Spatio-temporal assessment of land use land cover based on trajectories and cellular automata Markov modelling and its impact on land surface temperature of Lahore district Pakistan.

This research aims to assess the urban growth and impact on land surface temperature (LST) of Lahore, the second biggest city in Pakistan. In this research, various geographical information system (GIS) and remote sensing (RS) techniques (maximum likelihood classification (MLC)) LST, and different normalized satellite indices have been implemented to analyse the spatio-temporal trends of Lahore city; by using Landsat for 1990, 2004, and 2018. The development of integrated use of RS and GIS and combined cellular automata-Markov models has provided new means of assessing changes in land use and land cover and has enabled the projection of trajectories into the future. Results indicate that the built-up area and bare area increased from 15,541 (27%) to 23,024 km 2 (40%) and 5756 km 2 (10%) to 13,814 km 2 (24%). Meanwhile, water area and vegetation were decreased from 2302 km 2 (4%) to 1151 km 2 (2%) and 33,961 km 2 (59%) to 19,571 km 2 (34%) respectively. Under this urbanization, the LST of the city was also got affected. In 1990, the mean LST of most of the area was between 14 and 28 ℃, which rose to 22-28 ℃ in 2004 and 34 to 36 ℃ in 2018. Because of the shift of vegetation and built-up land, the surface reflectance and roughness of each land use land cover (LULC) class are different. The analysis established a direct correlation between Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI) with LST and an indirect correlation among Soil Adjusted Vegetation Index (SAVI), Normalized Difference Built-up Index (NDBI), and Built-up Index (BI) with LST. The results are important for the planning and development department since they may be used to guarantee the sustainable utilization of land resources for future urbanization expansion projects.