Revealing the Driving Mechanisms of Land Surface Temperature Spatial Heterogeneity and Its Sensitive Regions in China Based on GeoDetector
Published in Remote Sensing, 2023
Abstract
Land surface temperature (LST) has a critical impact on the energy balance of land surface processes and ecosystem stability. Meanwhile, LST is controlled by multiple factors at the surface, resulting in heterogeneity of its spatial distribution. To understand the drivers of LST spatial heterogeneity and their contributions, the effects of air temperature, normalized difference vegetation index (NDVI), soil moisture, net surface radiation, precipitation, aerosol optical depth (AOD), evapotranspiration, water vapor, digital elevation model (DEM), climate type, and land cover type on LST spatial heterogeneity was analyzed in this study with GeoDetector. The results showed that the explanatory ability of air temperature to impact the spatial heterogeneity of LST was the largest in each year with a mean value of 0.74, followed by water vapor with a mean value of 0.7, and the driving effect of the factors on LST showed an increasing trend year by year. However, the land cover type did not have an effect on the spatial heterogeneity of LST for the univariate analysis in this study. In addition, the interaction analysis indicated that the spatial distribution of LST was jointly driven by all the driving factors. Among them, air temperature had the strongest interaction with other factors, with the strength of the effect in the range of 0.73–0.8. In terms of the highly sensitive area of LST for each driver, AOD has the largest driving area, accounting for 15.8% of the total area, followed by WV, TA, and ET at about 11%, and the remaining variables are less than 10%. During the study period, the area of the highly sensitive region of LST for each factor showed an overall decreasing trend, indicating that the influence of the driving factors on LST will be stronger and more concentrated. Generally, this study provides meaningful understanding of the spatial heterogeneity of LST since 2003 and provides a scientific reference for coping with climate change, analyzing surface environmental patterns, and protecting ecological environment.
Key words
land surface temperature; spatial heterogeneity; drivers; MODIS; GeoDetector
Recommended citation: Yanru, Yu; Shibo Fang; Wen Zhuo. Revealing the Driving Mechanisms of Land Surface Temperature Spatial Heterogeneity and Its Sensitive Regions in China Based on GeoDetector. Remote Sensing, 2023, 15(11), 2814. https://doi.org/10.3390/rs15112814