 Analysis of Land Surface Temperature (LST) from ground weather stations in Iraq for various terrains.  Analysis of the maximum, minimum, and mean LST as long-term series from remote sensing output data (2000 to 2020).  Statistical Analysis (RMSE, NSE, R 2 , and Parson Correlation Coefficient) have been used to evaluate Tmin, Tmax, and Tmean between ground weather stations and MOD11C3 products. Land Surface Temperature (LST) is a critical parameter for water resources and hydrology investigation. Weather ground stations provide a continuous dataset on the LST. However, some stations rely on discrete events data, which shows limited capabilities to monitor diurnal and annual changes in LST. Remote Sensing technology provided much valid information by using Moderate Resolution Imaging Spectroradiometer (MODIS) to cover LST variations in Iraq. This study aims to analyze LST variation based on MOD11C3 Data with weather ground measurements stations for the different topography periods between 2000-2020. Different statistical parameters were used to validate LST results, including RSME; NSE; R 2 , and Parson Correlation. The results indicate agreement between MODIS and ground measurement stations during the winter season. The values ranged: RSME (close to zero); NSE (0 to 1); R 2 (between 0.5 and 1), and Parson Correlation (between 0.51 to 1).In spring, the values ranged: R 2 (between 0.5 and 1) and Parson Correlation (between 0.51 to 1). As the temperature rises during seasonal changes, the congruence in the four statistical indicators begins to decline dramatically. However, Baghdad, Basra, and Mosul stations still appear in good agreement, which is the validity of the data issued by MOD11C3. The finding presented in this research shows that the results of the LST by MOD11C3 are in good agreement and acceptable despite in various topographies of the ground stations.