The spatial distribution of land cover information and its changes is very valuable for any planning, management and monitoring at local as well as regional scale. In this paper, multi-temporal Landsat TM/ OLI data were used to classify the land cover of the Nakhon Nayok province in Thailand over the period 2004-2015. The supervised classification maximum likelihood method was implemented to assign probability to land the cover classes considered. The random sampling point method was used for field survey and accuracy assessment. The overall accuracy and kappa coefficient in 2015 were found to be 72% and 0.6626 respectively. The results also indicated that important changes concerned mainly urban (308.46 %), water (-50.46), and agricultural (-12.14) areas, and least changes forest areas (3.17). These results also highlighted that over the last 10 years, urban areas have been characterized by the highest expansion, mainly from the conversion of agricultural land.