Abstract            Volume:12  Issue-4  Year-2024         Original Research Articles

Online ISSN : 2347 - 3215 Issues : 12 per year Publisher : Excellent Publishers Email : editorijcret@gmail.com

Accurate and timely estimation of crop area is crucial for effective agricultural planning, food security assessments, and precision farming interventions. This study demonstrates the potential of Sentinel-1A Synthetic Aperture Radar (SAR) data for kharif paddy area estimation in Thanjavur district, a major rice-producing region in the Cauvery Delta of Tamil Nadu, India. Utilizing freely available C-band SAR data acquired at 12-day intervals between May and October 2019, a robust multi-temporal feature (MTF) extraction technique was employed to characterize the phenological stages of paddy cultivation. Pre-processing steps including speckle filtering, terrain correction, and atmospheric attenuation removal were conducted using the MAPscape-RICE processing chain. Key temporal features—such as VV minimum, VH maximum backscatter, and their corresponding dates—were derived and integrated into a parameterized classification framework. Ground truth data comprising 130 samples were used for training and validation, with 60% reserved for accuracy assessment. The classification achieved an overall accuracy of 94% and a Kappa coefficient of 0.77, indicating strong agreement with field observations. Spatial analysis revealed the temporal onset of the paddy season across different blocks within Thanjavur, providing insights into intra-regional cropping dynamics. The study validates the operational applicability of SAR-based remote sensing for paddy area estimation, particularly in regions frequently affected by cloud cover where optical sensors are limited. The results support SAR data as a reliable tool for agricultural monitoring, offering spatially explicit crop maps critical for decision-makers in precision agriculture and policy formulation.

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