Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020
Amid persistent global food security challenges, the efficient utilization of cultivated land resources has become increasingly critical, as optimizing Cultivated Land Utilization Efficiency (CLUE) is paramount to ensuring food supply. This study introduced a cultivated land utilization index (CLUI)...
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2024-12-01
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| author | Henggang Zhang Chenhui Zhu Tianyu Jiao Kaiyue Luo Xu Ma Mingyu Wang |
| author_facet | Henggang Zhang Chenhui Zhu Tianyu Jiao Kaiyue Luo Xu Ma Mingyu Wang |
| author_sort | Henggang Zhang |
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| description | Amid persistent global food security challenges, the efficient utilization of cultivated land resources has become increasingly critical, as optimizing Cultivated Land Utilization Efficiency (CLUE) is paramount to ensuring food supply. This study introduced a cultivated land utilization index (CLUI) based on Fractional Vegetation Cover (FVC) to assess the spatiotemporal variations in Henan Province’s CLUE. The Theil–Sen slope and the Mann–Kendall test were used to analyze the spatiotemporal variations of CLUE in Henan Province from 2000 to 2020. Additionally, we used a genetic algorithm optimized Artificial Neural Network (ANN) and a particle swarm optimization-based Random Forest (RF) model to assess the comprehensive in-fluence between topography, climate, and human activities on CLUE, in which incorporating Shapley Additive Explanations (SHAP) values. The results reveal the following: (1) From 2000 to 2020, the CLUE in Henan province showed an overall upward trend, with strong spatial heterogeneity across various regions: the central and eastern areas generally showed decline, the northern region remained stable with slight increases, the western region saw significant growth, while the southern area exhibited complex fluctuations. (2) Natural and economic factors had notable impacts on CLUE in Henan province. Among these factors, population and economic factors played a dominant role, whereas average temperature exerted an inhibitory effect on CLUE in most parts of the province. (3) The influenced factors on CLUE varied spatially, with human activity impacts being more concentrated, while topographical and climatic influences were relatively dispersed. These findings provide a scientific basis for land management and agricultural policy formulation in major grain-producing areas, offering valuable insights into enhancing regional CLUE and promoting sustainable agricultural development. |
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| spelling | doaj-art-32efd3ca2bac496d97663c164ca1837b2025-08-20T02:53:34ZengMDPI AGLand2073-445X2024-12-011312210910.3390/land13122109Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020Henggang Zhang0Chenhui Zhu1Tianyu Jiao2Kaiyue Luo3Xu Ma4Mingyu Wang5College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, ChinaCollege of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, ChinaCollege of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, ChinaCollege of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, ChinaCollege of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, ChinaCollege of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, ChinaAmid persistent global food security challenges, the efficient utilization of cultivated land resources has become increasingly critical, as optimizing Cultivated Land Utilization Efficiency (CLUE) is paramount to ensuring food supply. This study introduced a cultivated land utilization index (CLUI) based on Fractional Vegetation Cover (FVC) to assess the spatiotemporal variations in Henan Province’s CLUE. The Theil–Sen slope and the Mann–Kendall test were used to analyze the spatiotemporal variations of CLUE in Henan Province from 2000 to 2020. Additionally, we used a genetic algorithm optimized Artificial Neural Network (ANN) and a particle swarm optimization-based Random Forest (RF) model to assess the comprehensive in-fluence between topography, climate, and human activities on CLUE, in which incorporating Shapley Additive Explanations (SHAP) values. The results reveal the following: (1) From 2000 to 2020, the CLUE in Henan province showed an overall upward trend, with strong spatial heterogeneity across various regions: the central and eastern areas generally showed decline, the northern region remained stable with slight increases, the western region saw significant growth, while the southern area exhibited complex fluctuations. (2) Natural and economic factors had notable impacts on CLUE in Henan province. Among these factors, population and economic factors played a dominant role, whereas average temperature exerted an inhibitory effect on CLUE in most parts of the province. (3) The influenced factors on CLUE varied spatially, with human activity impacts being more concentrated, while topographical and climatic influences were relatively dispersed. These findings provide a scientific basis for land management and agricultural policy formulation in major grain-producing areas, offering valuable insights into enhancing regional CLUE and promoting sustainable agricultural development.https://www.mdpi.com/2073-445X/13/12/2109cultivated land utilization efficiencyspatiotemporal evolutionmachine learningtrend analysisdriving factors |
| spellingShingle | Henggang Zhang Chenhui Zhu Tianyu Jiao Kaiyue Luo Xu Ma Mingyu Wang Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020 Land cultivated land utilization efficiency spatiotemporal evolution machine learning trend analysis driving factors |
| title | Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020 |
| title_full | Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020 |
| title_fullStr | Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020 |
| title_full_unstemmed | Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020 |
| title_short | Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020 |
| title_sort | analysis of the trends and driving factors of cultivated land utilization efficiency in henan province from 2000 to 2020 |
| topic | cultivated land utilization efficiency spatiotemporal evolution machine learning trend analysis driving factors |
| url | https://www.mdpi.com/2073-445X/13/12/2109 |
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