Keywords

landscape management, modelling, framework, decision support

Start Date

1-7-2012 12:00 AM

Description

The evaluation of current and future land use and management impacts on ecosystem processes often requires the application of a wide range of specialized models covering different environmental research disciplines. We promote the newly developed Landscape Management Framework (LMF) as a way to facilitate and ease the consideration of land use and management actions within such integrated modeling approaches. LMF takes advantage of existing modeling approaches, provides easy to handle interfaces to external models, and mediates between them. Virtual model stakeholders (agents) within LMF follow a set of user defined decision rules according to binary and fuzzy logics to allow semi-optimal and customized decisions to be made in order to achieve optimal solutions and management timing even during unprecedented events. Preliminary results of LMF are promising and will be further tested with case studies to follow.

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Jul 1st, 12:00 AM

Landscape Management Framework (LMF) - development and application of a new concept for a dynamic landscape management model

The evaluation of current and future land use and management impacts on ecosystem processes often requires the application of a wide range of specialized models covering different environmental research disciplines. We promote the newly developed Landscape Management Framework (LMF) as a way to facilitate and ease the consideration of land use and management actions within such integrated modeling approaches. LMF takes advantage of existing modeling approaches, provides easy to handle interfaces to external models, and mediates between them. Virtual model stakeholders (agents) within LMF follow a set of user defined decision rules according to binary and fuzzy logics to allow semi-optimal and customized decisions to be made in order to achieve optimal solutions and management timing even during unprecedented events. Preliminary results of LMF are promising and will be further tested with case studies to follow.