Quantitative Analysis of Land Surface Temperature-vegetation Indexes Relationship Based on Remote Sensing

Vegetation coverage has a significant influence on the land surface temperature (LST) distribution. In the field of urban heat islands (UHIs) based on remote sensing, vegetation indexes are widely used to estimate the LST-vegetation relationship. However, little evaluation work has been done on the comparison of the relationship between different vegetation indexes and LST. A Landsat Thematic Mapper image was corrected for atmospheric effects. Then, the LST was calculated by utilizing a mono-window algorithm. Next, five vegetation parameters were computed respectively: Normalized difference vegetation index (NDVI), Ratio Vegetation Index (RVI), Greenness Vegetation Index (GVI), Modified Soil-Adjusted Vegetation Index (MSAVI) and the vegetation fraction (fg). Combined with the spatial distribution of LST in Beijing, comparison and analysis were conducted to investigate the relationship between LST and five vegetation parameters. Quantitative analysis of vegetation effect on UHI was also made. Results demonstrate that among the five parameters of vegetation, fg has the strongest correlation with LST. The average urban LST is 6.41K and 10.06K higher than the suburban and outer suburban temperature, respectively. In the urban area, the low vegetation fraction is the important contributor of the high LST. ∗ Corresponding author: [email protected]