Use of time series Sentinel-1 and Sentinel-2 image for rice crop inventory in parts of Bangladesh

Abstract  

Synergistic use of satellite data has an advantage over single-source data as optical, thermal, and microwave datasets. Previous studies have demonstrated the efficacy and focused mainly on the edge of the multisensory data over the stand-alone system due to primarily multi-dimension input. Crop classification and crop type mapping is the first step in the natural resource management theme, especially in agriculture. During the rainy season, accurate crop classification with crop-cultivar type mapping is the most challenging target to achieve using optical datasets. Therefore, the study’s prime focus was to extract the temporal signature of rice crop types from multi-temporal SAR datasets and classify various rice crop types based on sowing timing in the dominant production zone of rice, the Jashore district of Bangladesh. Sentinel-1 datasets were used primarily for the rainy season from July to September 2018; in addition, Sentinel-2 data of October was used to understand the relationships among these datasets. The temporal signature of various types of rice and others features was interpreted. Besides, the correlation between Sentinel-1 backscatter with Sentinel-2 derived indices has been exercised to find out a comprehensive framework for selection of optical vegetation indices which may be used as a proxy of SAR or vice-versa. The classified image from Sentinel-2 has around 80% overall accuracy, and 0.71 value of kappa coefficient for rice crop type mapping was comparable to SAR (about 80% for late sown crop and slightly less for the other 2 classes); class accuracy of the rice crop is 88–90% using three-date dual-polarized data. The latter’s advantage is early estimate availability during the initial crop phase when optical data is not available. Three types of rice were observed to be cultivated; these are early transplanted rice, late transplanted rice, and very late transplanted rice; among them, late transplanted rice covered a large area, and early transplanted rice covered lesser areas during the session. Sentinel-2 derived spectral indices have a higher correlation with very late rice crop type for VV backscatter than early (where the response in VH was significant probably after saturation in VV response due to matured crop) and late rice crop types. Understanding the micro and macro-scale crop structure from a multisource- remote-sensing perspective builds novelty in this research.