Abstract

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.

Details

Title
CLUMondo-BNU for simulating land system changes based on many-to-many demand–supply relationships with adaptive conversion orders
Author
Gao, Peichao 1 ; Gao, Yifan 2 ; Zhang, Xiaodan 2 ; Ye, Sijing 1 ; Song, Changqing 1 

 Beijing Normal University, State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964); Beijing Normal University, Center for Geodata and Analysis, Faculty of Geographical Science, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964) 
 Beijing Normal University, Center for Geodata and Analysis, Faculty of Geographical Science, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964) 
Pages
5559
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2795917885
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.