Abstract

Rapid urbanization has led to changes in the urban land surface thermal environment. However, there are still much unknown about the urban land surface thermal conditions in permafrost regions. Permafrost is a unique geological environment, changes in the urban land surface thermal environment may trigger geological disasters caused by permafrost degradation. This study utilized remote sensing data and geographic detectors to identify the dynamic changes in land surface temperature (LST) and land use/land cover (LU/LC) in Yakutsk, as well as the potential factors contributing to LST variations. Between 1992 and 2020, the built-up area in Yakutsk increased by 36%, and the annual average LST in Yakutsk has risen by 6.67 °C, accompanied by an expansion of high-temperature areas. Despite ongoing greening efforts, rapid urbanization poses a threat to these green spaces. Changes in the normalized difference built-up index (NDBI) and land use transfer (LDT) were identified as the primary drivers of urban LST changes. By integrating geographic detector technology and artificial neural network models, we optimized the selection of input factors in the prediction model and used it to explore the future changes in LST in Yakutsk. The average LST in Yakutsk is expected to reach 23.4 °C and 25.1 °C in 2030 and 2040, respectively, with a further increase in high-temperature areas. This study provides a reference for ecological, hydrological, and geological assessments of cities in permafrost regions.

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