Vol. 11, Special Issue 11 (2022)

Land use and Land cover (LULC) classification of satellite imagery is an essential research field and analyzed extensively in remote sensing. Although, precise and accurate land use land cover detection is still a challenge. This paper represents LULC classification of Sentinel 2 imagery using Minimum distance classifier. The study area for the present work is Jabalpur District of Madhya Pradesh, India. The Minimum distance classifier was applied to classify the image into five LULC classes viz. agriculture, vegetation, open/fallow/barren land, water body and habitation. It was found that agriculture covers 48.78%, 13.21% is occupied by vegetation, open/fallow land comprises of 34.04% area, 2.20% is covered by water body while habitation occupies 1.76% of the total area. The classification accuracy for multispectral image was found to be 87.75%.