Proper information on forest cover change and its spatio-temporal characteristics are essential for natural resource management and sustainable development. It is one of the major factor that affect the ecosystem and the services it provides. In this study, we used remote sensing techniques and a geographical information system to extract the forest cover categories based on the Object- based Image Analysis (OBIA) techniques from Landsat TM/ETM/OLI satellite in the Chure and Terai region from 1994-2018. In addition, ecosystem service value coefficient per unit area contributed by forest cover was taken from the previous studies and adjusted by taking accounts of yearly inflation or buying power to bring about the proper estimation of the ESV in terms of money impacting forest cover area. In 1994(40.02%), forest covered the highest area and found decreased quite faster till 2004(28.87%), and afterwards a gradual decrease arriving to 2018(26.52%). The highest ESV in 1994 was found to be 78.7 billion and lowest in 2018 was found to be 43.2 billion in current fiscal year. The spatial distribution of the Ecosystem Service Value is shown by the map where immediate action can be taken. The findings of this study could facilitate the strong forest conservation policy formulation further and development management intervention.