Aim of the study:
The study aims to assess the feasibility of using remote sensing to estimate crop area and yield in a major rice-growing region of Maharashtra.

Material and methods:
Recent advancements in remote sensing technology, including improvements in image resolution and availability, allowed for timely data collection. The study employs a random forest classifier to identify rice crop using sentinel-1A SAR temporal backscatter satellite images. Additionally, a semi-physical method that incorporates remote sensing and physiological concepts such as Photo-synthetically Active Radiation and a fraction of PAR absorbed by the crop is used to estimate crop yield.

Results and conclusions:
Net Primary Product was calculated using the Monteith model. The calculation of Kharif rice yield involved considering the actual NPP, Radiation use efficiency, and Harvest index. The present study was conducted throughout two kharif seasons, 2020 and 2021. Although there are minor differences in kharif rice area and yield estimations, the model is still applicable in other significant kharif rice-growing regions of India.