Long Time-Series Urban Heat Island Monitoring and Driving Factors Analysis Using Remote Sensing and Geodetector

Abstract

Urban heat island (UHI) effect decribes significant change due to rapid urbanization development. This study focused on the long time series analysis of UHI during the period 2000-2018, and analyzed the impact of land cover type and landscape metric factors on surface temperature. The results revealed that the UHI had a continuously decreasing trend in 2005–2010, and an increasing trend in 2000–2005 and 2010–2018. Cropland, built-up land, patch density (PD), Shannon Diversity Index (SHDI), and Landscape Shape Index (LSI) had a positive relationship with UHI, whereas forestland, open water, and CONTAG had a negative correlation with the UHI effect. The Geodetector analysis further revealed that PD, SHDI, and LSI had the greatest influences on LST as the three factors had the largest q values (0.287, 0.286, and 0.278). Forestland, cropland, and built-up land had greater impacts on the UHI than other land cover type factors. The explanatory power reached a maximum value of 0.408 when built-up land and cropland variables interacted. The findings of this study provide new understandings of the relationship between urban landscape and UHI, as well as important insights for urban planners to mitigate the UHI effect for the sustainable development of future urban agglomeration.