Change detection of land cover/land use dynamics in arid region of Bahawalpur District, Pakistan

Satellite remote sensing is an established geospatial technique that provides a precise method of land use and land cover evaluation at a global, regional, or local scale. The current study aims to assess the land cover and land use change of an arid region in Southern Punjab of Pakistan, i.e., Bahawalpur District. Landsat data is more consistent and pragmatic in providing historical imageries of the earth's surface for conducting such studies for the last 50 years. Satellite data employed in current research includes Landsat 5 TM for historical years of 1987, 1998, and 2009 and Landsat 8 OLI for the t year of 2020. Maximum likelihood supervised classification and change detection techniques are applied to calculate area percent change, annual dynamic rate of change in specific time intervals. Remote sensing indices normalized difference vegetation index and normalized difference bareness index are also employed techniques for change detection procedures in this study. Results show that agriculture area expanded at the rate of 2.3% and barren land reduced at dynamic rate of - 0.5% from 1987 to 2020. Linear regression analysis reveals a strong correlation coefficient R-2 of 0.99 between population growth rate and agriculture growth rate with 0.03 level of significance, 0.58 between agriculture growth rate and barren land reduction rate. Vegetation and bareness index-based change detection showed a 13.4% significant decline in bareness and 16.8% increase in vegetation mostly in southern side of the district towards lesser Cholistan. Linear regression between vegetation and bareness index also showed significant correlation R-2 of 0.83 in 1987 and 0.91 in 2020. Significant land use change in this arid region is deteriorating the natural environment and arid ecosystem of the study area. Study provides a good example for local stakeholders to identify the more vulnerable parts of land use change in the district for better and sustainable land use planning.