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CLUMondo-BNU for simulating land system changes based on many-to-many demand–supply relationships with adaptive conversion orders

Land resources are fundamentally important to human society, and their transition from one macroscopic state to another is a vital driving force of environment and climate change locally and globally. Thus, many efforts have been devoted to the simulations of land changes. Among all spatially explic...

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Autores principales: Gao, Peichao, Gao, Yifan, Zhang, Xiaodan, Ye, Sijing, Song, Changqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076298/
https://www.ncbi.nlm.nih.gov/pubmed/37019915
http://dx.doi.org/10.1038/s41598-023-31001-3
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author Gao, Peichao
Gao, Yifan
Zhang, Xiaodan
Ye, Sijing
Song, Changqing
author_facet Gao, Peichao
Gao, Yifan
Zhang, Xiaodan
Ye, Sijing
Song, Changqing
author_sort Gao, Peichao
collection PubMed
description Land resources are fundamentally important to human society, and their transition from one macroscopic state to another is a vital driving force of environment and climate change locally and globally. Thus, many efforts have been devoted to the simulations of land changes. Among all spatially explicit simulation models, CLUMondo is the only one that simulates land changes by incorporating the multifunctionality of a land system and allows the establishment of many-to-many demand–supply relationships. In this study, we first investigated the source code of CLUMondo, providing a complete, detailed mechanism of this model. We found that the featured function of CLUMondo—balancing demands and supplies in a many-to-many mode—relies on a parameter called conversion order. The setting of this parameter is a manual process and requires expert knowledge, which is not feasible for users without an understanding of the whole, detailed mechanism. Therefore, the second contribution of this study is the development of an automatic method for adaptively determining conversion orders. Comparative experiments demonstrated the validity and effectiveness of the proposed automated method. We revised the source code of CLUMondo to incorporate the proposed automated method, resulting in CLUMondo-BNU v1.0. This study facilitates the application of CLUMondo and helps to exploit its full potential.
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spelling pubmed-100762982023-04-07 CLUMondo-BNU for simulating land system changes based on many-to-many demand–supply relationships with adaptive conversion orders Gao, Peichao Gao, Yifan Zhang, Xiaodan Ye, Sijing Song, Changqing Sci Rep Article Land resources are fundamentally important to human society, and their transition from one macroscopic state to another is a vital driving force of environment and climate change locally and globally. Thus, many efforts have been devoted to the simulations of land changes. Among all spatially explicit simulation models, CLUMondo is the only one that simulates land changes by incorporating the multifunctionality of a land system and allows the establishment of many-to-many demand–supply relationships. In this study, we first investigated the source code of CLUMondo, providing a complete, detailed mechanism of this model. We found that the featured function of CLUMondo—balancing demands and supplies in a many-to-many mode—relies on a parameter called conversion order. The setting of this parameter is a manual process and requires expert knowledge, which is not feasible for users without an understanding of the whole, detailed mechanism. Therefore, the second contribution of this study is the development of an automatic method for adaptively determining conversion orders. Comparative experiments demonstrated the validity and effectiveness of the proposed automated method. We revised the source code of CLUMondo to incorporate the proposed automated method, resulting in CLUMondo-BNU v1.0. This study facilitates the application of CLUMondo and helps to exploit its full potential. Nature Publishing Group UK 2023-04-05 /pmc/articles/PMC10076298/ /pubmed/37019915 http://dx.doi.org/10.1038/s41598-023-31001-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Gao, Peichao
Gao, Yifan
Zhang, Xiaodan
Ye, Sijing
Song, Changqing
CLUMondo-BNU for simulating land system changes based on many-to-many demand–supply relationships with adaptive conversion orders
title CLUMondo-BNU for simulating land system changes based on many-to-many demand–supply relationships with adaptive conversion orders
title_full CLUMondo-BNU for simulating land system changes based on many-to-many demand–supply relationships with adaptive conversion orders
title_fullStr CLUMondo-BNU for simulating land system changes based on many-to-many demand–supply relationships with adaptive conversion orders
title_full_unstemmed CLUMondo-BNU for simulating land system changes based on many-to-many demand–supply relationships with adaptive conversion orders
title_short CLUMondo-BNU for simulating land system changes based on many-to-many demand–supply relationships with adaptive conversion orders
title_sort clumondo-bnu for simulating land system changes based on many-to-many demand–supply relationships with adaptive conversion orders
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076298/
https://www.ncbi.nlm.nih.gov/pubmed/37019915
http://dx.doi.org/10.1038/s41598-023-31001-3
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