Green vegetation detection in satellite imagery using the normalised difference vegetation index method.

With unmatched growth of the human population, it has become difficult for the government to keep track of farmland's correct map, which is critical for estimating the country's agricultural state, resources based on nature, utilisation of land along with mapping, observing and planning of infrastructure. It has also become mandatory for agricultural services to operate with maximum efficiency of our needs. This research uses EarthPy in order to work with geospatial data and focuses on detection of green vegetation from satellite images based on one of the methodologies of remote sensing, i.e., normalised difference vegetation index (NDVI). This utilises the sensing of multi-spectral remote information methods for estimating the density of green on an area of land and to classify whether the area comprises high vegetation, low vegetation, or no vegetation directly from satellite image with the help of very less band merging of the remotely sensed information.