Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32740
Title: A multiscale approach for spatio-temporal outlier detection
Authors: Cheng, T
Li, Z 
Issue Date: 2006
Source: Transactions in GIS, 2006, v. 10, no. 2, p. 253-263 How to cite?
Journal: Transactions in GIS 
Abstract: A spatial outlier is a spatially referenced object whose thematic attribute values are significantly different from those of other spatially referenced objects in its spatial neighborhood. It represents an object that is significantly different from its neighbourhoods even though it may not be significantly different from the entire population. Here we extend this concept to the spatio-temporal domain and define a spatial-temporal outlier (ST-outlier) to be a spatial-temporal object whose thematic attribute values are significantly different from those of other spatially and temporally referenced objects in its spatial or/ and temporal neighbourhoods. Identification of ST-outliers can lead to the discovery of unexpected, interesting, and implicit knowledge, such as local instability or deformation. Many methods have been recently proposed to detect spatial outliers, but how to detect the temporal outliers or spatial-temporal outliers has been seldom discussed. In this paper we propose a multiscale approach to detect ST-outliers by evaluating the change between consecutive spatial and temporal scales. A four-step procedure consisting of classification, aggregation, comparison and verification is put forward to address the semantic and dynamic properties of geographic phenomena for ST-outlier detection. The effectiveness of the approach is illustrated by a practical coastal geomorphic study.
URI: http://hdl.handle.net/10397/32740
ISSN: 1361-1682
DOI: 10.1111/j.1467-9671.2006.00256.x
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

41
Last Week
0
Last month
0
Citations as of Dec 5, 2018

Page view(s)

69
Last Week
0
Last month
Citations as of Dec 16, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.