Monitoring The Cropping Pattern Of Paddy Fields In Hilly Mountainous Areas Using Time-Series Remote Sensing Data

In this paper, a time-series surface reflectance dataset was constructed based on the time-series Sentinel-2 satellite data with topographic radiation and atmospheric corrections. A Shallow Water Index (SWI) was constructed based on the spectral characteristics of aquatic crop samples. Third, an algorithm for monitoring the cropping pattern of paddy fields was established by combining the time-series SWI and Normalized Difference Vegetation Index (NDVI). The algorithm was applied to monitor the cropping patterns of paddy fields in the Yongchuan District, Chongqing, China. Finally, samples from the field investigations were used to validate the results. The validation results showed that out of the 150 aquatic crop sample points, the monitoring algorithm recognized 143 points as aquatic crops with an accuracy of approximately 95.3%.