Abstract: In order to timely learn sugarcane harvesting progress information, improve information management level of sugarcane harvesting process in sugarcane milling season, based on domestic remote sensing cloud computing platform PIE-Engine, taking 2020/2021 milling season of sugarcane in Xingbin District, Laibin City, Guangxi as an example, NDVI time series dataset was generated by using Sentinel-2 multispectral images at three key time points before sugarcane harvest, according to the NDVI trend differences of main crops in the area, sugarcane planting areas were extracted by unsupervised classification．On this basis, the radar vegetation index（RVI）time series data set was synthesized by using characteristics of short revisit period and all-weather of Sentinel-1 dual-polarization SAR data, and approximate harvesting dates of different sugarcane planting areas were obtained through change detection．An on-line remote sensing monitoring program of sugarcane harvesting progress in county area was developed on pie-Engine platform．The sugarcane planting area in Xingbin district in 2020 extracted by this program was close to the stable planting area for many years．Statistical analysis and display of sugarcane harvesting progress in Xingbin district 2020/2021 milling season was realized as well．Study confirmed that sugarcane harvesting monitoring based on domestic remote sensing cloud computing platform was feasible．