earticle

영어

In 2021, South Korea enacted and promulgated the Framework Act on Carbon Neutrality and Green Growth for Coping with Climate Crisis, becoming the 14th country in the world to legislate a carbon neutrality vision and implementation framework. The country has also declared to the international community its goal to reduce greenhouse gas emissions by 40% by 2030. Achieving carbon neutrality and the national greenhouse gas reduction targets requires not only reducing emissions but also developing accurate estimation and forecasting methods for carbon sinks and promoting efforts to enhance them. This study aims to propose a methodology for forecasting carbon sinks that considers land-use changes, contributing to the establishment of Carbon Neutrality and Green Growth Basic Plans. To identify land-use changes, we developed a time-series land-use mapping method using high-resolution satellite imagery from Sentinel-2 integrated with machine learning techniques on the Google Earth Engine platform. To predict land-use changes, the constructed land-use maps along with topography and socio-economic variables were used as input data, while the ANN-CA model was employed as the prediction model to forecast land-use changes up to 2029. The results show that the developed land-use mapping and change prediction methodology can be effectively applied in establishing national and regional Carbon Neutrality and Green Growth Basic Plans.