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A variable resolution, geocomputational approach to the analysis of point patterns
Author(s) -
Brimicombe Allan J.,
Tsui Paul H. Y.
Publication year - 2000
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/1099-1085(20000815/30)14:11/12<2143::aid-hyp60>3.0.co;2-i
Subject(s) - variable (mathematics) , computer science , quadrat , scale (ratio) , data mining , exploratory data analysis , event (particle physics) , function (biology) , point (geometry) , cartography , geography , mathematics , geology , transect , mathematical analysis , oceanography , physics , geometry , quantum mechanics , evolutionary biology , biology
A geocomputational approach to the solution of applied spatial problems is being ushered in to take advantage of ever increasing computer power. The move is seen widely as a paradigm shift allowing better solutions to be found for old problems, solutions to be found for previously unsolvable problems and the development of new quantitative approaches to geography. This paper uses geocomputation to revisit point‐pattern analysis as an objective, exploratory means of evaluating mapped distributions of landforms and/or events. A new variable resolution approach is introduced and tested alongside more traditional approaches of nearest neighbour distance and quadrat analysis and against another geocomputational approach, the K function. The results demonstrate that firstly, the geocomputational paradigm allows new and more useful solutions to be found for old problems. Secondly, a variable resolution approach to geographical data analysis goes some way towards overcoming the problem of scale inherent in such analyses. Finally, the technique facilitates spatiotemporal analyses of event data, such as landslides, thus offering new lines of enquiry in areas such as hazard mitigation. Copyright © 2000 John Wiley & Sons, Ltd.