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The present study investigates the spatiotemporal pattern of Land Use land cover (LULC) and land surface temperature (LST) in Abha for the years 1990, 2000, and  2018 . This research also forecasts the future LULC and LST for the year 2028. The support vector machine (SVM) was utilised to classify the LULC for the periods 1990-. The LST for the same period was derived using the mono window algorithm. The artificial neural network-cellular automata model (ANN-CA) was employed to forecast LULC and LST for the year 2028. The results indicated that urban areas rose by 434.6% between 1990 and 2018, while the LST soared to 50 °C in 2018, covering half of the study area. The built-up area, as well as the high LST zone, will be expanded in 2028. As a result, sustainable management strategies should be implemented to limit uncontrolled urban sprawl and LST.

geocarto international

Spatio-temporal analysis and simulation of land cover changes and their impacts on land surface temperature in urban agglomeration of Bisha Watershed, Saudi Arabia