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Urban morphological change impacts the land surface temperature (LST) through modifying the net radiation, convective heat transfer, evapotranspiration, and heat storage on the ground. It is essential to quantify the contributions of these physical changes on LST changes. In this work, we conduct simulations using a weather research and forecasting model for the Chengdu–Chongqing urban agglomeration to identify causes of LST changes due to urban morphological changes through different morphological parameters: the aspect ratio, building plan area fraction, and average building height. A new method is proposed and used to quantify the contribution of these physical changes on LST changes. The results show as the aspect ratio increases, an increase of the average LST is induced by variations in radiation, and daytime cooling and nighttime warming are induced by variations in heat storage. There is warming associated with an increase in the building plan area fraction, which is mostly caused by a decrease in the efficiency of the long‐wave radiant heat emitted from the surface to the atmosphere. We also find that an increase in the average building height enhance the efficiency of convective heat transfer, which results in cooling. These results are important for the management of urban thermal environments. Plain Language Summary: Previous studies of the effects of urban morphological changes on the land surface temperature rarely quantified the contributions of different physical changes, including changes of the net radiation, convective heat transfer, evapotranspiration, and heat storage on the ground. Consequently, it is not clear which processes dominate the temperature changes. According to our analysis, which is based on simulations using a weather research and forecasting model, we found that an increase of the aspect ratio increases the radiation absorbed by urban surfaces, leading to an increase in the average temperature. As the aspect ratio increases, daytime cooling and nighttime warming result due to variations in heat storage. An increase of the building plan area fraction weakens the efficiency of the long‐wave radiant heat emitted from the surface to the atmosphere, which leads to warming. We also find that there is cooling associated with an increase in the average building height, which is mostly induced by an increase in the efficiency of convective heat transfer. These results are important to understanding and design heat mitigation strategies. Key Points: Land surface temperature response to urban morphological changes is attributed to different physical changesAs the street aspect ratio increases, heat storage dominates the cooling effect during the daytime and the warming effect at nighttimeThe building area fraction affects the surface temperature mainly by changing the amount of long‐wave radiation emitted by the surface [ABSTRACT FROM AUTHOR]

Accurately mapping urban built-up areas is critical for monitoring urbanization and development. Previous studies have shown that Night light (NTL) data is effective in characterizing the extent of human activity. But its inherently low spatial resolution and saturation effect limit its application in the construction of urban built-up extraction. In this study, we developed a new index called VNRT (Vegetation, Nighttime Light, Road, and Temperature) to address these challenges and improve the accuracy of built-up area extraction. The VNRT index is the first to fuse the Normalized Difference Vegetation Index (NDVI), NPP-VIIRS Nighttime NTL data, road density data, and land surface temperature (LST) through factor multiplication. To verify the good performance of VNRT in extracting built-up areas, the built-up area ranges of four national central cities in China (Chengdu, Wuhan, Xi'an, and Zhengzhou) in 2019 are extracted by the local optimum thresholding method and compared with the actual validation points. The results show that the spatial distribution of VNRT is highly consistent with the actual built-up area. THE VNRT increases the variability between urban built-up areas and non-built-up areas, and can effectively distinguish some types of land cover that are easily ignored in previous urban indices, such as urban parks and water bodies. The VNRT index had the highest Accuracy (0.97), F1-score (0.94), Kappa coefficient (0.80), and overall accuracy (92%) compared to the two proposed urban indices. Therefore, the VNRT index could improve the identification of urban built-up areas and be an effective tool for long-term monitoring of regional-scale urbanization. [ABSTRACT FROM AUTHOR]