A cloud computing and spatial modelling-based assessment for land use and land cover dynamics and their association with urban surface temperature

Evaluation of spatial-temporal patterns is essential to ensure long-term sustainability in land use land cover (LULC) and associated operations, such as land surface temperature (LST). Our study employed and generated data on spatial-temporal changes in LULC and LST for 1990–2020 (the past three decades) in the Gujrat district of Pakistan using geoinformation modelling and Google Earth Engine (GEE). Our results indicated that "built-up area" increased by 6.1% from 1990 to 2020. Agricultural land coverage decreased from 74.37% in 1990 to 72.76% in 2020; the "vegetation" showed a negative shift of 1.62%, despite a decrease in "farm area" between 1990 and 2020. The mean normalised difference vegetation index (NDVI) value also reduced from 0.23 to 0.18 between 1990 and 2020. In the year 1990, the LST ranged from 10.2 to 44.2 °C, whereas in 2000, it ranged from 10.5 to 44.4 °C. The LST values ranged from 10.6 to 44.7 °C in 2010 and from 10.9 to 45.1 °C in 2020. The regression coefficients (R²) between NDVI and LST were 0.82, 0.80, 0.79 and 0.75 in 1990, 2000, 2010 and 2020 respectively. The study’s findings are significant for mitigating and adapting to climate change, given the link between LULC and LST. Thus, this enables the establishment of sustainable LULC planning and management protocol.