Modeling Biophysical Variables and Land Surface Temperature Using the GWR Model: Case Study-Tehran and Its Satellite Cities

The land-cover type plays a decisive role for the land surface temperature (LST). Since cities and their satellite cities are composed of varying covers, including vegetation, built-up areas, buildings, roads, and bare areas, the main purpose of this research is to examine the LST in Tehran and its satellite cities and the cover type that contributes to increased or decreased temperature. The study investigated the relationship between NDVI, SAVI, NDBI, and NDBaI indices, as four biophysical variables, and LST over a period of 15 years (2001-2015) by the geographically weighted regression (GWR) model using imagery of Landsat 7. The results showed that the relationship between LST and NDBI is stronger than the associations with other variables. In 2010, biophysical variables had the greatest effect on LST. Using the GWR model, the local R2map was drawn for the studied area, showing that the highest value for the coefficient of determination belonged to Islamshahr and Shahriar because of the homogeneity of the land cover in these cities.