Remote Sensing and Geographic Information Systems for Precision Agriculture: A Review

C. Sangeetha

Agronomy, Kumaraguru institute of Agriculture, Nachimuthupuram – 638315, Tamil Nadu, India.

Vishnu Moond *

Department of Agronomy, RNT College of Agriculture Kapasan (MPUA&T-Udaipur), Chittorgarh, Rajasthan 312202, India.

Rajesh G. M.

Department of Soil and Water Conservation Engineering, KCAET, Kerala Agricultural University, Thrissur-680 656, India.

Jamu Singh Damor

Department of Soil Science and Agriculture Chemistry, Jawaharlal Nehru Kharshi Vishwa Vidhyalaya, Jabalpur, India.

Shivam Kumar Pandey

Rashtriya Raksha University, India.

Pradeep Kumar

Division of Agricultural Engineering, ICAR-Indian Agricultural Research Institute, New Delhi-110012, India.

Barinderjit Singh

Department of Food Science and Technology, I.K. Gujral Punjab Technical University, Kapurthala, Punjab-144601, India.

*Author to whom correspondence should be addressed.


Abstract

Precision agriculture aims to optimize crop production and minimise environmental impacts by using information technology, remote sensing, satellite positioning systems, and proximal data gathering. This review paper examines current applications and future directions of remote sensing and geographic information systems (GIS) for precision agriculture. Remote sensing provides data on crop health, soil conditions, water status, and yield which can guide variable rate applications within fields. Satellite and aerial platforms allow multispectral and hyperspectral imaging for vegetation indices analysis, crop classification, and stress detection. GIS technology integrates these data layers to model and map variations, develop prescription maps, and analyse spatial relationships. Key research frontiers include high-resolution satellite and drone data for within-field analysis, better integration of proximal and remote sensing, online nutrient and yield monitors, real-time prescription modelling, and predictive analytics using machine learning. Adoption continues to increase with better data analytics tools and greater economic returns realized. Remote sensing and GIS provide an integral platform for variable rate technologies, predictive modelling, and data-driven decision-making for precision agriculture.

Keywords: Precision agriculture, remote sensing, geographic information systems, variable rate technology, vegetation indices


How to Cite

Sangeetha , C., Moond , V., Rajesh G. M., Damor , J. S., Pandey , S. K., Kumar, P., & Singh , B. (2024). Remote Sensing and Geographic Information Systems for Precision Agriculture: A Review. International Journal of Environment and Climate Change, 14(2), 287–309. https://doi.org/10.9734/ijecc/2024/v14i23945

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