Paper/Poster/Presentation Title
Keywords
Multifunctionality; Sustainability; Land Use Optimization; Ecosystem Services; Biodiversity; Modelling.
Location
Session D10: The Role of Modelling in Sustainable Development
Start Date
11-7-2016 9:10 AM
End Date
11-7-2016 9:30 AM
Abstract
The sustainable appropriation of resources and the design of multifunctional landscapes requires the finding of solutions that minimize trade-offs between contrasting goals of land use, ecosystem services and biodiversity. Substantial progress has been made in the model-based quantification of land-use effects on ecosystem services and biodiversity over the past years, but finding ‘optimal' land use patterns is still one of the challenges. Existing implementations of multi- objective land use optimization often have shortcomings or are not well designed for meeting multiple demands. For example, users may wish to include computationally extensive and complex process- based or statistical models to define their objective functions. Further, land use optimization has to consider user-defined constraints for the transformation rules between different land uses, to allow the exclusion of certain areas (e.g., patches) from the optimization and to include ways to limit the total area of each land use type based on minimum and maximum thresholds. Building upon recent advances of how to consider such spatial constraints, we present the framework CoMOLA (Constrained Multi-Objective Land Allocation). It is a freely available spatially-explicit optimization routine based on the NSGA-II genetic algorithm, which embraces multiple objectives and the mentioned user-defined constraints. Specifically, we have included a new variator to efficiently generate feasible solutions and a novel approach to test the feasibility of solutions. CoMOLA may be applied to address a wide range of different research questions and is aimed to facilitate interdisciplinary and comprehensive assessments of the performance (and limits) of a landscape based on multiple criteria such as environmental quality indicators, biodiversity indicators but also economic returns. The different options to constrain the spatial optimization in order to achieve more realistic results further ease the involvement of stakeholders in the study design and evaluation of the results. Related to presented framework, the role of modelling for evaluating sustainability and the multifunctionality of landscapes “in science and practice” are discussed in the presentation.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
Towards Multifunctionality of Landscapes – A Multi- Objective Land Use Optimization Framework for Exploring Interaction between Ecosystem Services and Biodiversity
Session D10: The Role of Modelling in Sustainable Development
The sustainable appropriation of resources and the design of multifunctional landscapes requires the finding of solutions that minimize trade-offs between contrasting goals of land use, ecosystem services and biodiversity. Substantial progress has been made in the model-based quantification of land-use effects on ecosystem services and biodiversity over the past years, but finding ‘optimal' land use patterns is still one of the challenges. Existing implementations of multi- objective land use optimization often have shortcomings or are not well designed for meeting multiple demands. For example, users may wish to include computationally extensive and complex process- based or statistical models to define their objective functions. Further, land use optimization has to consider user-defined constraints for the transformation rules between different land uses, to allow the exclusion of certain areas (e.g., patches) from the optimization and to include ways to limit the total area of each land use type based on minimum and maximum thresholds. Building upon recent advances of how to consider such spatial constraints, we present the framework CoMOLA (Constrained Multi-Objective Land Allocation). It is a freely available spatially-explicit optimization routine based on the NSGA-II genetic algorithm, which embraces multiple objectives and the mentioned user-defined constraints. Specifically, we have included a new variator to efficiently generate feasible solutions and a novel approach to test the feasibility of solutions. CoMOLA may be applied to address a wide range of different research questions and is aimed to facilitate interdisciplinary and comprehensive assessments of the performance (and limits) of a landscape based on multiple criteria such as environmental quality indicators, biodiversity indicators but also economic returns. The different options to constrain the spatial optimization in order to achieve more realistic results further ease the involvement of stakeholders in the study design and evaluation of the results. Related to presented framework, the role of modelling for evaluating sustainability and the multifunctionality of landscapes “in science and practice” are discussed in the presentation.
