Clarity versus complexity: Land-use modeling as a practical tool for decision-makers.
Abstract: The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the...
| Publicado en: | Journal of Environmental Management Vol. 129; pp. 235 - 244 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Academic Press Inc.
Nov2013
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=91100671&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 91100671 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03014797 EMJ jtl: Journal of Environmental Management issn: 03014797 maglogo: N pubinfo: dt: Nov2013 vid: 129 pid: 735 pub: Academic Press Inc. artinfo: ui: 91100671 10.1016/j.jenvman.2013.07.027 ppf: 235 ppct: 9 formats: tig: atl: Clarity versus complexity: Land-use modeling as a practical tool for decision-makers. aug: au: Sohl, Terry L. Claggett, Peter R. affil: U.S. Geological Survey, Earth Resources Observation and Science (EROS) Center, 47914 252nd Street, Sioux Falls, SD 57198, USA U.S. Geological Survey, USGS Southeast Area, 410 Severn Avenue, Suite 109, Annapolis, MD 21403, USA su: Land use Decision making Environmental policy Cellular automata Biocomplexity Stakeholders sug: subj: Land use Decision making Environmental policy Other provincial and territorial public administration Administration of Air and Water Resource and Solid Waste Management Programs Cellular automata Biocomplexity Stakeholders keyword: Clarity Complexity Decision support Model Policy Clarity Complexity Decision support Model Policy ab: Abstract: The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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