• Sanjay K. Tupe

Remote sensing (RS) technologies have significantly revolutionized modern agriculture by providing real-time, non-invasive, and spatially extensive observations for better decision-making in crop management, soil assessment, water utilization, and pest control. The integration of satellite platforms, unmanned aerial vehicles (UAVs), and advanced sensors, including multispectral, hyperspectral, and thermal imaging devices has enabled precision agriculture practices at various scales. Artificial intelligence (AI) and machine learning (ML) models now play a pivotal role in extracting actionable insights from the high-dimensional datasets generated through RS. In the Indian context, government initiatives and technological innovations are rapidly accelerating the adoption of these tools, though challenges such as cloud cover, data processing complexity, and limited farmer access persist. This paper reviews the current state of RS-based agriculture, focusing on platforms, sensor technologies, analytical methodologies, and real-world applications, particularly within India. It also highlights the challenges and potential future developments in this rapidly evolving field.

Remote sensing, precision agriculture, UAV, NDVI, hyperspectral imaging, crop monitoring, machine learning, Indian agriculture

"Remote Sensing in Agriculture: Advances, Applications, and Future Directions in the Indian Context", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 8, page no.e101-e105, August-2025, Available :http://www.jetir.org/papers/JETIR2508414.pdf

"Remote Sensing in Agriculture: Advances, Applications, and Future Directions in the Indian Context", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 8, page no. ppe101-e105, August-2025, Available at : http://www.jetir.org/papers/JETIR2508414.pdf