Soil moisture estimation is essential for optimal water and soil resource management. Surface soil moisture is an important variable in the natural water cycle, which plays an important role in the global equilibrium of water and energy due to its impact on hydrological, ecological and meteorological processes. Too little or very high soil moisture can be an indication of a disequilibrium in the water recharge and discharge cycle, which may be indicative of potential flooding or draught respectively. Soil moisture measurements are performed directly using in-situ methods and indirectly, using transfer functions or remote sensing. Since in-situ measurements are usually costly and time consuming in large areas, we can use methods such as remote sensing to estimate soil moisture at very large scales. In this work, ground temperature was calculated using Landsat-8 thermal infrared band for Oredo Local Government Area and was used to estimate the soil moisture of the study area using ArcGIS (Arc-map 10.2.2). Object base modeling was used in the classification of the study area into area of high, moderate and low moisture content for both the rainy and dry seasons respectively. This study is expected to serve as a database that can be built upon by relevant government agencies to enable them embark on proper town planning and flood management strategy within the local government area under investigation