Using google earth engine to detect the land use changes, climate change and vegetation dynamics

Abstract Evaluating spatial–temporal patterns in land use and land cover (LULC) and related operations, like land surface temperature (LST), is crucial to ensuring long-term sustainability at all levels. The main purpose of this research, identify the LULC and LST changes over a 20 years in the Vehari district using Google earth engine (GEE). A combination of GEE and training points were used to create the LULC maps for 2003, 2013, and 2023 and also determine the connection between temperature and normalized difference vegetation index (NDVI) in study area. According to this study, build-up area was increased from 402 sq. km. (8.55%) to 742 sq. km. (16.93%) from 2003 to 2023, while the amount of vegetation decreased by 418 sq. km. (7.34%) in study area. In general, LST values were calculated from 12.11 °C to 27.17 °C in 2003, 16.24 °C to 34.65 °C in 2013, and 19.88 °C to 41.68 °C in 2023 in district Vehari. Relation of NDVI with LST, the present study found regression coefficients ( R 2 ) of 0.84, 0.82 and 0.82 for 2003, 2013, and 2023, respectively. Nearly, 79% of farmers reported that weather patterns had changed recently, with 71% stating that this had affected farming and 53% stating that the intensity of rainfall had decreased. To adapt and control agricultural systems in a fair and equitable manner to changing climate circumstances, this study contributes to advancing environmental science while addressing key ecological and societal concerns. The results of this study will, therefore, be very helpful to city planners and political leaders as they create local plans and policies for sustainable LULC management.