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Rapid urbanization is changing the existing patterns of Land Use Land Cover (LULC) globally which is consequently increasing the Land Surface Temperature (LST) in many regions. Present study was focused on estimating the current and simulating the future LULC and LST trends in the alpine environment of lower Himalayan region of Pakistan. Past patterns of LULC and LST were identified through the Support Vector Machine (SVM) and multi-spectral Landsat satellite images during 1987-2017 data period. The Cellular automata (CA) model and Artificial Neural Network (ANN) were applied to simulate future (years 2032 and 2047) LULC and LST changes, respectively, using their past patterns. CA model was validated for the simulated and the estimated LULC for the year 2017 with an overall Kappa (K) value of 0.77 using validation modules in QGIS and IDRISI software. ANN method was validated by correlating the observed and simulated LST for the year 2017 with correlation coefficient (R) and Mean Square Error (MSE) values of 0.81 and 0.51, respectively. Results indicated a change in the LULC and LST for instance the built-up area was increased by 4.43% while agricultural area and bare soil were reduced by 2.74% and 4.42%, respectively, from 1987 to 2017. The analysis of LST for different LULC classes indicated that built-up area has highest temperature followed by barren, agriculture and vegetation surfaces. Simulation of future LULC and LST showed that the built-up area will be increased by 2.27% (in 2032) and 4.13% (in 2047) which led 42% (in 2032) and 60% (in 2047) of the study area as compared to 26% area (in 2017) to experience LST greater than 27 degrees C. A strong correlation between built-up area changes and LST was thus found signifying major challenge to urban planners mitigating the consequent of Urban Heat Island (UHI) phenomenon. It is suggested that future urban planning should focus on urban plantation to counter UHI phenomena in the region of lower Himalayas.