Forestland classification using an ecosystem approach

C. C. Cheng, Y. K. Chen, Su-Fen Wang, J. F. Jan

Research output: Contribution to journalConference article

Abstract

This study focuses on using an ecosystem approach for forestland classification of the Liukuei Experimental Forest of Taiwan Forestry Research Institute. The content includes the delineation of ecosystem units using DTM, the development of a hierarchical ecosystem classification system using GIS and multivariate statistical analysis, the establishment of a forestland classification decision support system (DSS) and its application on site selection of a Taiwanese native species - Taiwania (Taiwania cryptomerioides). The results indicate that DTM is a fast, easy, feasible, and automatic approach for delineating ecosystem units of different spatial scales. The developed hierarchical ecosystem classification is a satisfactory scheme for Liukuei's forestland classification because the developed scheme coincides with the terrain characteristics along a continuum. The established DSS can effectively and feasibly analyze forestland classification under different spatial scales. Meanwhile, the system can easily perform site selection for Taiwania. From the results, it is concluded that techniques such as DTM, GIS, and DSS are useful for forest managers in the reasonable planning of forestland classification and management practice. In addition, the ecosystem approaches obtained from the Experimental Forest will be extended to island-wide forestland classification in Taiwan.

Original languageEnglish
Pages (from-to)181-185
Number of pages5
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume35
Publication statusPublished - 2004 Jan 1
Event20th ISPRS Congress on Technical Commission VII - Istanbul, Turkey
Duration: 2004 Jul 122004 Jul 23

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ecosystem approach
Ecosystems
digital terrain model
decision support system
Decision support systems
Site selection
ecosystem
site selection
Geographic information systems
Geographical Information System
Taiwan
GIS
Forestry
research facility
forestry
multivariate analysis
native species
statistical analysis
management practice
Statistical methods

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Geography, Planning and Development

Cite this

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abstract = "This study focuses on using an ecosystem approach for forestland classification of the Liukuei Experimental Forest of Taiwan Forestry Research Institute. The content includes the delineation of ecosystem units using DTM, the development of a hierarchical ecosystem classification system using GIS and multivariate statistical analysis, the establishment of a forestland classification decision support system (DSS) and its application on site selection of a Taiwanese native species - Taiwania (Taiwania cryptomerioides). The results indicate that DTM is a fast, easy, feasible, and automatic approach for delineating ecosystem units of different spatial scales. The developed hierarchical ecosystem classification is a satisfactory scheme for Liukuei's forestland classification because the developed scheme coincides with the terrain characteristics along a continuum. The established DSS can effectively and feasibly analyze forestland classification under different spatial scales. Meanwhile, the system can easily perform site selection for Taiwania. From the results, it is concluded that techniques such as DTM, GIS, and DSS are useful for forest managers in the reasonable planning of forestland classification and management practice. In addition, the ecosystem approaches obtained from the Experimental Forest will be extended to island-wide forestland classification in Taiwan.",
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Forestland classification using an ecosystem approach. / Cheng, C. C.; Chen, Y. K.; Wang, Su-Fen; Jan, J. F.

In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Vol. 35, 01.01.2004, p. 181-185.

Research output: Contribution to journalConference article

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AU - Cheng, C. C.

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AU - Wang, Su-Fen

AU - Jan, J. F.

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