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EMDS 3.0:A modeling framework for coping with complexity in environmental assessment and planning

EMDS 3.0:A modeling framework for coping with complexity in environmental assessment and planning

作     者:Keith M.Reynolds 

作者机构:U.S.Dept.AgricultureForest ServicePacific Northwest Research Station3200 SW Jefferson WayCorvallisOR 97331USA 

出 版 物:《Science China(Technological Sciences)》 (中国科学(技术科学英文版))

年 卷 期:2006年第49卷第z1期

页      面:63-75页

核心收录:

学科分类:0810[工学-信息与通信工程] 083002[工学-环境工程] 0830[工学-环境科学与工程(可授工学、理学、农学学位)] 07[理学] 08[工学] 0805[工学-材料科学与工程(可授工学、理学学位)] 0702[理学-物理学] 0812[工学-计算机科学与技术(可授工学、理学学位)] 0713[理学-生态学] 

基  金:U.S. Forest Service USFS 

主  题:natural resources, modeling, assessment, analysis, planning, software, ecosystem management. 

摘      要:The Ecosystem Management Decision Support (EMDS) system is an application framework for knowledge-based decision support of ecological assessments at any geographic scale. The system integrates state-of-the-art geographic information system (GIS) as well as knowledge-based reasoning and decision modeling technologies to provide decision support for a substantial portion of the adaptive management process of ecosystem management. EMDS 3.0 is implemented as an ArcMap extension and integrates the logic engine of NetWeaver to perform landscape evaluations, and the decision modeling engine of Criterium DecisionPlus for evaluating management priorities. Key features of the system s evaluation component include abilities to (1) reason about large, abstract, multi-faceted ecosystem management problems, (2) perform useful evaluations with incomplete information, (3) evaluate the influence of missing information, and (4) determine priorities for missing information. A key feature of the planning component is the ability to determine priorities for management activities, taking into account not only ecosystem condition, but also criteria that account for the feasibility and efficacy of potential management actions. Both components include powerful and intuitive diagnostic features that facilitate communicating the explanation of modeling results to a broad audience.

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