Spatial and temporal monitoring of land surface temperature trends using Remote Sensing Data

Land surface temperature, as a determining factor in climate change, is a key parameter for controlling and evaluating the physical, chemical, and biological processes of the Earth's surface and a critical factor for studying climate change in different regions. Further, natural and human factors, which promote significant impacts on Earth's energy relations, have been created notable changes in this index. Under these conditions, monitoring changes in Earth'ssurface temperature can play crucial roles in the management of natural resources. Further, several strategies have been reported to display changes in surface temperature in every region. In the meantime, the use of satellite imagery is known as the best method. Hence, resulting surface skin temperature data from physical models were employed to the monitoring of monthly and seasonal temporal and spatial changes in temperature over a period of ۲۰ years in the present study. According to the results, the coldest (areas adjacent to the Alborz and Zagros mountains) and the warmest (central plateau and southern regions of Iran) regions were identified and presented. Also, in the last two decades, the coldest and warmest seasons in Iran were identified for winter ۲۰۰۸ and summer ۲۰۱۸, respectively. In general, an increasing trend for temperature, especially for summer and winter seasons, is forecast in Iran

Keywords:

Iran , Noah Model , Satellite , Skin temperature