Point Building Data
收藏资源简介：
This contains the building damage data described in the manuscript 'A Bayesian Approach for Earthquake Impact Modelling' (available at: https://arxiv.org/abs/2412.15791).The code used to generate the R objects are contained in https://github.com/hamishwp/ODDRIN. It compiles data from several sources including:Global Data Lab: J. Smits and I. Permanyer. The Subnational Human Development Database. Scientific data, 6(1):1–15, 2019.Vs30: D. C. Heath, D. J. Wald, C. B. Worden, E. M. Thompson, and G. M. Smoczyk. A global hybrid VS 30 map with a topographic slope–based default and regional map insets. Earthquake Spectra, 36(3):1570–1584, 2020.Earthquake frequency: K. Johnson, M. Villani, K. Bayliss, C. Brooks, S. Chandrasekhar, T. Chartier, Y. Chen, J. Garcia-Pelaez, R. Gee, R. Styron, A. Rood, M. Simionato, and M. Pagani. Global Earthquake Model (GEM) seismic hazard map (version 2023.1 - June 2023). GEM https://doi.org/10.5281/zenodo.8409647, 2023.Income Inequality: F. Alvaredo, A. B. Atkinson, T. Piketty, and E. Saez. World Inequality Database, 2022. URL http://wid.world/data.Copernicus Building Damage Footprints: Copernicus Emergency Management Service. Copernicus emergency management service - mapping, 2012. URL https://emergency.copernicus.eu/mapping. The European Commission.UNITAR/UNOSAT Building Damage Footprints: UNITAR/UNOSAT. UNITAR’s Operational Satellite Applications Programme – UNOSAT, 2023. URL https://unosat.org/<br>products/.WorldPop Population: A. J. Tatem. WorldPop, open data for spatial demography. Scientific Data, 4(1):1–4, 2017. doi: 10.1038/sdata.2017.4.Bing Building Footprints: Microsoft. Global ML Building Footprints, 2022. URL https://github.com/microsoft/GlobalMLBuildingFootprints. Accessed:<br>2024-06-17.<br>Shakemap: D. J. Wald, B. C. Worden, V. Quitoriano, and K. L. Pankow. ShakeMap manual: Technical manual, user’s guide, and software guide. Technical Report 12-A1, United States Geological Survey, 2005.
本数据集收录了论文《A Bayesian Approach for Earthquake Impact Modelling》（可于https://arxiv.org/abs/2412.15791获取）中描述的建筑损毁数据。用于生成R对象的代码存储于https://github.com/hamishwp/ODDRIN。本数据集整合了多源数据，具体来源如下： 1. 全球数据实验室（Global Data Lab）：J. Smits与I. Permanyer. 《次国家人类发展数据库》. 科学数据，6(1):1–15，2019. 2. Vs30：D. C. Heath、D. J. Wald、C. B. Worden、E. M. Thompson与G. M. Smoczyk. 基于地形坡度默认值与区域地图插图的全球混合Vs30地图. 《地震谱》，36(3):1570–1584，2020. 3. 地震活动频次：K. Johnson、M. Villani、K. Bayliss、C. Brooks、S. Chandrasekhar、T. Chartier、Y. Chen、J. Garcia-Pelaez、R. Gee、R. Styron、A. Rood、M. Simionato与M. Pagani. 全球地震模型（GEM）地震危险性图（2023.1版——2023年6月）. GEM，https://doi.org/10.5281/zenodo.8409647，2023. 4. 收入不平等：F. Alvaredo、A. B. Atkinson、T. Piketty与E. Saez. 《世界不平等数据库》，2022. 网址：http://wid.world/data. 5. 哥白尼建筑损毁足迹（Copernicus Building Damage Footprints）：哥白尼紧急管理服务局. 哥白尼紧急管理服务——测绘业务，2012. 网址：https://emergency.copernicus.eu/mapping. 欧盟委员会. 6. 联合国训练研究所/联合国卫星项目办公室（UNITAR/UNOSAT）建筑损毁足迹：UNITAR/UNOSAT. 联合国训练研究所运营卫星应用项目——UNOSAT，2023. 网址：https://unosat.org/products/. 7. 世界人口（WorldPop）人口数据：A. J. Tatem. 《WorldPop：空间人口学开放数据》. 科学数据，4(1):1–4，2017. DOI: 10.1038/sdata.2017.4. 8. 必应建筑足迹（Bing Building Footprints）：微软（Microsoft）. 全球机器学习建筑足迹数据集，2022. 网址：https://github.com/microsoft/GlobalMLBuildingFootprints. 访问日期：2024-06-17. 9. 震动图（Shakemap）：D. J. Wald、B. C. Worden、V. Quitoriano与K. L. Pankow. 《ShakeMap手册：技术手册、用户指南与软件指南》. 美国地质调查局技术报告12-A1，2005.
