Using GIS for Precision Agriculture: Monitoring Crop and Soil Health
Keywords:
Precision, Agriculture, application, farmersAbstract
Precision Agriculture, also known as Precision Farming, uses modern technology and field data to take the right measures at the right time. This manufacturing process calls for site-specific management changes. This approach uses modern technology-enabled tools and information. GPS, GIS, yield monitoring equipment, soil, plant, and pest sensors, remote sensing (RS), and variable rate input applicator technologies are examples (Santosh et al. 2003). Remote sensing is essential for crop health and yield predictions, crop acreage estimates, crop pests and diseases identification, disaster location and mapping, wildlife management, water supply information, weather forecasting, rangeland management, and livestock surveys (Patil and Chetan 2017). Remote sensing can automate and impartially assess plant diseases (Mahlein et al. 2012). Huang et al. (2012) found that plant diseases have cost global agriculture productivity. PA applications often employ the Normalized Difference Vegetation indicator (NDVI) to measure green content. The NDVI index is calculated using R and NIR channels. Healthy plants absorb more NIR light but little red light (Shafi et al. 2019). Precision agronomic and economic decisions may benefit from remote sensing. Precision agriculture, largely from Western countries, is underutilized in India owing to farmer ignorance.
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