采用G2SFCA方法选择数据聚集方法对步行可达性结果的影响

Łukasz Lechowski
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引用次数: 0

摘要

在基于市场区域的空间可达性研究中,如浮动集水区(FCA)家庭方法,确定需求和供应方面的权重分配点至关重要。考虑到分类数据并不总是可行的,本文的目的是研究哪种确定点的方法,最大限度地减少步行可达性估计中的偏差。该研究使用了戴介绍的G2SFCA方法,该方法已多次用于建模步行可达性。结果清楚地表明,与基于集中加权平均值的方法相比,基于将数据分解为建筑物的区域单元的点定位方法在统计区或地籍区的规模上表现更好。他们还表明,欧几里得中心加权中值等位置测量可以改善在结算网络模式方面异质的单元中的分析结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of choice of data aggregation method to a point on walking accessibility results using the G2SFCA method
In spatial accessibility studies based on market areas, such as floating catchment area (FCA) family methods, it is crucial to identify the point to which weights are assigned, both on the demand and supply side. Bearing in mind that it is not always possible to work on disaggregated data, the aim of this paper was to investigate which method of determining a point, minimises bias in the estimation of walking accessibility. The research used the G2SFCA method, introduced by Dai, which has been employed several times to model walking accessibility. Results clearly show that point location methods for area units, based on disaggregating data to buildings, perform better at the scale of statistical districts or cadastral precincts, compared to those based on the centrally weighted mean. They also show that positional measures such as the Euclidean centrally weighted median can improve the results of analyses in units that are heterogeneous in terms of settlement network pattern.
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