Monitoring of Land Surface Temperature from Landsat Imagery: A Case Study of Al-Anbar Governorate in Iraq

Land surface temperature (LST) estimation is a crucial topic for many applications related to climate, land cover, and hydrology. In this research, LST monitoring of the main part Al-Anbar Governorate in Iraq presented using Landsat imagery from five years (2005, 2010, 2015, 2016 2020). Images 2005 2010 were captured by 5 (TM) others 8 (OLI/TIRS). The Single Channel Algorithm was applied retrieve images. Moreover, use/land cover (LULC) maps developed maximum likelihood classifier. difference normalized vegetation index (NDVI) values over period observed due changes LULC. Finally, regression analysis conducted model relationship between NDVI. results showed that highest study area recorded (min = 21.1°C, max 53.2°C mean 40.8°C). This attributed fact people displaced had left their agricultural fields. Therefore, thousands hectares which previously been green became desertified. conclusion supported comparing areas registered throughout years. polynomial NDVI revealed better coefficient determination (R2) than linear with an average R2 0.423.