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A local polycategorical approach to areal interpolation

机译：区域插值的局部多分类方法

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Areal interpolation is a technique used to transfer attribute information from source zone's with known values to target zones with unknown values. This paper presents and describes a new polycategorical method that integrates positive aspects of both geographically weighted regression (GWR)-based and quantile regression (QR)-based interpolators for solving areal interpolation problems. Two different types of neighborhoods for selecting observations used to estimate ancillary control densities are presented: one that is spatially based and one that is statistically based. The new polycategorical methods are evaluated against a number of existing methods - areal weighting, pycnophylactic, binary dasymetric, intelligent dasymetric mapping, and GWR using test data from the 2010 census population, the National Land Cover Database 2006 (NLCD2006) and the Topologically Integrated Geographic Encoding and Reference (TIGER) line graph files. The evaluations include several overall error measurement indices as well as maps of the spatial distribution of the error associated with selected methods. Results suggest that with appropriate land cover categories and neighborhoods, the new polycategorical methods provide comparable results to local regression models but with much less computation complexity. (C) 2015 Elsevier Ltd. All rights reserved.
机译：区域插值是一种用于将属性信息从具有已知值的源区域传输到具有未知值的目标区域的技术。本文介绍并描述了一种新的多类别方法，该方法整合了基于地理加权回归（GWR）和基于分位数回归（QR）的插值器的积极方面，以解决区域插值问题。介绍了两种不同类型的邻域，用于选择用于估计辅助控制密度的观测值：一种是基于空间的，另一种是基于统计的。使用来自2010年人口普查人口，国家土地覆盖数据库2006（NLCD2006）和拓扑综合地理学的测试数据，对照许多现有方法对新的多类别方法进行了评估-面积加权，叶肉预防，二元大数据测绘，智能大数据测绘和GWR。编码和参考（TIGER）折线图文件。评估包括几个总体误差测量指标以及与所选方法相关的误差的空间分布图。结果表明，有了适当的土地覆盖类别和邻域，新的多类别方法可以提供与本地回归模型相当的结果，但计算复杂度要低得多。 （C）2015 Elsevier Ltd.保留所有权利。

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