SAR Features and Sentinel-2 NDVI for Different Land Use / Land Cover Classes in Central Africa

Although rapid detection of ecosystem disruptions is feasible with satellite remote sensing, in many regions optical observations, which are mainly used for this purpose cannot be used on a regular and continuous basis due to cloud cover. Therefore, weather-independent SAR data can serve as a complementary source of information to Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) obtained from multispectral observations. The objective of this study is to assess the impact of the lack of optical data on vegetation monitoring and to evaluate the correlation of SAR features including the VH and VV polarizations, derived from Sentinel-1 and NDVI time series calculated from the Sentinel-2 data for four land use / land cover (LU/LC) classes, i.e. cropland, grassland, shrubland and forest in the Central African region. The results show a high correlation, giving the highest values for cultivated fields and the lowest for forests.