Open AccessSPATIAL AUTOCORRELATION ANALYSIS OF HOUSING DISTRIBUTION IN JOHOR BAHRU
Author(s) -
Nur Asyikin Mohd Sairi,
Burhaida Burhan,
Edie Ezwan Mohd Safian
Publication year - 2021
Publication title -
planning malaysia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.232
H-Index - 7
eISSN - 1675-6215
pISSN - 0128-0945
DOI - 10.21837/pm.v19i17.1014
Subject(s) - spatial analysis , geography , spatial distribution , autocorrelation , distribution (mathematics) , cluster analysis , cluster (spacecraft) , cartography , identification (biology) , spatial ecology , economic geography , statistics , mathematics , computer science , ecology , remote sensing , mathematical analysis , biology , programming language
Geographic location naturally generates spatial patterns that are either clustered, dispersed, or random. Moreover, Tobler’s First Law of Geography is essentially a testable assumption in the concept where geographic location matters and one method for quantifying Tobler’s law of geography is through measures of spatial autocorrelation. Therefore, the purpose of this study is to identify the spatial patterns of housing distribution in Johor Bahru through the spatial autocorrelation method. The result of the global spatial autocorrelation analysis demonstrates a high degree of clustering within the housing distribution, as well as the identification of a clustered pattern with a highly positive Moran’s I value of 0.995207. Following that, the LISA cluster map successfully identified individual clusters of each housing unit with their neighbours through the red and blue colours displayed on the map, as well as revealing home buyers’ preferences for a property in each location.