Geneticland : Modelling Land-Use Change Using Evolutionary Algorithms
Future land-use configurations provide valuable knowledge for policy makers and economic agents, especially under expected environmental changes such as decreasing rainfall or increasing temperatures. This chapter proposes an optimisation approach for modelling land-use change in which landscapes (land uses) are generated through the use of an evolutionary algorithm called GeneticLand. It is designed for a multiobjective function that aims at the minimisation of soil erosion and the maximisation of carbon sequestration, under a set of local restrictions. GeneticLand has been applied to a Mediterranean landscape, located in southern Portugal. The algorithm design and the results obtained show the feasibility of the generated landscapes, the appropriateness of the evolutionary methods to model land-use changes and the spatial characteristics of the landscape solutions that emerge when physical drivers have a major influence on their evolution.
| Main Authors: | , , , |
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| Format: | Part of book or chapter of book biblioteca |
| Language: | English |
| Published: |
Springer
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| Subjects: | Mediterranean landscape, Spatial planning, climate change, evolutionary computing, land use, long-term, optimisation, |
| Online Access: | https://research.wur.nl/en/publications/geneticland-modelling-land-use-change-using-evolutionary-algorith |
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| Summary: | Future land-use configurations provide valuable knowledge for policy makers and economic agents, especially under expected environmental changes such as decreasing rainfall or increasing temperatures. This chapter proposes an optimisation approach for modelling land-use change in which landscapes (land uses) are generated through the use of an evolutionary algorithm called GeneticLand. It is designed for a multiobjective function that aims at the minimisation of soil erosion and the maximisation of carbon sequestration, under a set of local restrictions. GeneticLand has been applied to a Mediterranean landscape, located in southern Portugal. The algorithm design and the results obtained show the feasibility of the generated landscapes, the appropriateness of the evolutionary methods to model land-use changes and the spatial characteristics of the landscape solutions that emerge when physical drivers have a major influence on their evolution. |
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