Land Cover Classification Using Landsat 7 Data for Land Sustainability

Detection of land use/land cover with the help of satellite image data and extraction of geographical features is a challenging problem as it requires continuous monitoring and accurate processing of the images. For environment change management, Land Use Land Cover (LULC) information plays a vital part. This paper proposes a way for the detection of LULC types such as buildings, vegetation, water bodies, etc. with the use of Landsat 7 multispectral satellite images in Sabarmati Riverfront region, Ahmedabad, India. Landsat images have become valuable as well as a free resource as it provides the factors like high resolution, temporal distribution, and availability for the detection of LULC. Further, the use of the QGIS tool based Maximum/Minimum likelihood classification helps to explore and object-based image classification. Thus, Continuous monitoring over the same area will give the difference of LULC resulting in rapid or slower growth of land cover land use region. The proposed method gave a high rate of success and approximate 70–80% accurate results of LULC over period of 2014–2022.