Journal Press India^®

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This study examines the spatial structure and temporal dynamics of cropping systems in Chikkaballapur District, Karnataka, using integrated geospatial techniques. Multi-sensor remote sensing datasets from Sentinel-1 Synthetic Aperture Radar (SAR), Sentinel-2 multispectral imagery, and Landsat time series were combined with GIS-based spatial analysis to assess crop distribution, cropping intensity, diversification, and land-use change at the taluk level. Vegetation indices, radar backscatter metrics, and machine learning classification methods were employed to generate high-resolution thematic maps and quantitative indicators. The results reveal pronounced spatial heterogeneity in cropping intensity and diversification, largely driven by irrigation availability, topography, and market accessibility. Irrigated taluks exhibit higher cropping intensity and greater adoption of horticultural crops, while rainfed regions show persistent fallow land and lower vegetation vigor. The study demonstrates the effectiveness of multi-sensor data integration for fine-scale agricultural assessment and provides evidence-based insights to support sustainable land-use planning and water resource management in semi-arid regions.

Keywords

Cropping systems; Geospatial analysis; Remote sensing; Cropping intensity; GIS; Land use

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