Abstract

The continuous economic and ecological construction in the Yangtze River Delta (YRD) and Pearl River Delta (PRD) has caused frequent temporal and spatial changes in local forests, thus affecting the regional climate. Yet few studies have addressed the temperature feedback through biophysical mechanisms due to forest change in two urban agglomerations of China. We compared MODIS and Landsat-based land cover data to detect a more accurate forest cover change. We then used the moving window strategy and spatiotemporal pattern change analysis method to quantify and compare the actual impact of forest cover change on temperature and the differences in driving factors (e.g., evapotranspiration (ET), albedo, and precipitation) from 2010 to 2020. The results showed that Landsat-based land cover data performed well. The conversion from forest to cropland was dominated in YRD and PRD, followed by the conversion of cropland to forest, with a small proportion of forest converting to impervious surface. The afforested areas in the two regions showed a diurnal cooling effect (-0.18 ± 0.07 °C and -0.10 ± 0.13 °C, respectively), which was greater than the air temperature. Forest converting to impervious surfaces led to stronger warming (0.39 ± 0.37 °C in YRD) than that of cropland (0.05 ± 0.03 °C in YRD and 0.07 ± 0.06 °C in PRD). The daytime LST variations can be explained by ET and inconsistent albedo effects. Seasonally, the cooling effects induced by afforestation predominated during the growing season (spring and summer), accompanied by the relatively high ET. This study shows that rational afforestation and control of deforestation are helpful to achieve sustainable forest management in urban agglomerations and to regulate climate warming.

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