ABSTRACT To assess micro-scale population dynamics effectively, demographic variables should be available over temporally consistent small area units. However, fine-resolution census boundaries often change between survey years. This research advances areal interpolation methods with dasymetric refinement to create accurate consistent population estimates in 1990 and 2000 (source zones) within tract boundaries of the 2010 census (target zones) for five demographically distinct counties in the US. Three levels of dasymetric refinement of source and target zones are evaluated. First, residential parcels are used as a binary ancillary variable prior to regular areal interpolation methods. Second, Expectation Maximization (EM) and its data-extended version leverage housing types of residential parcels as a related ancillary variable. Finally, a third refinement strategy to mitigate the overestimation effect of large residential parcels in rural areas uses road buffers and developed land cover classes. Results suggest the effectiveness of all three levels of dasymetric refinement in reducing estimation errors. They provide a first insight into the potential accuracy improvement achievable in varying geographic and demographic settings but also through the combination of different refinement strategies in parts of a study area. Such improved consistent population estimates are the basis for advanced spatio-temporal demographic research.

中文翻译：

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通过 dasymetric 细化增强区域插值框架，以在普查中创建一致的人口估计

摘要 为了有效地评估微观人口动态，人口变量应该在时间一致的小区域单位上可用。然而，精细分辨率的人口普查边界经常在调查年份之间发生变化。这项研究推进了区域插值方法与 dasymetric 细化，以在 2010 年人口普查（目标区域）的区域边界内为美国五个人口统计不同的县创建准确一致的 1990 年和 2000 年（源区域）人口估计值。评估了源和目标区域的三个级别的 dasymetric 细化。首先，在常规面积插值方法之前，住宅地块被用作二进制辅助变量。其次，期望最大化 (EM) 及其数据扩展版本利用住宅地块的住房类型作为相关的辅助变量。最后，减轻农村地区大型住宅地块高估影响的第三个改进策略使用道路缓冲区和发达的土地覆盖等级。结果表明所有三个级别的 dasymetric 细化在减少估计误差方面的有效性。它们提供了对在不同地理和人口背景下可实现的潜在准确度提高的初步见解，也通过在研究区域的某些部分结合不同的细化策略。这种改进的一致人口估计是高级时空人口研究的基础。结果表明所有三个级别的 dasymetric 细化在减少估计误差方面的有效性。它们提供了对在不同地理和人口背景下可实现的潜在准确度提高的初步见解，也通过在研究区域的某些部分结合不同的细化策略。这种改进的一致人口估计是高级时空人口研究的基础。结果表明所有三个级别的 dasymetric 细化在减少估计误差方面的有效性。它们提供了对在不同地理和人口背景下可实现的潜在准确度提高的初步见解，也通过在研究区域的某些部分结合不同的细化策略。这种改进的一致人口估计是高级时空人口研究的基础。