Optimizing Fertilizer Use in Precision Agriculture with GIS and Remote Sensing

Optimization of fertilizer is important for increasing the yield of crops as well as for increased crop value and efficiency with low environmental impact. It achieves this by accurately tailoring nutrient applications that avoid the challenges of overuse and one of the contributing causes of runoff — otherwise, fertilizers help crops grow optimally and sustainably. An integrated approach in the GIS/remote sensing framework for fertilizer use in precision agriculture is proposed in this work. First, there is the gathering of soil samples, remote sensing imagery, and weather data. Imageries undergo pre-processing to produce vegetation indices and GIS maps to have soil properties and topography. In the processing stage, spatial analysis is done to discover nutrient and crop health variations which lead to a fertilizer optimization model that allocates specific rates of fertilizer application. The optimized fertilizer application map and expected impact on yield are produced at the last computation stage and yielded and maximum potential yield is predicted. The idea behind this method is to have more exact 'fertigation' by making fertilizer more efficient combining as much as possible to maximize yield while minimizing environmental impact through detailed data analysis and advanced modeling. This dramatically improves the results obtained on agricultural efficiency and sustainability. NDVI data and variability in the soil nutrient are integrated to precisely taper fertilizer application to the agricultural field zone needs. This targeted approach is aimed at enhancing crop health by application of nutrients only in areas where nutrient levels are low and reducing the potential of application of excessive amounts of nutrients in areas where nutrient levels are already sufficient. Therefore, nutrient utilization is improved and crop yields increase, with a decrease in environmental effects. The detailed yield improvement maps provide farmers with a way to identify and prioritize zones where efforts in yield improvement should first be targeted for an improved resource allocation strategy. This method produces more crops with less cost, thus minimizing the harm to the environment, it will facilitate more sustainable farming operations and more efficient use of fertilizer.