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Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty

Land-use allocation models can effectively support sustainable land use. A large number of studies solve the problems of land-use planning by constructing models, such as mathematical models and spatial analysis models. However, these models fail to fully and comprehensively consider three uncertain...

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Autores principales: Lu, Yao, Zhou, Min, Ou, Guoliang, Zhang, Zuo, He, Li, Ma, Yuxiang, Ma, Chaonan, Tu, Jiating, Li, Siqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8708993/
https://www.ncbi.nlm.nih.gov/pubmed/34949016
http://dx.doi.org/10.3390/ijerph182413411
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author Lu, Yao
Zhou, Min
Ou, Guoliang
Zhang, Zuo
He, Li
Ma, Yuxiang
Ma, Chaonan
Tu, Jiating
Li, Siqi
author_facet Lu, Yao
Zhou, Min
Ou, Guoliang
Zhang, Zuo
He, Li
Ma, Yuxiang
Ma, Chaonan
Tu, Jiating
Li, Siqi
author_sort Lu, Yao
collection PubMed
description Land-use allocation models can effectively support sustainable land use. A large number of studies solve the problems of land-use planning by constructing models, such as mathematical models and spatial analysis models. However, these models fail to fully and comprehensively consider three uncertain factors of land-use systems: randomness, interval and fuzziness. 33Therefore, through the study of the watershed land-use system, this paper develops a land-use allocation model considering the regional land–society–economy–environment system under uncertain conditions. On the basis of this model, an interval fuzzy two-stage random land-use allocation model (IFTSP-LUAM) combining social, economic and ecological factors is proposed to provide sustainable development strategies at the basin level. In addition, the proposed IFTSP-LUAM takes into account the above three uncertainties and multistage, multiobjective, dynamic, systematic and complex characteristics of typical land-use planning systems. The results showed that the model considers more socioeconomic and ecological factors and can effectively reflect the quantitative relationship between the increase in economic benefits and the decrease in environmental costs of a land-use system. The model was applied to land-use planning of Nansihu River Basin in Shandong Province. The results provided a series of suitable land-use patterns and environmental emission scenarios under uncertain conditions, which can help the watershed environmental protection bureau and watershed land-use decision-makers to formulate appropriate land-use policies, so as to balance social and economic development and ecological protection. The simulation results can provide support for an in-depth analysis of land-use patterns and the trade-off between economic development and ecological environment protection.
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spelling pubmed-87089932021-12-25 Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty Lu, Yao Zhou, Min Ou, Guoliang Zhang, Zuo He, Li Ma, Yuxiang Ma, Chaonan Tu, Jiating Li, Siqi Int J Environ Res Public Health Article Land-use allocation models can effectively support sustainable land use. A large number of studies solve the problems of land-use planning by constructing models, such as mathematical models and spatial analysis models. However, these models fail to fully and comprehensively consider three uncertain factors of land-use systems: randomness, interval and fuzziness. 33Therefore, through the study of the watershed land-use system, this paper develops a land-use allocation model considering the regional land–society–economy–environment system under uncertain conditions. On the basis of this model, an interval fuzzy two-stage random land-use allocation model (IFTSP-LUAM) combining social, economic and ecological factors is proposed to provide sustainable development strategies at the basin level. In addition, the proposed IFTSP-LUAM takes into account the above three uncertainties and multistage, multiobjective, dynamic, systematic and complex characteristics of typical land-use planning systems. The results showed that the model considers more socioeconomic and ecological factors and can effectively reflect the quantitative relationship between the increase in economic benefits and the decrease in environmental costs of a land-use system. The model was applied to land-use planning of Nansihu River Basin in Shandong Province. The results provided a series of suitable land-use patterns and environmental emission scenarios under uncertain conditions, which can help the watershed environmental protection bureau and watershed land-use decision-makers to formulate appropriate land-use policies, so as to balance social and economic development and ecological protection. The simulation results can provide support for an in-depth analysis of land-use patterns and the trade-off between economic development and ecological environment protection. MDPI 2021-12-20 /pmc/articles/PMC8708993/ /pubmed/34949016 http://dx.doi.org/10.3390/ijerph182413411 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lu, Yao
Zhou, Min
Ou, Guoliang
Zhang, Zuo
He, Li
Ma, Yuxiang
Ma, Chaonan
Tu, Jiating
Li, Siqi
Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty
title Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty
title_full Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty
title_fullStr Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty
title_full_unstemmed Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty
title_short Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty
title_sort sustainable land-use allocation model at a watershed level under uncertainty
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8708993/
https://www.ncbi.nlm.nih.gov/pubmed/34949016
http://dx.doi.org/10.3390/ijerph182413411
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