Land use/cover change detection through remote sensing and GIS techniques: a case study of Astrakhan, Russia

Abstract

The present study illustrates the spatial-temporal dynamics of Land use/cover change in Astrakhan city, Russia. Landsat satellite imageries of three different time periods of 2000, 2007 and 2015 were acquired by earth explorer website and quantify the changes in the Astrakhan. In this study maximum-likelihood supervised classification along with post-classification change detection was applied to satellite images for 2000, 2007 and 2015 in order to map land use/cover changes. The land use/cover study was classified into five major class’s viz. agriculture, bare-land, settlements, vegetation and water body. The classification results were then further refined using ancillary data, visual interpretation and expert knowledge of the area along with GIS. After post-classification change detection a change image form the cross-tabulations were generated. The result shows extensive vegetation degradation and water logging in different parts of the study area.