Methods for translating narrative scenarios into quantitative assessments of land use change
In the land use and land cover (LULC) literature, narrative scenarios are qualitative descriptions of plausible futures associated with a combination of socio-economic, policy, technological, and climate changes. LULC models are then often used to translate these narrative descriptions into quantita...
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Published in | Environmental modelling & software : with environment data news Vol. 82; pp. 7 - 20 |
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Main Authors | , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.08.2016
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Subjects | |
Online Access | Get full text |
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Summary: | In the land use and land cover (LULC) literature, narrative scenarios are qualitative descriptions of plausible futures associated with a combination of socio-economic, policy, technological, and climate changes. LULC models are then often used to translate these narrative descriptions into quantitative characterizations of possible future societal and ecological impacts and conditions. To respect the intent of the underlying scenario descriptions, this process of translation needs to be thoughtful, transparent, and reproducible. This paper evaluates the current state of the art in scenario translation methods and outlines their relative advantages and disadvantages, as well as the respective roles of stakeholders and subject matter experts. We summarize our findings in the form of a decision matrix that can assist land use planners, scientists, and modelers in choosing a translation method appropriate to their situation.
•Assessments of land use and land cover change often employ narrative scenarios.•Detailed evaluation of policy actions and outcomes requires quantitative model output.•We review methods of translating narrative scenarios into model-based assessments.•A summary table provides guidance for choosing a method suitable for the situation. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1364-8152 1873-6726 |
DOI: | 10.1016/j.envsoft.2016.04.011 |