ABSTRACT

Socioeconomic characteristics are commonly used as indicators of vulnerability and resilience to inform disaster risk planning and management. Vancouver is a coastal seaport city along the west coast of Canada and is exposed to risk from the impacts of flooding. Previous studies have assessed and modelled a city's resilience to environmental hazards based on socioeconomic status derived from census data, such as income status, family structure, and dwelling conditions. However, these data sources are aggregated into different census units of varying scale, such as Census Tracts (CT) and Dissemination Areas (DA). Spatial analysis of the same data using different aggregation units manifests in the Modifiable Areal Unit Problem (MAUP), where varying scale can produce different results and conclusions. This exploratory analysis of the MAUP demonstrates that social resilience to flooding hazards in Vancouver at the CT and DA census scales can have contradictory results depending on the census scale adopted. The effect of scale and the aggregation units at which spatial analysis occurs can have a significant impact on the conclusions imparted and decision making to identify priority areas. Since individual-level disaggregate data is unavailable, the analytical results based solely on aggregate data should be interpreted with caution.

摘要

社会经济特征通常用作脆弱性和复原力的指标，为灾害风险规划和管理提供信息。温哥华是加拿大西海岸的沿海港口城市，面临洪水影响的风险。先前的研究已经根据从人口普查数据得出的社会经济状况（例如收入状况、家庭结构和居住条件）评估和模拟了城市对环境危害的恢复能力。然而，这些数据源被汇总到不同规模的不同人口普查单位中，例如人口普查区域 (CT) 和传播区域 (DA)。使用不同聚合单位对相同数据进行空间分析体现在可修改面积单位问题 (MAUP) 中，其中不同的规模会产生不同的结果和结论。MAUP 的这种探索性分析表明，根据所采用的人口普查规模，在 CT 和 DA 人口普查范围内，温哥华对洪水灾害的社会复原力可能会产生相互矛盾的结果。发生空间分析的规模和聚合单位的影响可能对得出的结论和确定优先领域的决策产生重大影响。由于个人层面的分解数据不可用，因此应谨慎解释仅基于聚合数据的分析结果。发生空间分析的规模和聚合单位的影响可能对得出的结论和确定优先领域的决策产生重大影响。由于个人层面的分解数据不可用，因此应谨慎解释仅基于聚合数据的分析结果。发生空间分析的规模和聚合单位的影响可能对得出的结论和确定优先领域的决策产生重大影响。由于个人层面的分解数据不可用，因此应谨慎解释仅基于聚合数据的分析结果。