Sensitivity Analysis of Spatial Autocorrelation Using Distinct Geometrical Settings: Guidelines for the Urban Econometrician

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Abstract

Inferences based on spatial analysis of areal data depend greatly on the method used to quantify the degree of proximity between spatial units - regions. These proximity measures are normally organized in the form of weights matrices, which are used to obtain statistics that take into account neighbourhood relations between agents. In any scientific field where the focus is on human behaviour, areal datasets are immensely relevant since this is the most common form of data collection (normally as count data). The method or schema used to divide a continuous spatial surface into sets of discrete units influence inferences about geographical and social phenomena, mainly because these units are neither homogeneous nor regular. This article tests the effect of different geometrical data aggregation schemas on global spatial auto-correlation statistics. Two geographical variables are taken into account: scale (resolution) and form (regularity). This is achieved through the use of different aggregation levels and geometrical schemas. Five different datasets are used, all representing the distribution of resident population aggregated for two study areas, with the objective of consistently test the effect of different spatial aggregation schemas.

Original languageEnglish
Title of host publicationCOMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2014, PT III
EditorsB Murgante, S Misra, AMAC Rocha, C Torre, JG Rocha, MI Falcao, D Taniar, BO Apduhan, O Gervasi
PublisherSPRINGER-VERLAG BERLIN
Pages345-356
Number of pages12
ISBN (Print)978-3-319-09149-5
Publication statusPublished - 2014
Event14th International Conference on Computational Science and Its Applications (ICCSA) - Guimaraes, Portugal
Duration: 30 Jun 20143 Jul 2014

Publication series

NameLecture Notes in Computer Science
PublisherSPRINGER-VERLAG BERLIN
Volume8581
ISSN (Print)0302-9743

Conference

Conference14th International Conference on Computational Science and Its Applications (ICCSA)
CountryPortugal
CityGuimaraes
Period30/06/143/07/14

Keywords

  • Spatial Autocorrelation
  • spatial weights matrix
  • spillover effects

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