Global spatially-distributed sectoral GDP map for disaster risk analysis

Abstract. Global risk assessments of economic losses by natural disasters while considering various land uses is essential. However, sector-specific, high-resolution pixel-level economic data are not yet available globally to assess exposure to local disasters such as floods. In this study, we employed new land-use data to construct global, spatially distributed map of sector-specific gross domestic product (GDP). We developed three global GDP maps in 2010, 2015, and 2020 for service, industry, and agriculture sector, with 30 arcsec resolution. Firstly, we found that the spatial relationship between the distribution of industrial GDP and urban areas, where the service GDP is highly concentrated, varies across countries. For example, in the United States, industrial GDP is widely dispersed regardless of urban areas, whereas in India, industrial GDP is concentrated in proximity to urban areas. Secondly, we evaluated the GDP map by subnational regional statistics of Thailand, where validation data are accessible. Traditional GDP maps relying solely on population distribution exhibited 63.0 % relative error of the sectoral GDP in each subnational region to regional statistical data, which the new sector-specific GDP map reduced to 26.2 %. Subsequently, we assessed the map in conjunction with sector-level business interruption (BI) losses resulting from river flooding. Our estimation of sector-level losses revealed that the sectoral ratio to the total loss varied significantly depending on the spatial distribution of flood hazards. The estimated total loss became closer to the reported value when the new GDP map was used, while sectoral ratios of losses still had some differences from the reported ratios suggesting the need for further improving the procedures of loss-estimation models. These global sectoral GDP maps (SectGDP30) are available at https://doi.org/10.5281/zenodo.13991673 (Shoji et al., 2024).