Forest Ecosystem Management Decision Support System─A Case Study of Lukuei Experimental Forest

博士 === 國立臺灣大學 === 森林學研究所 === 90 === The purpose of this study is to establish a multi-scale forestland classification decision support system under the integration of a hierarchical forestland classification and a mathematic programming method. The Ecosystem Management Decision Support (EMDS) system...

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Bibliographic Details
Main Authors: Su-Fen Wang, 王素芬
Other Authors: Yeong-Kuan Chen
Format: Others
Language:zh-TW
Published: 2001
Online Access:http://ndltd.ncl.edu.tw/handle/61371293670411549948
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Summary:博士 === 國立臺灣大學 === 森林學研究所 === 90 === The purpose of this study is to establish a multi-scale forestland classification decision support system under the integration of a hierarchical forestland classification and a mathematic programming method. The Ecosystem Management Decision Support (EMDS) system, which was developed by the Forest Service, USDA was applied as a tool to help forest managers make a decision in different management levels. Applied with the mathematic programming method and the fuzzy logic approach, the criteria of forestland classification were rationalized and organized into a knowledge database. The integration between geographical information system (GIS), decision support system (DSS) and mathematic programming methods was then achieved and applied to the Lukuei Experimental Forest for the assessment of forestland suitability analysis and potential Taiwania’s site selection. The results indicate as follows. 1. The multi-scale forestland classification decision support system was a timesaving tool in forestland regulation. With its assistance, forest managers may not only arbitrarily adjust the range of the area interested but also promptly and efficiently modify the value of the criteria selected. The forestland classification system can be associated with different management level models to meet the need of different hierarchical managers. 2. The fuzzy logic approach is theoretically more similar to environmental features than the traditional dichotomy. Therefore, the accuracy of forestland classification can be improved further by jointing the mathematic programming method with the fuzzy logic criteria existing in an auxiliary knowledge database. 3. The potential site selection of Taiwania evaluated by the fores-land classification decision support system was approximately in accord with the distribution of real situation. This indicates that the system is very useful in the practices of site selection and ecosystem management. From the above results, the study was concluded that the multi-scale forestland classification decision support system can be applied to the Lukuei Experimental Forest in terms of forestland classification and ecosystem management practices as a pilot study on one hand; it will, on the other hand, be extended nationwide for the same purpose in the future.