"A Bifurcated Land Surface Temperature Analysis Method for Exploring the Spatiotemporal Variation Characteristics of Urban Surfac"

"High temperatures directly threaten human health, with their intensity and duration exerting substantial impacts on mortality rates. Investigating land surface high-temperature dynamics is critical for understanding the complex interactions among urbanization, climate change, and human well-being. Given the insufficient research on the spatiotemporal variations of land surface high temperatures, this study proposes a Bifurcated Land Surface Temperature Analysis Method (Bifurcated-LSTAM). Taking Zhengzhou\u2014a rapidly urbanizing megacity in China\u2019s most populous province\u2014as a case study, based on long-term MODIS remote sensing data from 2003 to 2024, we conducted a comprehensive analysis of land surface high-temperature characteristics across diurnal, monthly, seasonal, and interannual scales using GIS spatial analysis and mathematical statistical methods, and we further discuss the temperature resilience response mechanism in high-density urban areas. The main results are as follows: (1) Both daytime and nighttime land surface temperatures exhibit significant warming trends at monthly, seasonal, and interannual scales. The most pronounced positive growth rate occurred in daytime during March, while daytime and nighttime monthly mean temperatures in October showed an overall negative trend; Spring recorded the strongest daytime warming rate, whereas autumn exhibited the weakest. These results indicate an advance in the timing of land surface high-temperature events. The annual mean daytime land surface temperature peaked at 26.39 \u2103 in 2019, and the annual mean nighttime temperature exceeded 10 \u2103 in both 2023 and 2024; (2) The standard deviational ellipses of the centers of gravity for the three-level warning high temperatures exhibit a distinct southeast-to-northwest strip orientation, which consistent with the urban spatial development pattern; (3) In terms of annual time proportion, yellow-level and orange-level warning high temperatures exhibited negative trends, while the red-level warning high temperature showed a positive trend. In terms of annual area proportion, all three warning levels displayed positive growth rates. These findings indicate that land surface high temperatures not only increased in extent but also tended to accumulate toward the highest-temperature categories. We present a comprehensive 22-year analysis of land surface temperature dynamics in a high-density city. The results provide valuable support for urban high-temperature disaster prevention and high-temperature risk assessment in the study region. The proposed method also offers a systematic framework for investigating spatiotemporal characteristics of land surface high temperatures in other urban areas."