植被指数与地表温度定量关系遥感分析——以北京市TM数据为例

A Quantitative Analysis of the Relationship Between Vegetation Indices and Land Surface Temperature Based on Remote Sensing:a Case Study of TM Data for Beijing

以北京市为研究区,在对Landsat-5 TM数据大气校正基础上,利用TM单窗算法定量反演地表温度,并估算了5种植被参数:归一化差值植被指数(NDVI)、比值植被指数(RVI)、绿度植被指数(GVI)、土壤调节植被指数(MSAVI)和植被覆盖度(fg)。结合地表温度(LST)空间分布,对比分析5种植被参数与地表温度的相关程度。分析结果显示,相对于上述4种植被指数f,g与地表温度有更好的负相关性,对地表温度空间分布的指示能力更佳。利用fg与地表温度关系定量分析了植被覆盖程度对热岛效应的影响,发现北京市区平均地表温度比近郊区和远郊区分别高1.6 K和5.3 K。

Through correcting the Landsat -5 TM image of atmospheric effects and employing the calculation method of mono -window algorithm ,the LST in Beijing was calculated by inversion. On such a basis, five vegetation parameters were computed respectively, i. e. , Normalized Difference Vegetation Index （NDVI） , Ratio Vegetation Index （ RVI ）, Greenness Vegetation Index （ GVI）, Modified Soil - Adjusted Vegetation Index （MSAVI） and vegetation fraction （fs） Combined with the spatial distribution of LST in Beijing,this paper compared and analyzed the relevance between LST and the five vegetation parameters. Quantitative analysis of vegetation effect on the Urban Heat Island （UHI） was also carried out. The results show that, of the five parameters of vegetation,fg has the strongest negative correlation with LST. The average urban LST is 1.6 K and 5.3 K higher than that of the suburban and outer suburban respectively.