Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model
Nowadays, cities meet numerous sustainable development challenges in facing growing urban populations and expanding urban areas. The monitoring and simulation of land use and land-cover change have become essential tools for understanding and managing urbanization. This paper interprets and predicts...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/11/5/652 |
| _version_ | 1797498535992623104 |
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| author | Linfeng Xu Xuan Liu De Tong Zhixin Liu Lirong Yin Wenfeng Zheng |
| author_facet | Linfeng Xu Xuan Liu De Tong Zhixin Liu Lirong Yin Wenfeng Zheng |
| author_sort | Linfeng Xu |
| collection | DOAJ |
| description | Nowadays, cities meet numerous sustainable development challenges in facing growing urban populations and expanding urban areas. The monitoring and simulation of land use and land-cover change have become essential tools for understanding and managing urbanization. This paper interprets and predicts the expansion of seven different land use types in the study area, using the PLUS model, which combines the Land use Expansion Analysis Strategy (LEAS) and the CA model, based on the multi-class random patch seed (CARS) model. By choosing a variety of driving factors, the PLUS model simulates urban expansion in the metropolitan area of Hangzhou. The accuracy of the simulation, manifested as the kappa coefficient of urban land, increased to more than 84%, and the kappa coefficient of other land use types was more than 90%. To a certain extent, the PLUS model used in this study solves the CA model’s deficiencies in conversion rule mining strategy and landscape dynamic change simulation strategy. The results show that various types of land use changes obtained using this method have a high degree of accuracy and can be used to simulate urban expansion, especially over short periods. |
| first_indexed | 2024-03-10T03:34:43Z |
| format | Article |
| id | doaj.art-64f33f7d77504a2d934bc61d2004c777 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-10T03:34:43Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-64f33f7d77504a2d934bc61d2004c7772023-11-23T11:46:53ZengMDPI AGLand2073-445X2022-04-0111565210.3390/land11050652Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS ModelLinfeng Xu0Xuan Liu1De Tong2Zhixin Liu3Lirong Yin4Wenfeng Zheng5School of Life Science, Shaoxing University, Shaoxing 312000, ChinaSchool of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu 610054, ChinaLaboratory for Urban Future, Peking University Shenzhen Graduate School, Shenzhen 518055, ChinaSchool of Life Science, Shaoxing University, Shaoxing 312000, ChinaDepartment of Geography and Anthropology, Louisiana State University, Baton Rouge, LA 70803, USASchool of Automation, University of Electronic Science and Technology of China, Chengdu 610054, ChinaNowadays, cities meet numerous sustainable development challenges in facing growing urban populations and expanding urban areas. The monitoring and simulation of land use and land-cover change have become essential tools for understanding and managing urbanization. This paper interprets and predicts the expansion of seven different land use types in the study area, using the PLUS model, which combines the Land use Expansion Analysis Strategy (LEAS) and the CA model, based on the multi-class random patch seed (CARS) model. By choosing a variety of driving factors, the PLUS model simulates urban expansion in the metropolitan area of Hangzhou. The accuracy of the simulation, manifested as the kappa coefficient of urban land, increased to more than 84%, and the kappa coefficient of other land use types was more than 90%. To a certain extent, the PLUS model used in this study solves the CA model’s deficiencies in conversion rule mining strategy and landscape dynamic change simulation strategy. The results show that various types of land use changes obtained using this method have a high degree of accuracy and can be used to simulate urban expansion, especially over short periods.https://www.mdpi.com/2073-445X/11/5/652urban expansionLEASCARSland use interpretationChina |
| spellingShingle | Linfeng Xu Xuan Liu De Tong Zhixin Liu Lirong Yin Wenfeng Zheng Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model Land urban expansion LEAS CARS land use interpretation China |
| title | Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model |
| title_full | Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model |
| title_fullStr | Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model |
| title_full_unstemmed | Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model |
| title_short | Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model |
| title_sort | forecasting urban land use change based on cellular automata and the plus model |
| topic | urban expansion LEAS CARS land use interpretation China |
| url | https://www.mdpi.com/2073-445X/11/5/652 |
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