Maantay Juliana, Maroko Andrew
Corresponding Author, Associate Professor, Urban Environmental Geography, Director of GISc Program and Urban GISc Lab, Department of Environmental, Geographic, and Geological Sciences, Lehman College, City University of New York, 250 Bedford Park Blvd. West, Bronx, NY 10468, (718) 960-8574 (tel), (718) 960-8584,
Appl Geogr. 2009 Jan 1;29(1):111-124. doi: 10.1016/j.apgeog.2008.08.002.
This paper demonstrates the importance of disaggregating population data aggregated by census tracts or other units, for more realistic population distribution/location. A newly-developed mapping method, the Cadastral-based Expert Dasymetric System (CEDS), calculates population in hyper-heterogeneous urban areas better than traditional mapping techniques. A case study estimating population potentially impacted by flood hazard in New York City compares the impacted population determined by CEDS with that derived by centroid-containment method and filtered areal weighting interpolation. Compared to CEDS, 37 percent and 72 percent fewer people are estimated to be at risk from floods city-wide, using conventional areal weighting of census data, and centroid-containment selection, respectively. Undercounting of impacted population could have serious implications for emergency management and disaster planning. Ethnic/racial populations are also spatially disaggregated to determine any environmental justice impacts with flood risk. Minorities are disproportionately undercounted using traditional methods. Underestimating more vulnerable sub-populations impairs preparedness and relief efforts.
本文论证了对按普查区或其他单位汇总的人口数据进行分解的重要性，以便获得更现实的人口分布/位置。一种新开发的制图方法，即基于地籍的专家赋值法系统（CEDS），在超异质城市地区计算人口方面比传统制图技术表现更佳。一项估算纽约市可能受洪水灾害影响人口的案例研究，将CEDS确定的受影响人口与质心包容法和过滤面积加权插值法得出的受影响人口进行了比较。与CEDS相比，使用传统的普查数据面积加权法和质心包容法选择，估计全市面临洪水风险的人数分别减少了37%和72%。受影响人口统计不足可能会对应急管理和灾害规划产生严重影响。族裔/种族人口也按空间进行分解，以确定洪水风险对环境正义的任何影响。使用传统方法对少数群体的统计严重不足。低估更脆弱的亚群体人数会损害备灾和救灾工作。
