Crop Health Assessment Using Sentinel-1 SAR Time Series Data in a Part of Central India

In India, agriculture monitoring is severely hampered by frequent cloud cover. Crop health assessment from the early growing stage onwards is vital for accurate and timely yield prediction. In this study, time series of Sentinel-1A SAR images over central India have been processed to quantify kharif crops’ growth rate. Sentinel-1 and Sentinel-2 images acquired on the same day have been used to compare the radar backscattered energy at the VH channel with normalized difference vegetation index (NDVI). A good coefficient of determination ( R 2 = 0.824) was found between backscatter and NDVI. It attests that the NDVI can be used in combination with SAR backscatter during the kharif season. In addition, k -means clustering classification of Sentinel-1 images indicated that the total area covered by paddy, soybean, and other crops were 103,506.86 ha, 85,390.93 ha, and 71,667.02 ha, respectively. The classification result has been validated with ground information, which has indicated an overall accuracy of 83.47%. The work indicated that radar signals’ temporal behavior is sensitive to the health status of the crops from sowing to harvesting stages. Sentinel-1 SAR images can be used to analyze kharif crops during the whole phenological cycle. The approach may serve as a solution for assessing both the health and spatial distribution of kharif crops.