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.
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