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Degradation-Loss Sensitivity Analysis in Multi-Objective Land Allocation

Description: Dataset generated by Monte Carlo sampling of a Multi-Objective Land Allocation that incorporates a model of environmental degradation.
Authors: Cabrera, Sierra; Queen's University
Babayan, Irina; Queen's University
Aliahmadi, Hazhir; Queen's University
Chen, Dongmei; Queen's University
van Anders, Greg; Queen's University; ORCID iD 0000-0002-9746-2484
Keywords: Multi-Objective Land Allocation
Climate Change
Monte Carlo Sampling
Statistical Physics
Geographic Information Systems
Field of Research: 
Social and economic geography
>
Urban and regional planning
>
Land use and environmental planning
Publication Date: 2023-11-22
Publisher: Federated Research Data Repository / dépôt fédéré de données de recherche
Funder: Natural Sciences and Engineering Research Council of Canada; RGPIN-2019-05655
Natural Sciences and Engineering Research Council of Canada; DGECR-2019-00469
Natural Sciences and Engineering Research Council of Canada; RGPIN-2019-05773
URI: https://doi.org/10.20383/103.0842
Related Identifiers: 
Geographic Coverage: 
Place Name
Dongxihu District
City
Wuhan
Province / Territory / State
Hubei
Country
China

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Access to this dataset is subject to the following terms:
Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
Citation
Cabrera, S., Babayan, I., Aliahmadi, H., Chen, D., van Anders, G. (2023). Degradation-Loss Sensitivity Analysis in Multi-Objective Land Allocation. Federated Research Data Repository. https://doi.org/10.20383/103.0842