Coordinated Development Path of Cultivated Land Utilization in Henan Section of the Yellow River Basin
Abstract
:1. Introduction
2. Materials and Methods
2.1. Overview of the Research Area
2.2. Data Sources
- Spatial data
- 2.
- Statistics. From Henan Statistical Yearbook, Statistical Yearbook of various cities, Henan Provincial Water Resources Bulletin.
2.3. Research Methods
2.3.1. Research Framework
2.3.2. Ecological Vulnerability Assessment
Connotation and Calculation of Ecological Vulnerability Assessment Indicators
- Indicators of ecological sensitivity
- 2.
- Indicators of ecological resilience
- 3.
- Indicators of ecological stress
- 4.
- Standardization of evaluation indicators
- 5.
- Ecological vulnerability index calculation
- 6.
- Ecological vulnerability classification
2.3.3. Cultivated Land Resilience Diagnosis
2.3.4. Simulation of Future Land-Use Change
3. Results and Analysis
3.1. Ecological Vulnerability Analysis
3.2. Evaluation of Cultivated Land Resilience
3.3. Multi-Scenario Simulation of Future Land-Use Change
3.4. Determination of Urban Development Boundaries under Different Development Scenarios
3.5. Arable Land Zoning Protection Strategy
4. Discussion
- Conflict optimization for protection and development
- 2.
- Contribution, limitations, and future work
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Tan, Y.; Chen, H.; Lian, K.; Yu, Z. Comprehensive Evaluation of Cultivated Land Quality at County Scale: A Case Study of Shengzhou, Zhejiang Province, China. Int. J. Environ. Res. Public Health 2020, 17, 1169. [Google Scholar] [CrossRef] [PubMed]
- Yan, J.-Y.; Zhao, Y. Research Hot and Prospect of Ecologically Vulnerable Area in China in the Past Three Decades. J. Nanjing Norm. Univ. (Nat. Sci. Ed.) 2020, 43, 74–85. [Google Scholar]
- Shang, Y.-R. Vulnerability Study-The New Development of Synthetized Study on Natural Disasters. Areal Res. Dev. 2000, 19, 73–77. [Google Scholar] [CrossRef]
- Smith, K. Vulnerability. Resilience and the collapse of socieiy: A review of models and possible climatic applications. Int. J. Climatol. 1981, 1, 396. [Google Scholar] [CrossRef]
- Dow, K. Exploring differences in our common future(s): The meaning of vulnerability to global environmental change. Geoforum 1992, 23, 417–436. [Google Scholar] [CrossRef]
- Hou, K.; Tao, W.-D.; Wang, L.-M.; Li, X.-X. Study on hierarchical transformation mechanisms of regional ecological vulnera bility and its applicability. Ecol. Indic. 2020, 114, 106343. [Google Scholar] [CrossRef]
- De Lange, H.J.; Sala, S.; Vighi, M.; Faber, J.H. Ecological vulnerability in risk assessment—A review and perspectives. Sci. Total Environ. 2010, 18, 3871–3879. [Google Scholar] [CrossRef]
- Chen, Y.; Xiong, K.; Ren, X.; Cheng, C. An overview of ecological vulnerability: A bibliometric analysis based on the Web of Science database. Environ. Sci. Pollut. Res. 2022, 29, 12984–12996. [Google Scholar] [CrossRef]
- Kang, H.; Tao, W.; Chang, Y.; Zhang, Y.; Xuxiang, L.; Chen, P. A feasible method for the division of ecological vulnerability and its driving forces in Southern Shaanxi. J. Clean. Prod. 2018, 205, 619–628. [Google Scholar] [CrossRef]
- Lu, W.H.; Liu, J.S.; Cai, W.X. Analysis on the ecological vulnerability of Jilin Province based on ecological footprint. J. Arid. Land Resour. Environ. 2010, 24, 17–21. [Google Scholar] [CrossRef]
- Zhang, Q.; Wang, G.; Yuan, R. Dynamic responses of ecological vulnerability to land cover shifts over the Yellow river Basin, China. Ecol. Indic. 2022, 144, 109554. [Google Scholar] [CrossRef]
- Hu, X.; Ma, C.; Huang, P. Ecological vulnerability assessment based on AHP-PSR method and analysis of its single parameter sensitivity and spatial autocorrelation for ecological protection—A case of Weifang City, China. Ecol. Indic. 2021, 125, 107464. [Google Scholar] [CrossRef]
- Cai, X.; Li, Z.; Liang, Y. Tempo-spatial changes of ecological vulnerability in the arid area based on ordered weighted average model. Ecol. Indic. 2021, 133, 108398. [Google Scholar] [CrossRef]
- Qiu, P.-H.; Xu, S.-J.; Xie, G.-Z. Analysis on the ecological vulnerability of the western Hainan Island based on its landscape pattern and ecosystem sensitivity. Acta Ecol. Sin. 2007, 27, 1257–1264. [Google Scholar] [CrossRef]
- Jiang, Y.; Shi, B.; Su, G. Spatiotemporal analysis of ecological vulnerability in the Tibet Autonomous Region based on a pressure-state-response-management framework. Ecol. Indic. 2021, 130, 108054. [Google Scholar] [CrossRef]
- Shang, L.-Z.; Zhang, L.-S. Quantitative Evaluation of Ecological Vulnerability of Gansu Counties Based on “Cause and Effect” Indicators. Soil Water Conserv. China 2010, 6, 11–13+23. [Google Scholar] [CrossRef]
- Zhang, X.; Liu, K.; Wang, S.; Wu, T.; Li, X.; Wang, J.; Wang, D.; Zhu, H.; Tan, C.; Ji, Y. Spatiotemporal evolution of ecological vulnerability in the Yellow River Basin under ecological restoration initiatives. Ecol. Indic. 2022, 135, 108586. [Google Scholar] [CrossRef]
- Mafi-Gholami, D.; Pirasteh, S.; Ellison, J.C.; Jaafari, A. Fuzzy-based vulnerability assessment of coupled social-ecological systems to multiple environmental hazards and climate change. J. Environ. Manag. 2021, 229c, 113537. [Google Scholar] [CrossRef]
- Guo, B.; Luo, W.; Zang, W. Spatial-temporal shifts of ecological vulnerability of Karst Mountain ecosystem-impacts of global change and anthropogenic interference. Sci. Total Environ. 2020, 741, 140256. [Google Scholar] [CrossRef]
- Qin, Z.; Haili, X.; Xiao, L.; Luwei, D.; Bojie, W.; Fengqi, C.; Haiping, T. Livelihood vulnerability of pastoral households in the semiarid grasslands of northern China: Measurement and determinants. Ecol. Indic. 2022, 140, 109020. [Google Scholar] [CrossRef]
- Ippolito, A.; Sala, S.; Faber, J.; Vighi, M. Ecological vulnerability analysis: A river basin case study. Sci. Total Environ. 2009, 408, 3880–3890. [Google Scholar] [CrossRef]
- Zhang, F.; Liu, X.; Zhang, J.; Wu, R.; Ma, Q.; Chen, Y. Ecological vulnerability assessment based on multi-sources data and SD model in Yinma River Basin, China. Ecol. Model. 2017, 349, 41–50. [Google Scholar] [CrossRef]
- Lv, X.; Wang, Y.-N.; Wang, B.-Y. Some thoughts on the use and conservation of arable land from the perspective of resilience theory. China Land 2022, 4. [Google Scholar] [CrossRef]
- Guo, Y.-Y.; Luo, F.-Z.; Zhong, X.-R. Study on Urban Resilience Assessment Based on Entropy Weight-Normal Cloud Model. J. Catastrophol. 2021, 36, 168–174. [Google Scholar]
- Hou, X.; Liu, J.; Zhang, D.; Zhao, M.; Xia, C. Impact of urbanization on the eco-efficiency of cultivated land utilization: A case study on the Yangtze River Economic Belt, China. J. Clean. Prod. 2019, 238, 117916. [Google Scholar] [CrossRef]
- Su, H.; Wu, C.-F. Mechanism of cultivated land system change in black soil areas of Northeast China. Trans. Chin. Soc. Agric. Eng. 2021, 37, 243–251. [Google Scholar] [CrossRef]
- Zheng, H.; Li, Y.; Tu, H.-Y. Interlayer properties of short fiber interlayer carbon fiber/epoxy composites. Acta Mater. Compos. Sin. 2022, 39, 8. [Google Scholar] [CrossRef]
- Chen, J.-P.; Hu, X.-W.; Qian, J.-Q. Study on high temperature hot ductility of high corrosion resistance weathering steel S450EW. J. Plast. Eng. 2021, 28, 166–172. [Google Scholar] [CrossRef]
- Duan, Y.-Y.; Zhai, G.-F.; Li, W.-J. International Research Advances in Urban Resilience Measurement. Urban Plan. Int. 2019, 439, 79–85. [Google Scholar] [CrossRef]
- Zhang, Y.-H.; Xue, Y.; Xu, M.-L.; Li, F. Research on the Dynamic Prediction and Spatial-temporal Evolution of Urban Resilience. Mod. Manag. 2021, 41, 77–81. [Google Scholar] [CrossRef]
- Li, B.; Liu, Y.; Xing, H.; Meng, Y.; Yang, G.; Liu, X.; Zhao, Y. Integrating urban morphology and land surface temperature characteristics for urban functional area classification. Geo-Spat. Inf. Sci. 2022, 25, 16. [Google Scholar] [CrossRef]
- Liang, X.; Guan, Q.; Clarke, K.C.; Liu, S.; Wang, B.; Yao, Y. Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China. Comput. Environ. Urban Syst. 2021, 85, 101569. [Google Scholar] [CrossRef]
- Yang, J.; Huang, X. The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019. Earth Syst. Sci. Data 2021, 13, 3907–3925. [Google Scholar] [CrossRef]
- Liu, Y.; Liu, R.; Chen, J.M. Retrospective retrieval of long-term consistent global leaf area index (1981–2011) from combined AVHRR and MODIS data:LONG-TERM GLOBAL LEAF AREA INDEX. J. Geophys. Res. Biogeosci. 2012, 44, 1872–1884. [Google Scholar] [CrossRef]
- Zou, T.; Chang, Y.; Chen, P.; Liu, J. Spatial-temporal variations of ecological vulnerability in Jilin Province (China), 2000 to 2018. Ecol. Indic. 2021, 133, 108429. [Google Scholar] [CrossRef]
- Mary, A.B. Ecological vulnerability indicators. Ecol. Indic. 2016, 60, 329–334. [Google Scholar] [CrossRef]
- Dai, Q.; Zhu, J.; Zhang, S.; Zhu, S.; Han, D.; Lv, G. Estimation of rainfall erosivity based on WRF-derived raindrop size distributions. Hydrol. Earth Syst. Sci. 2020, 24, 5407–5422. [Google Scholar] [CrossRef]
- Zhang, X.; Wang, L.; Fu, X.; Li, H.; Xu, C. Ecological vulnerability assessment based on PSSR in Yellow River Delta. J. Clean. Prod. 2017, 167, 1106–1111. [Google Scholar] [CrossRef]
- Jiang, G.; Wang, M.; Qu, Y.; Zhou, D.; Ma, W. Towards cultivated land multifunction assessment in China: Applying the “influencing factors-functions-products-demands” integrated framework. Land Use Policy 2020, 99, 104982. [Google Scholar] [CrossRef]
- Ji, Z.; Wei, H.; Xue, D.; Liu, M.; Cai, E.; Chen, W.; Feng, X.; Li, J.; Lu, J.; Guo, Y. Trade-Off and Projecting Effects of Land Use Change on Ecosystem Services under Different Policies Scenarios: A Case Study in Central China. Int. J. Environ. Res. Public Health 2021, 18, 3552. [Google Scholar] [CrossRef]
- Chen, W.-G.; Kong, X.-B.; Liao, Y.-B. Countermeasures and Suggestions to Improve the “North-South Imbalance” in the Utilization and Protection of Arable Land Resources. China Land 2021, 12, 12–13. [Google Scholar] [CrossRef]
- Xiao, L.-Q.; Deng, Q.-Z.; Lin, Y.-Q. Study on the Synergistic Development of Arable Land Protection and Intensive Use of Construction Land in the Context of New Urbanization. Chin. J. Agric. Resour. Reg. Plan. 2021, 42, 62–71. [Google Scholar]
- Song, X.-Q.; Ouyang, Z. Multifunctional connotation of arable land and its implication for arable land conservation. Prog. Geogr. 2012, 31, 859–868. [Google Scholar] [CrossRef]
- Jiang, S.; Meng, J.; Zhu, L.; Cheng, H. Spatial-temporal pattern of land use conflict in China and its multilevel driving mechanisms. Sci. Total Environ. 2021, 801, 149697. [Google Scholar] [CrossRef] [PubMed]
- Chen, J.; Fu, H.; Chen, S.T. Multi-Scenario Simulation and Assessment of Ecosystem Service Value at the City Level from the Perspective of “Production–Living–Ecological” Spaces: A Case Study of Haikou, China. Land 2023, 12, 1021. [Google Scholar] [CrossRef]
Data Name | Data Sources | Resolution |
---|---|---|
Land-use data | China land cover dataset (https://zenodo.org/, accessed on 12 May 2023) | 30 m |
Soil data | World Soil Database of Henan Province (http://www.fao.org, accessed on 12 May 2023) | 1000 m |
DEM elevation data | Geospatial data cloud platform (http://www.gscloud.cn, accessed on 12 May 2023) | 30 m |
NPP data | MOD17A3HGF Version 6.0 products (https://lpdaac.usgs.gov, accessed on 12 May 2023) | 500 m |
NDVI data | Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences (http://www.resdc.cn, accessed on 12 May 2023) | 1000 m |
Leaf area index | Globmap leaf area index product (http://www.resdc.cn, accessed on 12 May 2023) | 1000 m |
Rainfall data | National Earth System Science Data Center. (http://gre.geodata.cn, accessed on 12 May 2023) | 1000 m |
River systems | OSM Map Platform (http://www.openstreetmap.org, accessed on 12 May 2023) | - |
Population data | Worldpop Population Dataset (https://www.worldpop.org, accessed on 12 May 2023) | - |
GDP data | China GDP Spatial Distribution Kilometer Grid Dataset (http://www.resdc.cn, accessed on 12 May 2023) | - |
Statistics panel data | Statistical Yearbook of Various Municipalities in 2020 | - |
Target Layer | Guidelines Layer | Feature Layer | Metrics Layer | Nature of Indicators | One Level Weight | Secondary Weights |
---|---|---|---|---|---|---|
Ecological vulnerability | Ecosensitivity | Terrain factor | DEM | + | 0.404 | 0.067 |
Slope | + | 0.070 | ||||
Terrain undulation | + | 0.079 | ||||
Soil erosion factor | Soil erosion index | + | 0.090 | |||
Rainfall erosion index | + | 0.098 | ||||
Ecological resilience | Vegetation factor | Vegetation cover | - | 0.278 | 0.052 | |
Leaf area index | - | 0.050 | ||||
Net primary productivity | - | 0.053 | ||||
Species abundance index | - | 0.060 | ||||
Meteorological factors | Rainfall | - | 0.063 | |||
Ecological pressure | Human activity factor | Expansion of construction land | + | 0.318 | 0.106 | |
Intensity of fertilizer pesticide use | + | 0.125 | ||||
Road construction | + | 0.086 |
Vulnerability Level | Normalized Index Values | Characteristics and Connotations |
---|---|---|
Slight vulnerability | 0–0.2 | The ecosystem is functionally stable, well-structured, and less susceptible to external disturbances. |
Mild vulnerability | 0.2–0.4 | The ecosystem function is relatively complete, showing its strong anti-interference capability to external disturbance, and ecological problems are potentially encountered. |
Moderate vulnerability | 0.4–0.6 | The ecosystem structure is relatively unstable, maintains basic ecological functions, and is sensitive to external disturbances. |
Severe vulnerability | 0.6–0.8 | The ecosystem has ecological function defects and strong sensitivity to external interference; thus, performing a considerable number of human activities is difficult. |
Extreme vulnerability | 0.8–1 | The structure of the ecosystem is extremely unstable, and the ecological functions are seriously degraded; thus, restoring the ecosystem after being damaged is difficult. |
Level 1 Indicators | Secondary Indicators | Low | Lower | Medium | Higher | High | Weight |
---|---|---|---|---|---|---|---|
Internal resilience | Topsoil texture | Sandy soil | - | Clay | Clay loam | Loam | 0.177 |
Groundwater table | >8 | 6–8 | 4–6 | 2–4 | 1–2 | 0.141 | |
slope | >25 | 15–25 | 6–15 | 2–6 | 2 | 0.178 | |
Soil water content | Serious deficiencies | Deficit area | Medium zone | Good area | Abundance zone | 0.190 | |
Effective soil thickness | <60 | - | 60–100 | - | >100 | 0.157 | |
Organic matter content | <10 | - | 10–20 | - | >20 | 0.157 | |
External resilience | Degree of agricultural mechanization | 0–0.2 | 0.2–0.4 | 0.4–0.6 | 0.6–0.8 | 0.8–1 | 0.184 |
Distance from river (km) | >1.5 | 1–1.5 | 0.5–1 | 0.2–0.5 | 0–0.2 | 0.183 | |
Ditch density (km/km2) | 0–3 | 3–5 | 5–7 | 7-9 | >9 | 0.225 | |
GDP level (10,000 CNY/km2) | >5 | 1–5 | 0.5–1 | 0.2–0.5 | 0–0.2 | 0.222 | |
Population density (person/km2) | >500 | 100–500 | 50–100 | 10–50 | 0–10 | 0.186 |
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Cheng, Y.; Li, C.; He, S.; Li, L.; Dong, L.; Wang, X. Coordinated Development Path of Cultivated Land Utilization in Henan Section of the Yellow River Basin. Land 2023, 12, 1342. https://doi.org/10.3390/land12071342
Cheng Y, Li C, He S, Li L, Dong L, Wang X. Coordinated Development Path of Cultivated Land Utilization in Henan Section of the Yellow River Basin. Land. 2023; 12(7):1342. https://doi.org/10.3390/land12071342
Chicago/Turabian StyleCheng, Yaohan, Chengxiu Li, Shuting He, Ling Li, Liangyun Dong, and Xiuli Wang. 2023. "Coordinated Development Path of Cultivated Land Utilization in Henan Section of the Yellow River Basin" Land 12, no. 7: 1342. https://doi.org/10.3390/land12071342
APA StyleCheng, Y., Li, C., He, S., Li, L., Dong, L., & Wang, X. (2023). Coordinated Development Path of Cultivated Land Utilization in Henan Section of the Yellow River Basin. Land, 12(7), 1342. https://doi.org/10.3390/land12071342