VST-PCA: A Land Use Change Simulation Model Based on Spatiotemporal Feature Extraction and Pre-Allocation Strategy
Land use/cover change (LUCC) refers to the phenomenon of changes in the Earth’s surface over time. Accurate prediction of LUCC is crucial for guiding policy formulation and resource management, contributing to the sustainable use of land, and maintaining the health of the Earth’s ecosystems. LUCC is...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/13/3/100 |
| _version_ | 1797240753265573888 |
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| author | Minghao Liu Qingxi Luo Jianxiang Wang Lingbo Sun Tingting Xu Enming Wang |
| author_facet | Minghao Liu Qingxi Luo Jianxiang Wang Lingbo Sun Tingting Xu Enming Wang |
| author_sort | Minghao Liu |
| collection | DOAJ |
| description | Land use/cover change (LUCC) refers to the phenomenon of changes in the Earth’s surface over time. Accurate prediction of LUCC is crucial for guiding policy formulation and resource management, contributing to the sustainable use of land, and maintaining the health of the Earth’s ecosystems. LUCC is a dynamic geographical process involving complex spatiotemporal dependencies. Existing LUCC simulation models suffer from insufficient spatiotemporal feature learning, and traditional cellular automaton (CA) models exhibit limitations in neighborhood effects. This study proposes a cellular automaton model based on spatiotemporal feature learning and hotspot area pre-allocation (VST-PCA). The model utilizes the video swin transformer to acquire transformation rules, enabling a more accurate capture of the spatiotemporal dependencies inherent in LUCC. Simultaneously, a pre-allocation strategy is introduced in the CA simulation to address the local constraints of neighborhood effects, thereby enhancing the simulation accuracy. Using the Chongqing metropolitan area as the study area, two traditional CA models and two deep learning-based CA models were constructed to validate the performance of the VST-PCA model. Results indicated that the proposed VST-PCA model achieved Kappa and FOM values of 0.8654 and 0.4534, respectively. Compared to other models, Kappa increased by 0.0322–0.1036, and FOM increased by 0.0513–0.1649. This study provides an accurate and effective method for LUCC simulation, offering valuable insights for future research and land management planning. |
| first_indexed | 2024-04-24T18:12:26Z |
| format | Article |
| id | doaj.art-6fb49cb2b5ea45d4adaee31523f68e56 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-04-24T18:12:26Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-6fb49cb2b5ea45d4adaee31523f68e562024-03-27T13:44:56ZengMDPI AGISPRS International Journal of Geo-Information2220-99642024-03-0113310010.3390/ijgi13030100VST-PCA: A Land Use Change Simulation Model Based on Spatiotemporal Feature Extraction and Pre-Allocation StrategyMinghao Liu0Qingxi Luo1Jianxiang Wang2Lingbo Sun3Tingting Xu4Enming Wang5College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaCollege of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaCollege of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaCollege of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaSchool of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaCollege of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaLand use/cover change (LUCC) refers to the phenomenon of changes in the Earth’s surface over time. Accurate prediction of LUCC is crucial for guiding policy formulation and resource management, contributing to the sustainable use of land, and maintaining the health of the Earth’s ecosystems. LUCC is a dynamic geographical process involving complex spatiotemporal dependencies. Existing LUCC simulation models suffer from insufficient spatiotemporal feature learning, and traditional cellular automaton (CA) models exhibit limitations in neighborhood effects. This study proposes a cellular automaton model based on spatiotemporal feature learning and hotspot area pre-allocation (VST-PCA). The model utilizes the video swin transformer to acquire transformation rules, enabling a more accurate capture of the spatiotemporal dependencies inherent in LUCC. Simultaneously, a pre-allocation strategy is introduced in the CA simulation to address the local constraints of neighborhood effects, thereby enhancing the simulation accuracy. Using the Chongqing metropolitan area as the study area, two traditional CA models and two deep learning-based CA models were constructed to validate the performance of the VST-PCA model. Results indicated that the proposed VST-PCA model achieved Kappa and FOM values of 0.8654 and 0.4534, respectively. Compared to other models, Kappa increased by 0.0322–0.1036, and FOM increased by 0.0513–0.1649. This study provides an accurate and effective method for LUCC simulation, offering valuable insights for future research and land management planning.https://www.mdpi.com/2220-9964/13/3/100land use change simulationspatiotemporal dependenceVST-PCAChongqing metropolitan area |
| spellingShingle | Minghao Liu Qingxi Luo Jianxiang Wang Lingbo Sun Tingting Xu Enming Wang VST-PCA: A Land Use Change Simulation Model Based on Spatiotemporal Feature Extraction and Pre-Allocation Strategy ISPRS International Journal of Geo-Information land use change simulation spatiotemporal dependence VST-PCA Chongqing metropolitan area |
| title | VST-PCA: A Land Use Change Simulation Model Based on Spatiotemporal Feature Extraction and Pre-Allocation Strategy |
| title_full | VST-PCA: A Land Use Change Simulation Model Based on Spatiotemporal Feature Extraction and Pre-Allocation Strategy |
| title_fullStr | VST-PCA: A Land Use Change Simulation Model Based on Spatiotemporal Feature Extraction and Pre-Allocation Strategy |
| title_full_unstemmed | VST-PCA: A Land Use Change Simulation Model Based on Spatiotemporal Feature Extraction and Pre-Allocation Strategy |
| title_short | VST-PCA: A Land Use Change Simulation Model Based on Spatiotemporal Feature Extraction and Pre-Allocation Strategy |
| title_sort | vst pca a land use change simulation model based on spatiotemporal feature extraction and pre allocation strategy |
| topic | land use change simulation spatiotemporal dependence VST-PCA Chongqing metropolitan area |
| url | https://www.mdpi.com/2220-9964/13/3/100 |
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