Please use this identifier to cite or link to this item: https://doi.org/10.1111/tgis.12025
Title: Combining Geo‐SOM and Hierarchical Clustering to Explore Geospatial Data
Authors: Feng, Chen-Chieh 
Wang, Yi‐Chen 
CHEN CHIH-YUAN 
Issue Date: Feb-2014
Publisher: Wiley
Citation: Feng, Chen-Chieh, Wang, Yi‐Chen, CHEN CHIH-YUAN (2014-02). Combining Geo‐SOM and Hierarchical Clustering to Explore Geospatial Data. Transactions in GIS 18 (1) : 125-146. ScholarBank@NUS Repository. https://doi.org/10.1111/tgis.12025
Abstract: Geo-SOM is a useful geovisualization technique for revealing patterns in spatial data, but is ineffective in supporting interactive exploration of patterns hidden in different Geo-SOM sizes. Based on the divide and group principle in geovisualization, the article proposes a new methodology that combines Geo-SOM and hierarchical clustering to tackle this problem. Geo-SOM was used to "divide" the dataset into several homogeneous subsets; hierarchical clustering was then used to "group" neighboring homogeneous subsets for pattern exploration in different levels of granularity, thus permitting exploration of patterns at multiple scales. An artificial dataset was used for validating the method's effectiveness. As a case study, the rush hour motorcycle flow data in Taipei City, Taiwan were analyzed. Compared with the best result generated solely by Geo-SOM, the proposed method performed better in capturing the homogeneous zones in the artificial dataset. For the case study, the proposed method discovered six clusters with unique data and spatial patterns at different levels of granularity, while the original Geo-SOM only identified two. Among the four hierarchical clustering methods, Ward's clustering performed the best in pattern discovery. The results demonstrated the effectiveness of the approach in visually and interactively exploring data and spatial patterns in geospatial data.
Source Title: Transactions in GIS
URI: http://scholarbank.nus.edu.sg/handle/10635/78627
ISSN: 13611682
14679671
DOI: 10.1111/tgis.12025
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

7
checked on May 19, 2018

WEB OF SCIENCETM
Citations

7
checked on Apr 2, 2018

Page view(s)

93
checked on Apr 20, 2018

Google ScholarTM

Check

Altmetric


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