Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-4029
Publication type: Conference paper
Type of review: Peer review (publication)
Title: Deconstructed and inverted multi-criteria evaluation for on-the-fly scenario development and decision-making
Authors: Geilhausen, Martin
Laube, Patrick
DOI: 10.21256/zhaw-4029
10.4230/LIPIcs.GISCIENCE.2018.27
Proceedings: 10th International Conference on Geographic Information Science (GIScience 2018)
Editors of the parent work: Winter, Stephan
Griffin, Amy
Sester, Monika
Volume(Issue): 2018
Issue: 27
Pages: 27:1
Pages to: 27:7
Conference details: 10th International Conference on Geographic Information Science (GIScience 2018), Melbourne, 28-31 August 2018
Issue Date: 2018
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Series volume: 114
Publisher / Ed. Institution: Dagstuhl Publishing
ISBN: 978-3-95977-083-5
ISSN: 1868-8969
Other identifiers: https://nbn-resolving.de/urn:nbn:de:0030-drops-97424
Language: English
Subject (DDC): 
Abstract: We propose a variation of the conventional spatial multi-criteria evaluation workflow for suitability analysis that allows efficient on-the fly scenario development for decision-making. Our approach proposes to reconstruct the conventional MCE workflow in order to exclude computationally expensive geoprocessing from the iterative scenario development. We then introduce a procedure that replaces costly iterations of spatial operations with one off-line preprocessing step followed by iterations of much less computationally expensive database queries. We illustrate our approach for deconstructed and inverted multi-criteria analysis with a case study aiming at selecting suitable sites for wind turbines in the Swiss Alps.
URI: http://drops.dagstuhl.de/opus/volltexte/2018/9355
https://digitalcollection.zhaw.ch/handle/11475/11875
Fulltext version: Published version
License (according to publishing contract): CC BY 3.0: Attribution 3.0 Unported
Departement: Life Sciences and Facility Management
Organisational Unit: Institute of Natural Resource Sciences (IUNR)
Published as part of the ZHAW project: Potential zur Windenergienutzung auf Arealen der SBB
Appears in collections:Publikationen Life Sciences und Facility Management

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