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[ABSTRACT]Indonesian region is lately experiencing extreme weather resulting in deviant climate change. It is occurred due to the massive amount of carbon dioxide produced on this planet. As the consequence, the ozone layer protecting the earth from solar radiation becomes vulnerable and damaged. The existence of the green plants classified as forest biodiversity is expected to reduce the large amount of carbon dioxide gas by transforming it into oxygen through photosynthesis. Forest biodiversity in Southeast Sulawesi is categorized into tropical forest, savannah and mangrove forest. Each type of forest has different amount of carbon stock. Nowadays, information in relation to carbon stocks and forest biodiversity are needed for the analysis of climate change. The main objective of this research is to analyze climate change according to carbon stocks and forest biodiversity in Southeast Sulawesi by applying hyper spectral data. In order to distinguish the forest types and to comprehend its carbon potentials, unsupervised classification method is applied and correlated with the biomass carbon. Furthermore, it is analyzed using NDVI formula to determine the extent and density of vegetation and carbon potential existing in an area. Further analysis is conducted by utilizing weather parameter of air pressure observation data, air temperature data, and weather satellite data to discover monthly average weather conditions semi-objectively. The results obtained, will enable this research to analyze climate change in order to provide early prevention efforts.