Benefits of global earth observation missions for disaggregation of exposure data and earthquake loss modeling: evidence from Santiago de Chile
Benefits of global earth observation missions for disaggregation of exposure data and earthquake loss modeling: evidence from Santiago de Chile
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DOI：
10.1007/s11069-022-05672-6
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发表时间：
2022-11
期刊：
影响因子：
3.7
通讯作者：
C. Geiss;Peter Priesmeier;Patrick Aravena Pelizari;Angélica Rocio Soto Calderon;E. Schoepfer;T. Riedlinger;Mabé Villar Vega;Hernán Santa María;Juan Camilo Gomez- Zapata;M. Pittore;E. So;Alexander Fekete;H. Taubenböck
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作者：
C. Geiss;Peter Priesmeier;Patrick Aravena Pelizari;Angélica Rocio Soto Calderon;E. Schoepfer;T. Riedlinger;Mabé Villar Vega;Hernán Santa María;Juan Camilo Gomez- Zapata;M. Pittore;E. So;Alexander Fekete;H. Taubenböck
暴露是风险模型的一个重要组成部分，描述了受危害危害和易受损害的要素。相关的脆弱性是指在一定灾害强度下遭受损害（可转化为损失）的可能性。通常情况下，汇编暴露信息是风险评估程序中成本最高的部分（就时间和劳动力而言）。现有模型通常以聚合方式描述暴露，例如，依靠特定行政实体的统计/普查数据。如今，地球观测技术允许收集大地理区域的空间连续信息，同时能够实现高几何和时间分辨率。因此，我们利用地球观测任务TanDEM-X和哨兵-2的测量，在全球范围内收集数据，以表征建筑环境的构成形态属性，即建筑密度和高度。随后，我们使用这些信息来约束现有的暴露数据的空间分解方法。因此，我们建立了离散化方法。结果是为智利的圣地亚哥，这是容易发生地震等自然灾害的城市。我们目前的损失估计，由于地震地面震动和相应的灵敏度作为模型中使用的曝光数据的分辨率属性的函数。实验结果强调了部署现代地球观测技术的好处，用于精确的暴露映射和相关的地震损失估计，具有更高的准确性。
Exposure is an essential component of risk models and describes elements that are endangered by a hazard and susceptible to damage. The associated vulnerability characterizes the likelihood of experiencing damage (which can translate into losses) at a certain level of hazard intensity. Frequently, the compilation of exposure information is the costliest component (in terms of time and labor) of risk assessment procedures. Existing models often describe exposure in an aggregated manner, e.g., by relying on statistical/census data for given administrative entities. Nowadays, earth observation techniques allow the collection of spatially continuous information for large geographic areas while enabling a high geometric and temporal resolution. Consequently, we exploit measurements from the earth observation missions TanDEM-X and Sentinel-2, which collect data on a global scale, to characterize the built environment in terms of constituting morphologic properties, namely built-up density and height. Subsequently, we use this information to constrain existing exposure data in a spatial disaggregation approach. Thereby, we establish dasymetric methods for disaggregation. The results are presented for the city of Santiago de Chile, which is prone to natural hazards such as earthquakes. We present loss estimations due to seismic ground shaking and corresponding sensitivity as a function of the resolution properties of the exposure data used in the model. The experimental results underline the benefits of deploying modern earth observation technologies for refined exposure mapping and related earthquake loss estimation with enhanced accuracy properties.