昆明中心城区地表温度反演及与土地覆盖关系分析

结合MODIS大气水汽3通道平均反演法与地表温度劈窗反演法，用Landsat 8反演了昆明中心城区的地表温度；应用面向对象法分尺度提取出城市土地覆盖类型，从可规划控制角度出发，选择各类土地覆盖的多种特征，对不同土地覆盖的特征与地表温度之间建立逐步回归模型。结果表明：昆明中心城区的地表温度呈现高温区与低温区两端分布特点，绿地分布不合理、道路和其他不渗水面比例过大是昆明城市高温区多的主要原因；回归模型显示，植被覆盖率、植被覆盖的外形复杂度、水域面积、河流长度、其他不渗水面内的植被绿化率与地表温度呈负相关，除道路之外的不渗水面的斑块面积和周长则与地表温度呈正相关；各类型土地覆盖的部分斑块特征与地表温度之间存在弱关联。进一步明确这些关系将有助于城市热环境调控、城市规划建设研究。

The Retrieval of Land Surface Temperature of Kunming Urban Area and its Relationships with Landscape Compositions

Taking the average water content of atmosphere derived from MODIS 3 bands as a parameter, the split window algorithm was employed on Landsat 8 to retrieve the land surface temperature (LST) of the central urban area of Kunming City. Then, the landscape compositions were identified by objected based hierarchical classification. After selecting controllable features of landscape composition, stepwise regression fitting was applied to analyze the relationship between LST and these features. The research showed the central parts of Kunming tend to have either high LST or low LST, and the major reason for numerous urban heat islands of Kunming is due to the uneven distribution of vegetation coverage and the high percentage of impervious surface and roads. Regression models indicated that the coverage percentage of vegetation, the shape index of vegetation patches, the size of pool, the length of river and the green rate in impervious surface have negative correlations with LST, while the size and perimeter of impervious surface have positive correlations with LST. It was concluded that there are some weak correlations between LST and some features of landscape compositions. Therefore, further research will be meaningful for the control of city thermal environment and the city planning.