Monitoring and prediction of the LULC change dynamics using time series remote sensing data with Google Earth Engine

Urbanization is a significant global problem affecting many regions facing climate change. Land use land cover (LULC), land surface temperature (LST), urban sprawl, and significant concerns. The research objective was to evaluate the effects of LULC change, pre-urban expansion, and urban growth on LST for 30 years (1992, 1997, 2002, 2007, 2012, 2017 and 2022) in District Lahore using Landsat (TM, ETM+, and OLI/TIRS) data in Google Earth Engine (GEE). In this study, we concentrate on four major LULC classes identified: urban area, vegetation, barren land, and water bodies through Landsat data and Support Vector Machine (SVM) in GEE. Results showed that 975.6 km2 (196.5%) of the built-up area increased, while vegetation decreased by 579.15 km2 (30.4%) from 1992 to 2002. Additionally, the normalized difference built-up index (NDBI) and the normalized difference vegetation index (NDVI) were retrieved to measure the association with LST. A negative and positive correlation was found between NDVI, NDBI, and LST, respectively. The urban heat island ratio index (UHIRI) was also mapped, and an upward trend was displayed during this research. These results are crucial for the division of development and planning to secure the enduring utilization of land resources for future urbanization growth.