Incorporating the value of ecological networks into cost–benefit analysis to improve spatially explicit land-use planning
Our research is based on the assumption that cost–benefit analysis facilitates efficient and effective decision-making in spatially explicit land-use planning where there are competing land uses. Land-use planning can be improved if the value of the spatial relationships between land uses can be com...
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Veröffentlicht in: | Ecological economics 2012, Vol.73 (1), p.66-74 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Our research is based on the assumption that cost–benefit analysis facilitates efficient and effective decision-making in spatially explicit land-use planning where there are competing land uses. Land-use planning can be improved if the value of the spatial relationships between land uses can be computed sufficiently easily. In this paper, we developed an economically sound way to incorporate the spatial dimensions (size and connectedness) of ecological networks within cost–benefit analysis. The methodology computes the value of ecological networks by accounting for the essential spatial characteristics (size and configuration) of areas of natural land. This methodology can be generalised to other land uses, which we illustrate using a hypothetical case study that contains all the relevant elements. The optimal configuration of different land uses, which accounts for the value of the ecosystem network, will generate a land-use plan with the highest net benefit.
► Improve land-use planning by computing the value of the spatial relationships between land uses. ► We incorporated the spatial dimensions of ecological networks within CBA. ► We compute the value of ecological networks using the essential spatial characteristics. ► We show that this methodology can be generalised to other land uses. ► Optimal configuration of different land uses generates land-use plan with highest net benefit. |
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ISSN: | 0921-8009 1873-6106 |
DOI: | 10.1016/j.ecolecon.2011.10.021 |