Identifying clusters in spatial area data

Autor:	Friedrich Gebhardt
Rok vydání:	1998
Předmět:	Variable (computer science) Statistics Spatial clustering Cluster (physics) Value (computer science) Adjacency list Division (mathematics) Spatial analysis Task (project management) Mathematics
Zdroj:	Informatik und Unternehmensführung ISBN: 9783815423110 Geomed
DOI:	10.1007/978-3-322-95397-1_20
Popis:	A task peculiar to spatial data is to find spatial clusters. Three alternative tests will be given here for the case that a region is divided into a number of districts and each district is assigned a numerical value, i. e. the value for a variable of interest. A cluster of districts with high (or low) values cannot just be based on the adjacency of districts since then a random assignment would already produce too many and too large clusters. Thus the cluster definition is based on district triplets, essentially three districts meeting at a common corner. Two tests are designed for a division of the area into marked and unmarked districts. The third, more elaborate test uses the given values directly.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::73f63b14f1df58939ba0e4f3c17e0ceb https://doi.org/10.1007/978-3-322-95397-1_20 Zobrazit plný text záznamu