Derivation of land surface temperature from Landsat Thematic Mapper (TM) sensor data and analyzing relation between land use changes and surface temperature

Abstract

Land surface temperature (LST) is one of the key parameters in the physics of land surface processes from local to global scales, and it is one of the indicators of environmental quality. Evaluation of the surface temperature distribution and its relation with existing land use types are very important to investigate the urban microclimate. Land use planning in the cities must be in accordance with sustainable development goals to make the urban environment without soil, water and air pollution. In the arid and semi-arid regions, understanding the role of land use changes in the formation of urban heat islands is necessary to provide urban planning to control or reduce surface temperature. Internal factors and environmental conditions of the Yazd city have important role in the formation of special thermal conditions in the Iran. In this paper, we used the Temperature Emissivity Separation (TES) algorithm for LST retrieving from TIRS data of the Landsat Thematic Mapper (TM). The Root Mean-Square Error (RMSE) and Coefficient of Determination (R2) were used for validation of retrieved LST values. Land use types of the Yazd city were identified and relations between land use types, land surface temperature and NDVI index were analyzed. The Kappa coefficient and overall accuracy were calculated for accuracy assessment of the land use classification. The results of this study showed that optical and thermal remote sensing methodologies can be used to research urban environmental parameters. Finally, it was found that special thermal conditions in Yazd city were formed by land use changes. Increasing the area of asphalt roads, residential, commercial and industrial types and decreasing the area of the parks, green spaces and fallow lands types of land uses in the Yazd city caused a rise in surface temperature during the 11-year period.