Abstract
This study applies remote sensing, GIS, landscape indices, and multivariate statistical analysis to monitor spatial and temporal land-use variations of Taipei districts from 1993 to 2007. The process includes the calculation of landscape indices from land-use maps and the performance of multivariate statistical analysis with three cases (i.e., cluster analysis with original landscape indices, principal component analysis, and factor analysis). The result from landscape indices indicates that variations exist among districts. As for multivariate statistical analysis, three cases achieve the same result. The results are concluded as follows: The integration of spatial technologies and landscape indices is a timely and useful approach to monitor Taipei land-use change. In addition, multivariate statistical analysis is a feasible approach for land-use change analysis. Particularly, principal component analysis and factor analysis are good for reducing the number of landscape indices, and cluster analysis is good for analyzing the spatial and temporal variations of Taipei districts. Therefore, the result obtained from this study can be a reference of Taipei urban planning in future.
| Original language | English |
|---|---|
| Title of host publication | 31st Asian Conference on Remote Sensing 2010, ACRS 2010 |
| Pages | 1479-1485 |
| Number of pages | 7 |
| Publication status | Published - 2010 Dec 1 |
| Event | 31st Asian Conference on Remote Sensing 2010, ACRS 2010 - Hanoi, Viet Nam Duration: 2010 Nov 1 → 2010 Nov 5 |
Publication series
| Name | 31st Asian Conference on Remote Sensing 2010, ACRS 2010 |
|---|---|
| Volume | 2 |
Other
| Other | 31st Asian Conference on Remote Sensing 2010, ACRS 2010 |
|---|---|
| Country | Viet Nam |
| City | Hanoi |
| Period | 10-11-01 → 10-11-05 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
Cite this
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Study on monitoring taipei land-use change. / Chen, Yeong Kuan; Cheng, Chi Chuan; Wang, Su Fen; Wang, Rong Peng.
31st Asian Conference on Remote Sensing 2010, ACRS 2010. 2010. p. 1479-1485 (31st Asian Conference on Remote Sensing 2010, ACRS 2010; Vol. 2).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Study on monitoring taipei land-use change
AU - Chen, Yeong Kuan
AU - Cheng, Chi Chuan
AU - Wang, Su Fen
AU - Wang, Rong Peng
PY - 2010/12/1
Y1 - 2010/12/1
N2 - This study applies remote sensing, GIS, landscape indices, and multivariate statistical analysis to monitor spatial and temporal land-use variations of Taipei districts from 1993 to 2007. The process includes the calculation of landscape indices from land-use maps and the performance of multivariate statistical analysis with three cases (i.e., cluster analysis with original landscape indices, principal component analysis, and factor analysis). The result from landscape indices indicates that variations exist among districts. As for multivariate statistical analysis, three cases achieve the same result. The results are concluded as follows: The integration of spatial technologies and landscape indices is a timely and useful approach to monitor Taipei land-use change. In addition, multivariate statistical analysis is a feasible approach for land-use change analysis. Particularly, principal component analysis and factor analysis are good for reducing the number of landscape indices, and cluster analysis is good for analyzing the spatial and temporal variations of Taipei districts. Therefore, the result obtained from this study can be a reference of Taipei urban planning in future.
AB - This study applies remote sensing, GIS, landscape indices, and multivariate statistical analysis to monitor spatial and temporal land-use variations of Taipei districts from 1993 to 2007. The process includes the calculation of landscape indices from land-use maps and the performance of multivariate statistical analysis with three cases (i.e., cluster analysis with original landscape indices, principal component analysis, and factor analysis). The result from landscape indices indicates that variations exist among districts. As for multivariate statistical analysis, three cases achieve the same result. The results are concluded as follows: The integration of spatial technologies and landscape indices is a timely and useful approach to monitor Taipei land-use change. In addition, multivariate statistical analysis is a feasible approach for land-use change analysis. Particularly, principal component analysis and factor analysis are good for reducing the number of landscape indices, and cluster analysis is good for analyzing the spatial and temporal variations of Taipei districts. Therefore, the result obtained from this study can be a reference of Taipei urban planning in future.
UR - http://www.scopus.com/inward/record.url?scp=84865635290&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84865635290&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84865635290
SN - 9781617823978
T3 - 31st Asian Conference on Remote Sensing 2010, ACRS 2010
SP - 1479
EP - 1485
BT - 31st Asian Conference on Remote Sensing 2010, ACRS 2010
ER -