Mapping paddy rice using an adaptive stacking algorithm and Sentinel-1/2 images based on Google Earth Engine

Abstract

ABSTRACT Rice is the most important food crop in China, which is of great significance to the country’s food security and regional stability. Therefore, it is very important to accurately monitor the paddy rice planting area and its changes. In this study, an adaptive-stacking method based on Google Earth Engine (GEE) was proposed to identify paddy rice using multi-temporal Sentinel-1 and Sentinel-2 remote sensing data. The classification accuracy and Kappa coefficient are 88.53% and 0.85, respectively. Moreover, the user accuracy and producer accuracy of paddy rice reached 86.58% and 86.92%, respectively. The results demonstrate that the superiority of the strategy that integrates multi-temporal optical and SAR data, and the potential of using adaptive-Stacking algorithm based on the GEE for paddy classification.