The integration of Remote Sensing (RS) and Geographic Information Systems (GIS) has transformed agricultural monitoring and extension services by enabling real-time, location-specific, and data-driven decision-making. This study explores the conceptual framework, technologies, and practical applications of RS and GIS in monitoring crop health, predicting yield, and delivering adaptive agri-advisories. It highlights the capabilities of satellite imagery, UAVs, hyperspectral and thermal imaging, and their integration within GIS platforms to support sustainable and precision agriculture. The paper reviews notable initiatives such as India’s FASAL project and platforms like GeoFarmer, which demonstrate the effectiveness of geospatial tools in improving farm-level interventions. Furthermore, the study examines the growing role of Artificial Intelligence and Big Data in enhancing the accuracy and reach of extension services. Despite these advances, challenges persist, including high costs, technical capacity gaps, limited rural infrastructure, and the need for better socio-economic data integration. The paper concludes with future directions and policy implications, emphasizing the need for investment in digital infrastructure, training, open-data access, and public-private partnerships to make RS-GIS-based agriculture more inclusive, resilient, and impactful.
V et al. (Wed,) studied this question.
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