The urban heat island(UHI) is an environmental problem of wide concern because it poses a threat to both the human living environment and the sustainable development of cities. Knowledge of the spatiotemporal characte...The urban heat island(UHI) is an environmental problem of wide concern because it poses a threat to both the human living environment and the sustainable development of cities. Knowledge of the spatiotemporal characteristics and the driving factors of UHI is essential for mitigating their impact. However, current understanding of the UHI in the Guangdong–Hong Kong–Macao Greater Bay Area(GBA) is inadequate. Combined with data(e.g., land surface temperature and land use.) acquired from the Google Earth Engine and other sources for the period 2001–2020, this study examined the diurnal and seasonal variabilities, spatial heterogeneities, temporal trends, and drivers of surface UHI intensity(SUHII) in the GBA. The SUHII was calculated based on the urban–rural dichotomy, which has been proven an effective method. The average SUHII was generally 0–2°C, and the SUHII in daytime was generally greater than that at night. The maximum(minimum) SUHII was found in summer(winter);similarly, the largest(smallest) diurnal difference in SUHII was during summer(winter). Generally, the Mann–Kendall trend test and the Sen's slope estimator revealed a statistically insignificant upward trend in SUHII on all time scales. The influence of driving factors on SUHII was examined using the Geo-Detector model. It was found that the number of continuous impervious pixels had the greatest impact, and that the urban–rural difference in the enhanced vegetation index had the smallest impact, suggesting that anthropogenic heat emissions and urban size are the main influencing factors. Thus, controlling urban expansion and reducing anthropogenic heat generation are effective approaches for alleviating surface UHI.展开更多
基金National Natural Science Foundation of China,No.42071123,No.42201104。
文摘The urban heat island(UHI) is an environmental problem of wide concern because it poses a threat to both the human living environment and the sustainable development of cities. Knowledge of the spatiotemporal characteristics and the driving factors of UHI is essential for mitigating their impact. However, current understanding of the UHI in the Guangdong–Hong Kong–Macao Greater Bay Area(GBA) is inadequate. Combined with data(e.g., land surface temperature and land use.) acquired from the Google Earth Engine and other sources for the period 2001–2020, this study examined the diurnal and seasonal variabilities, spatial heterogeneities, temporal trends, and drivers of surface UHI intensity(SUHII) in the GBA. The SUHII was calculated based on the urban–rural dichotomy, which has been proven an effective method. The average SUHII was generally 0–2°C, and the SUHII in daytime was generally greater than that at night. The maximum(minimum) SUHII was found in summer(winter);similarly, the largest(smallest) diurnal difference in SUHII was during summer(winter). Generally, the Mann–Kendall trend test and the Sen's slope estimator revealed a statistically insignificant upward trend in SUHII on all time scales. The influence of driving factors on SUHII was examined using the Geo-Detector model. It was found that the number of continuous impervious pixels had the greatest impact, and that the urban–rural difference in the enhanced vegetation index had the smallest impact, suggesting that anthropogenic heat emissions and urban size are the main influencing factors. Thus, controlling urban expansion and reducing anthropogenic heat generation are effective approaches for alleviating surface UHI.
