Detection of Surface Temperature Changes Using Satellite Images and Real Data and its Relationship with the Covered Vegetation in the Southern Part of the Lake Urmia

Today, the use of remote sensing methods for measuring land surface temperature has got more popular. Because remote sensing provides the opportunity to estimate the temperature in every region accurately. This study aimed to estimate land surface temperature using remote sensing in the south of Urmia Lake, compare them with observed data, and analyze the relationship between estimated land surface temperature and vegetation cover.

Changes in temperature of the surface of the earth were investigated from 2000 to 2017 as well as their relationship with changes in vegetation and land use in agricultural regions. Then, thermal bands of Landsat 7 and OLI were used for measuring land surface temperature and converting DN to radians and brightness temperature. Moreover, NDVI was used for calculating emissivity and determining land use based using an object-oriented method. Then, the relationship between vegetation and land surface temperature was investigated using regression analysis.

The results showed that the observed and estimated land surface temperature had increased from 2000 to 2017 due to the changes in land use and vegetation cover. According to the results of linear regression analysis, there is a significant relationship between estimated and observed land surface temperature (R2 = 0.72). Furthermore, there is a significant negative relationship between land surface temperature and vegetation cover.

The results showed that remote sensing methods provide accurate results in estimating the surface temperature. Understanding the surface temperature and its relationship with various land uses helps planners and experts to make managerial decisions to protect natural resources and agricultural lands.