Resilience Assessment of Urban Complex Giant Systems in Hubei Section of the Three Gorges Reservoir Area Based on Multi-Source Data

Li, Guiyuan; Cheng, Guo; Wu, Zhenying

doi:10.3390/su14148423

Cited by 7 publications

(10 citation statements)

References 36 publications

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“…The results show that Wuhan City has shown a distinct "urban core-urban fringe-rural hinterland" layered structure in its development over the past 20 years; (2) The geographic spatial structure of Wuhan City has evolved in a spreading circle pattern. In 2000, the area of the urban fringe was 474.351 km 2 ; in 2010, it expanded to 864.82 km 2 , and by 2020, it had increased further to 1220.104 km 2 . In contrast, the area of rural hinterland decreased from 7883.823 km 2 in 2000 to 6617.068 km 2 in 2020.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…The urban fringe continuously expanded outward and spread to the rural hinterland. The area of rural hinterland decreased from 7853.823 km 2 to 7232.925 km 2 , with an average annual dynamic degree of 0.791%. Under the rapid development of…”

Section: Dynamic Degree Analysis Of Urban Fringementioning

confidence: 99%

“…With the advancement of urbanization, the city continues to expand outward, gradually eroding rural Hinterland, the green ecological space is significantly reduced, and the contradiction between man and nature is constantly prominent [1,2]. The urban fringe, located at the junction of the urban core and rural hinterland, is a transitional area in the process of transforming the rural form into the urban form, and it is also the urban space reserve land in the Territorial Spatial Plan, which has three characteristics: fuzziness, dynamics and uncertainty.…”

Section: Introductionmentioning

confidence: 99%

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Evolution and Prediction of Urban Fringe Areas Based on Logistic–CA–Markov Models: The Case of Wuhan City

Long,

Liu,

Luo

et al. 2023

Land

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The urban fringe is the transitional area from rural form to urban form, and it is also the urban space reserve land in the Territorial Spatial Plan. However, few researchers predict its overall evolution and guide the implementation of the Territorial Spatial Plan. This study attempts to explore the dynamic evolution law of urban fringe, analyze its driving factors, predict its future development, and put forward management suggestions for the implementation of the Territorial Spatial Plan. In this paper, the land use data of Wuhan in 2000, 2010 and 2020 are applied to delimit the urban fringe area of Wuhan by means of a sliding t-test. Fifteen driving factors are selected from three dimensions, natural factors, socio-economic factors and traffic accessibility, and brought into the Logistic model to explore the driving factors of its spatial evolution. The CA–Markov model is used to predict the fringe area of Wuhan in 2035. The results show that the transformation of rural hinterland into urban fringe is obviously affected by the distance from railway stations, highways, commercial centers and urban main roads. It is predicted that the outer boundary of Wuhan’s fringe area in 2035 will be basically the same as the planned urban development boundary. In order to realize the intention of land space planning, the development and construction of the northwest of the Huangpi District, the East Lake Scenic Area, and the west side of the Jiangxia District should be restricted. From the perspective of the evolution of the fringe area, this paper puts forward some management suggestions for the implementation of the Territorial Spatial Plan and makes a beneficial attempt in theory and method to understand the development characteristics of the fringe area and promote the implementation of the Territorial Spatial Plan.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Dynamic Degree Analysis Of Urban Fringementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evolution and Prediction of Urban Fringe Areas Based on Logistic–CA–Markov Models: The Case of Wuhan City

Long,

Liu,

Luo

et al. 2023

Land

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“…In order to control and develop the Yangtze River basin, the construction of the Three Gorges Water Conservancy Project began in December 1994. Around October 2008, the offshore power station unit was put into operation, and the reservoir water level was 175 m [47]. In January 2010, the Three Gorges Project was completed and accepted after 16 years.…”

Section: Study Areamentioning

confidence: 99%

Research on the Spatiotemporal Dynamic Relationship between Human Activity Intensity and Ecosystem Service Value in the Three Gorges Reservoir Area

Li,

Wu,

Cheng

et al. 2023

Sustainability

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The Three Gorges Dam project and other human activities, including regional urbanization and industrialization, have had a substantial influence on the biological environment of the Three Gorges Reservoir Area (TGRA). They have changed the surface land use pattern, disrupted ecosystem structure and function, and influenced changes in the value of ecosystem services. The human activity intensity (HAI) assessment model, the ecosystem services value (ESV) assessment model, and the bivariate spatial autocorrelation model were used based on the spatiotemporal evolution data of towns along the Yangtze River in the TGRA in 1995, 2000, 2005, 2010, 2015, and 2020. At the same time, the spatiotemporal impact of the HAI on land use patterns was evaluated and the magnitude of the spatiotemporal influences on the ESV was investigated. The findings demonstrate the following: (1) The TGRA’s higher reaches are occupied by forested land, while the middle and lower portions are characterized by agricultural land. Land change in the reservoir region has mostly featured transitions between wooded land, agricultural land, grassland, and building land during the last 25 years. Because of differences in natural geography and administrative divisions, the intensity of human activity in the TGRA changes throughout the Yangtze River, with higher intensity in Chongqing and lower intensity in Hubei. By comparing the ESV and the HAI and validating with Moran scatter plots, it was determined that there is a negative relationship between the value of ecosystem services and the intensity of human activities. (2) The ESV rose from CNY 1017.16 × 108 in 1995 to CNY 1052.73 × 108 in 2020, suggesting that the policies of converting farmland back into forests, eliminating outdated production capacity, and developing green industries, among other ecological conservation measures, are effective. (3) In the research area, the effect coefficient of HAI on ESV ranges from −0.02 to −0.032 to −0.031. This coefficient represents the correlation between the HAI and ESV and can preliminarily judge the change in the degree of correlation between the HAI and ESV. The increase in HAI leads to a decrease in the value of ecosystem services, and there is a clear negative spatial correlation between the two. The low human activity area and low ecosystem service value area in the Chongqing section have been transformed into a high ecosystem service value area through years of returning farmland to forest and ecological management measures for sustainable development.

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“…It is a critical hurdle in ensuring the Yangtze River Basin's ecological security. It is also an essential environmental function area [29,30] on the Yangtze River Economic Belt, which is strategically vital. Because the TGRA is a geographical area formed by the Three Gorges Project, its distinct formation method, development pattern, geographical environment, and climatic conditions have resulted in a slew of urban diseases during the urbanization process, including unbalanced urban-rural development, insufficient infrastructure construction, and severe soil erosion [31].…”

Section: Study Areamentioning

confidence: 99%

Coupling Coordination Research on Disaster-Adapted Resilience of Modern Infrastructure System in the Middle and Lower Section of the Three Gorges Reservoir Area

Cheng

et al. 2022

Sustainability

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Rapid incremental urbanization in China has resulted in an incomplete modern infrastructure system and multiple point-like flaws. This is due to a lack of funding and poor scientific construction concepts and procedures. This also contributes to the infrastructure system’s low disaster-adapted resilience and insufficient coupling coordination of production-oriented and service-oriented infrastructure subsystems. Based on the “Robustness-Rapidity-Redundancy-Resourcefulness-Durability” (4R-D) frameworks, this study screens 53 indicators across three tiers of “production-oriented, service-oriented, intelligent” infrastructure subsystems to establish a modern infrastructure resilience evaluation system. We examined the overall infrastructure resilience and coupling coordination development among subsystems in the Three Gorges Reservoir Area (TGRA) from 2009 to 2020 using a coupling coordination degree model (CCDM). Grey relational analysis (GRA) was used to analyze the significant control aspects of infrastructure resilience and coupling coordination degree based on grey system theory. The findings show the following: (1) at the macro level the overall resilience, resilience of each subsystem, and coupling coordination among subsystems in the research region show an upward trend from 2009 to 2020, with the rise from 2018 to 2020 being the most significant; (2) at the micro level, from 2010 to 2013, there was no obvious spatial divergence and from 2014 to 2020, driven by the radiation of the two major urban agglomerations, the resilience and coupling coordination of Yiling and Wanzhou both show a trend of more substantial increase, while the rest of the counties have a small increase; and (3) at the meso level, seven factors have a more significant impact on the coupled and coordinated development of urban infrastructure than other indicators, including urbanization rate, average annual rainfall, the number of health technicians per 10,000 people, and the percentage of GDP in the tertiary industrial sector.

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Resilience Assessment of Urban Complex Giant Systems in Hubei Section of the Three Gorges Reservoir Area Based on Multi-Source Data

Cited by 7 publications

References 36 publications

Evolution and Prediction of Urban Fringe Areas Based on Logistic–CA–Markov Models: The Case of Wuhan City

Evolution and Prediction of Urban Fringe Areas Based on Logistic–CA–Markov Models: The Case of Wuhan City

Research on the Spatiotemporal Dynamic Relationship between Human Activity Intensity and Ecosystem Service Value in the Three Gorges Reservoir Area

Coupling Coordination Research on Disaster-Adapted Resilience of Modern Infrastructure System in the Middle and Lower Section of the Three Gorges Reservoir Area

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