Detection of land use/land cover changes in a watershed: A case study of the Murredu watershed in Telangana state, India

Abstract

Land-use change refers to a change in how a particular area of land is utilised or managed by humans. Land-cover change refers to a change in some continuous features of the land, such as vegetation type, soil conditions, and so on. For the purpose of identifying change-vulnerable areas and creating sustainable ecosystem services, mapping and quantifying the state of land use/land cover (LULC) changes and change-causing factors are crucial. The present research utilizes a geographic information system (GIS) and remote sensing (RS) techniques to categorise and identify changes in a Murredu watershed in Telangana state, India, between 1996 and 2019. Five major LULC categories (agricultural land, forest, barren land, built-up area, and waterbodies) from satellite images of 1996 to 2019 were mapped. The maximum likelihood approach was used to supervise the classification process, and high-resolution Google Earth Pro was used to evaluate the accuracy of the classified map. The accuracy of the mapping was evaluated using the error matrix and Kappa statistics. Overall classification accuracy for the classified image of 2019 was found to be 90 % with overall kappa statistics of 85.98%. From these findings, change detection analysis shows that the area used for agricultural land, barren land, forest, built-up areas, and waterbodies has increased by 5.17%, 3.39%, 0.84%, and 0.26%, respectively, between 1996 and 2019. The forest area has decreased by 9.67% at the same time. Therefore, this research anticipates that the findings might provide information to planners, land managers, and decision-makers for the sustainable management and development of the natural resource.