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选择日本埼玉县熊谷市为研究区,应用ASTER热红外遥感图像,采用PCACA模型以及理论定位算法,对城市地表热通量的相关参数进行反演,进而分析城市下垫面不同土地覆盖类型对地表热通量以及能量平衡的影响。结果表明,PCACA模型应用于城市区域地表通量估算是可行的。这种算法可以大大减少在下垫面结构复杂的城市区域进行地表热通量估算时所需的参数,并有效降低研究结果的不确定性。研究发现,城乡不同下垫面地表覆盖类型对地表热通量的影响差异显著。不同地表下垫面类型的波文比由大到小顺序依次为:工业用地>住宅用地>交通用地>公共设施用地>旱田>公共绿地>水域。在相同的外部气象条件下,与城市周边的植被覆盖区相比,城市人工建筑用地具有较高的显热通量,较低的潜热通量,以及较高的波文比。由于城市地表显热通量和波文比明显高于周边植被覆盖地表,导致城市地表向低层大气供热的增加,这是城市热岛效应形成的重要机制之一。
In the study, Kumagai, Saitama, Japan, was selected as the study area. The ASTER thermal infrared remote sensing image was used. The PCACA model and the theoretical localization algorithm were used to invert the relevant parameters of urban surface heat flux. Then the effects of different land cover types on urban surface Heat flux and energy balance. The results show that it is feasible to apply PCACA model to urban area surface flux estimation. This algorithm can greatly reduce the parameters needed for surface heat flux estimation in the urban area with complex underlying surface structure and effectively reduce the uncertainty of the research results. The study found that the impact of land cover types on surface heat flux varies significantly between urban and rural areas. The order of the wave ratios of different underlying surface types is descending order: industrial land> residential land> transportation land> public facilities land> dry land> public green land> water area. Under the same external weather conditions, urban artificial land for construction has higher sensible heat flux, lower latent heat flux and higher Bowen ratio than the vegetation cover around the city. As the surface heat flux and the Bowen ratio of the urban area are significantly higher than those of the surrounding vegetation, the urban surface heat supply to the lower atmosphere increases, which is one of the important mechanisms for the formation of urban heat island effect.