Using Landsat TM imagery, the author investigated urban surface temperature and its relationship with

such underlying surface parameters as NDVI, SAVI, NDBI, NDMI, Tasseled Cap Brightness (TCB), Greenness (TCG) and

Wetness (TCW), total shortwave albedo, and visible and near-IR broadband albedos in Jinan City, Shandong province.

The results show that the mean land surface temperature (Ts) in the built-up areas is 11.04℃, higher than that in

the suburban areas. Simple linear models between landcover parameters and Ts derived from Landsat TM thermal image

were built by using robust LTS regression and classic least-squares regression. Ts is negatively correlated with

vegetation indices (NDVI, SAVI and TCG), wetness indices (NDMI and TCW) and near-IR broadband albedo and

positively correlated with brightness indices (NDBI and TCB) and visible broadband albedo at the significant level

of α=0.05. However, simple linear relationship between Ts and total shortwave albedo does not exist. Most of the

regression models have high fitness score, except only for the two models associated with TCW and TCB. It is

also shown that the linear regression model between NDMI and Ts is most robust, while the regression equations

associated with visible and near-IR broadband albedo, TCW and TCB are not robust.