Digital Change Detection Analysis Criteria and Techniques used for Land Use and Land Cover Classification in Agriculture

The term "Land Cover" (LC) refers to the physical characteristics of the land, such as flora, water bodies, building areas, and forests. Identifying them using a remote sensing dataset is called land cover mapping. Land Use (LU) is a series of activities carried out on land by humans to obtain products. Land use classification examples include cropland, a built-up region used for business or industrial needs. Mapping and monitoring both land use and land cover (LULC) can be carried out using remote sensing datasets like Sentinal-2 Landsat-8 etc. Compared to algebra-based change detection techniques, the change vector analysis method offers a higher level of accuracy, according to the current study. This paper discussed the change detection analysis criteria and techniques which can be used for detecting the change and also compared the accuracy of different classifiers used for land use land cover in Agriculture.