Insang Yu (Korea, Republic of) 1; Huicheul Jung (Korea, Republic of) 1; Daeok Youn (Korea, Republic of) 2
1 - Korea Adaptation Center for Climate Change, Korea Environment Institute; 2 - Department of Earth Science Education, Chungbuk National University
According to fifth Assessment report of IPCC, Impacts from recent climate-related extremes, such as heat waves, droughts, floods, cyclones and wildfires, reveal significant vulnerability and exposure of some ecosystems and many human systems to current climate variability. Impacts of such climate-related extremes include damage to settlements, human mortality and consequences for mental health. In order to reduce climate change impacts, risky areas should be selected through risk assessment using risk, exposure, vulnerability and adaptive capacity indicators and adaptation measures should be established. Previously, the risk assessment was conducted at the administrative district level. Recently, however, a grid-level risk assessment has been required in order to establish regionalized measures for climate change adaptation.
One of the most important data for grid-based risk assessment, grid-based population density maps should be created by allocating administrative population density data to grids. In this study, grid-based population density maps of the Republic of Korea were developed by using ancillary datasets such as census data, land cover maps, roads, and so on. Population density estimate equation was developed through regression analysis between population density and ancillary datasets and regression equations were used to allocate population density to the 1km grid. The population density map is expected to be used for grid-based risk assessment for climate change adaptation, analysis and planning purposes including humanitarian response, disease mapping, and evacuation modelling.
This work is supported by Korea Environment Industry & Technology Institute (KEITI) through Climate Change R&D Program, funded by Korea Ministry of Environment (MOE) (2018001310004).