Multi-year paddy planting acreage estimation based on SAR and MODIS satellite data

Year 2025, Volume: 7 Issue: 2, 391 - 406, 30.12.2025

Pritam K Meshram , Kishan Singh Rawat , Sudhir Kumar Singh

https://doi.org/10.51489/tuzal.1704187

Abstract

Precise and immediate details about paddy planting areas are crucial for agricultural planning, management of water resources, and yield estimation. The aim was to use multi-year Sentinel-1 SAR and MODIS-NDVI to estimate paddy planting acreage in the high rainfall zone of eastern Maharashtra, India. In this study, satellite data was analyzed for the period of 2020-2022, during the paddy growing season (June-November) using a random forest classifier to distinguish between paddy and non-paddy pixels. Sentinel-1 SAR (VH polarization) showed better accuracy than MODIS NDVI in identifying paddy fields, with an 84.7% to 86.4% (k value 0.80 – 0.82) overall accuracy compared to 67.2% - 71.3% (k value 0.58 - 0.61) for MODIS NDVI. However, MODIS NDVI was better at mapping the morphology of the fields. The study suggests that Sentinel-1 SAR (VH polarization) can be used effectively in cloud-prone areas to monitor paddy transplantation and acreage estimation, compensating for the missing data caused by clouds and rain.

Keywords

SAR , MODIS , SNAP , Time series , Google earth engine , Random forest

Ethical Statement

NA

Supporting Institution

NA

Project Number

NA

Thanks

NA

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