Developments in areal interpolation methods and GIS
Developments in areal interpolation methods and GIS
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DOI：
10.1007/978-3-642-77500-0_5
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发表时间：
1992-03
期刊：
影响因子：
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通讯作者：
R. Flowerdew;Mick Green
中科院分区：
文献类型：
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作者：
R. Flowerdew;Mick Green
本文是作者面积插值研究项目的回顾和扩展。它所涉及的问题是，当一个区域因不同的目的被划分为不同的区域组时，一组区域（源区域）的可用数据需要用于不同的区域组（目标区域）。标准的方法是基于假设源区域数据均匀分布在每个区域内，但我们的方法允许考虑有关目标区域的额外信息，以便可以得出更准确的目标区域估计。所使用的方法是基于EM算法。迄今为止报道的大多数工作（例如Flowerdew和绿色，1989年）都与计数数据有关，其分布可以用泊松假设来模拟。在人口普查和调查中经常会遇到这种数据。其他类型的数据更适合被视为具有连续分布。本文主要研究正态分布数据的面积插值问题。一种方法是开发适合这样的数据，并适用于房价数据普雷斯顿，兰开夏郡，开始与平均房价在1990年为当地政府病房和估计平均房价的邮政编码部门。
This paper is a review and extension of the authors’ research project on areal interpolation. It is concerned with problems arising when a region is divided into different sets of zones for different purposes, and data available for one set of zones (source zones) are needed for a different set (target zones). Standard approaches are based on the assumption that source zone data are evenly distributed within each zone, but our approach allows additional information about the target zones to be taken into account so that more accurate target zone estimates can be derived. The method used is based on the EM algorithm. Most of the work reported so far (e.g. Flowerdew and Green 1989) has been concerned with count data whose distribution can be modelled using a Poisson assumption. Such data are frequently encountered in censuses and surveys. Other types of data are more appropriately regarded as having continuous distributions. This paper is primarily concerned with areal interpolation of normally distributed data. A method is developed suitable for such data and is applied to house price data for Preston, Lancashire, starting with mean house prices in 1990 for local government wards and estimating mean house prices for postcode sectors.