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Development of an Asset Value Map for Disaster Risk Assessment in China by Spatial Disaggregation Using Ancillary Remote Sensing Data

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  • Jidong Wu
  • Ying Li
  • Ning Li
  • Peijun Shi

Abstract

The extent of economic losses due to a natural hazard and disaster depends largely on the spatial distribution of asset values in relation to the hazard intensity distribution within the affected area. Given that statistical data on asset value are collected by administrative units in China, generating spatially explicit asset exposure maps remains a key challenge for rapid postdisaster economic loss assessment. The goal of this study is to introduce a top‐down (or downscaling) approach to disaggregate administrative‐unit level asset value to grid‐cell level. To do so, finding the highly correlated “surrogate” indicators is the key. A combination of three data sets—nighttime light grid, LandScan population grid, and road density grid, is used as ancillary asset density distribution information for spatializing the asset value. As a result, a high spatial resolution asset value map of China for 2015 is generated. The spatial data set contains aggregated economic value at risk at 30 arc‐second spatial resolution. Accuracy of the spatial disaggregation reflects redistribution errors introduced by the disaggregation process as well as errors from the original ancillary data sets. The overall accuracy of the results proves to be promising. The example of using the developed disaggregated asset value map in exposure assessment of watersheds demonstrates that the data set offers immense analytical flexibility for overlay analysis according to the hazard extent. This product will help current efforts to analyze spatial characteristics of exposure and to uncover the contributions of both physical and social drivers of natural hazard and disaster across space and time.

Suggested Citation

  • Jidong Wu & Ying Li & Ning Li & Peijun Shi, 2018. "Development of an Asset Value Map for Disaster Risk Assessment in China by Spatial Disaggregation Using Ancillary Remote Sensing Data," Risk Analysis, John Wiley & Sons, vol. 38(1), pages 17-30, January.
    • Handle: RePEc:wly:riskan:v:38:y:2018:i:1:p:17-30
    DOI: 10.1111/risa.12806
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    References listed on IDEAS

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    Cited by:

    1. Jian Ma & Anirudh Rao & Vitor Silva & Kai Liu & Ming Wang, 2021. "A township-level exposure model of residential buildings for mainland China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 389-423, August.
    2. Ruiling Sun & Ge Gao & Zaiwu Gong & Jie Wu, 2020. "A review of risk analysis methods for natural disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 100(2), pages 571-593, January.
    3. Peng Ye, 2022. "Remote Sensing Approaches for Meteorological Disaster Monitoring: Recent Achievements and New Challenges," IJERPH, MDPI, vol. 19(6), pages 1-28, March.
    4. Jidong Wu & Mengqi Ye & Xu Wang & Elco Koks, 2019. "Building Asset Value Mapping in Support of Flood Risk Assessments: A Case Study of Shanghai, China," Sustainability, MDPI, vol. 11(4), pages 1-19, February.
    5. Xin He & Jidong Wu & Cailin Wang & Mengqi Ye, 2018. "Historical Earthquakes and Their Socioeconomic Consequences in China: 1950–2017," IJERPH, MDPI, vol. 15(12), pages 1-15, December.
    6. Ruiling Sun & Zaiwu Gong & Weiwei Guo & Ashfaq Ahmad Shah & Jie Wu & Haiying Xu, 2022. "Flood disaster risk assessment of and countermeasures toward Yangtze River Delta by considering index interaction," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(1), pages 475-500, May.
    7. Wenhui Liu & Jidong Wu & Rumei Tang & Mengqi Ye & Jing Yang, 2020. "Daily Precipitation Threshold for Rainstorm and Flood Disaster in the Mainland of China: An Economic Loss Perspective," Sustainability, MDPI, vol. 12(1), pages 1-14, January.

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