Mapping rice areas with Sentinel-1 time series and superpixel segmentation

Abstract

Rice is the single most important crop for food security in Asia. Knowledge about the distribution of rice fields is also relevant in the context of green-house relevant methane emissions, disease transmission and water resource management. Copernicus Sentinel-1 provides the first openly available archive of C-band SAR data at high spatial and temporal resolution. We developed one of the first methods that shows the potential of this data for accurate and timely mapping of rice growing areas. We used superpixel segmentation to create spatially averaged backscatter time-series, which are robust to speckle and reduce the amount of data to process. This method has been applied to six study sites in different rice growing regions of the world and achieved an average overall accuracy of 0.83.