Vol. 11, Special Issue 3 (2022)

Author(s):
Govind Madariya, Dr. SK Pandey and Dr. SK Sharma

Abstract:
This study reviewed a number of supervised and unsupervised techniques of Land Use and Land Cover classification. Land use and land cover is a basic concept of the Earth's system that is associated with the relationship between humans’ activities and the environment. Frequently updated land use/land cover information is necessitated for many socioeconomic and environmental activities, such as urban and regional planning, natural resource conservation and management, etc (Homer et al., 2007; Lu and Weng, 2007; Jensen, 2009). Earth observation technology such as remote sensing offers a useful source of data that covers the earth surface at a spatial and spectral resolution that allows easier land use and land cover classification than traditional approaches. LULC map is the most significant remote sensing products, which is achieved by a technique called image classification. Classification is a very important statistical method for obtaining information from satellite images. LULC maps are essential for monitoring of numerous earth observation activities such as land use planning, natural resources inventories, agricultural forecasting, deforestation, environmental disasters monitoring and estimation of soil erosion. As enough platforms are deployed in orbit and new applications arise in various fields, so many researchers in LULC have examined in various sections of subjects during the last two decades. The purpose of the study is to provide consistent information on all-encompassing algorithms of supervised and unsupervised technique for LULC mapping.