摘要:以大中小城市协同发展为特征的城市群已成为我国城市化发展的主要形式，城市化和农业作为城市群地区最主要的土地利用活动，其气候效应是国际研究的热点。然而过去研究多关注大城市的热岛效应，对更为普遍的农业活动以及中小城市城市化的气候效应认识十分薄弱。基于MODIS地表温度数据，以自然林地为参照，提出了一种可逐像元估算土地利用地表热环境效应的新方法，进而对比分析了我国三大城市群地区（京津冀、长三角和珠三角）城市和农业用地地表热环境效应及其驱动因子差异。结果表明各城市群白天城市热岛效应明显，地级以上城市年平均热岛强度达3.2℃以上，但最强热岛均未发生在核心城市。夜晚热岛效应明显减弱，京津冀和长三角部分城市甚至出现冷岛效应。农业用地在白天亦表现出明显的增温效应，特别是在京津冀地区，而在夜晚除珠三角城市群外，降温效应明显，京津冀和长三角地区平均降温2.3℃和0.7℃。虽然城市用地平均增温强度大于农业用地，但农业用地因面积优势对区域温度变化起控制作用。白天城市和农业用地整体导致各城市群温度明显增加，京津冀增温最高（4.0℃），夜晚二者导致长三角和京津冀地区平均温度降低。研究还发现各城市群城市和农业用地地表热环境效应时空异质性极大，主要受植被、地表反照率、气候背景和人口密度控制。本文对制定缓解气候变化的土地利用策略具有重要的指导意义。



Abstract:Urban agglomerations, characterized by the synergetic development of large, medium, and small cities, are becoming the main form of urbanization in China. The climate effects of urbanization and agriculture, two most pervasive land use activities, have been the subject of active investigation. However, previous studies focused mainly on the urban heat island (UHI) effect of mega cities, while the climate effects of the more widespread agricultural activities and the urbanization in small/medium cities remain poorly understood. Using natural forests as reference, we proposed a new method to estimate the surface thermal environmental effects of human land use activities on a per-pixel basis based on MODIS land surface temperature (LST). We then compared the thermal effects of urban and agricultural lands and their drivers in three major urban agglomerations, China, namely Beijing-Tianjin-Hebei (BTHUA), Yangtze River Delta (YRDUA), and Pearl River Delta (PRDUA). Results showed that the daytime UHI effects were significant in all the urban agglomerations, with annual mean intensity larger than 3.2 ℃ for all the cities above prefecture-level, but the strongest did not occur in the core cities. The UHI effects reduced substantially at night, and even turned to be cold islands in some cities of the BTHUA and YRDUA. The agricultural lands also warmed the LST substantially during the daytime, especially in the BTHUA. Whereas they cooled the LST obviously at night for the BTHUA and YRDUA, with annual mean intensity of 2.3 ℃ and 0.7 ℃, respectively. Although the urban lands had greater warming potentials, the agricultural lands dominated the regional temperature changes due to their larger area share. The urban and agricultural lands together warmed the daytime LST in all urban agglomerations, with the greatest LST increase in the BTHUA (4.0 ℃), and cooled the LST at night for the BTHUA and YRDUA. Also, this study indicated that the surface thermal environmental effects of urban and agricultural lands varied greatly with the space and time. They were mainly controlled by vegetation activities, surface albedo, background climate, and population density. Our results provide important insights for formulating local land use strategies to mitigate climate change.





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