UAV-Based Crop Health Analysis Using the Normalized Difference Vegetation Index (NDVI) Method

The agriculture sector is under stress due to the change in the climate, increasing population, and traditional cultivation practices. Moreover, small landholding capacity and increasing pollution, which caused land degradation, are responsible for lowering agriculture income. Therefore, smart farming or precision agriculture are imperative solutions due to their potential and efficacy. In this case, remote sensing-based techniques are efficiently used in agricultural sectors for crop monitoring. However, satellite-based crop monitoring has limitations, such as data unavailability in rainy seasons due to dense cloud cover, low spatial resolutions, and timely unavailability. However, unmanned aerial vehicles (UAVs) are game changers in the agriculture sector because UAVs can perform various operations like spraying, crop monitoring, fertilizer, yield estimation, irrigation mapping, disease monitoring, etc. Therefore, the present research used the DJI Phantom P4 UAV with a multispectral camera to monitor cotton health using NDVI. It is observed that the cotton cultivated with poly-mulch has better health than cotton cultivated without poly-mulch.