Understanding Spatio-Temporal Patterns of Land Use/Land Cover Change under Urbanization in Wuhan, China, 2000–2019

Zhai, Han; Lv, Chaoqun; Liu, Wanzeng; Yang, Chao; Fan, Dasheng; Wang, Zikun; Guan, Qingfeng

doi:10.3390/rs13163331

Cited by 108 publications

(63 citation statements)

References 46 publications

(59 reference statements)

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“…Wuhan's urban space shows a trend of radiating and expanding from the central urban area to the surrounding areas (Figure 10), especially in the south and northeast of Wuhan, which is closely related to Wuhan's policies to accelerate the construction of the Yangtze River Economic Belt and is in line with the urban space development trend of "one master and four deputies". Moreover, He et al (2017) and Zhai et al (2021) found that when simulating the urban spatial expansion of Wuhan, it mainly concentrated in the edges of the Hanyang and Hongshan Districts [49,50], which is consistent with the findings of this study. In addition, the UDB of Wuhan is lower than the expansion scale of the built-up area predicted by Liang et al (2021) and Wang et al (2021) [51,52].…”

Section: Comparison With Existing Researchsupporting

confidence: 90%

“…How to achieve the rational, orderly, and sustainable development of cities has always been a hot topic in China's urbanization research. Moreover, the rational delineation of the urban development boundary as an effective means to control the disorderly expansion and restrict the healthy development of cities has attracted attention from scholars [49,50]. In this context, a series of mathematical models for the urban development boundary have emerged [12,51,52].…”

Section: Strength and Limitationsmentioning

confidence: 99%

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A New Perspective for Urban Development Boundary Delineation Based on the MCR Model and CA-Markov Model

Yong

2022

Land

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In order to control the development of urban space, it is important to explore scientific methods to provide a reference for regional territorial space planning. On the basis of the minimum cumulative resistance (MCR) model and the cellular automaton (CA)-Markov model, we constructed a new technical method for delineating urban development boundaries, exploring the temporal and spatial distribution characteristic of land use in Wuhan from 2010 to 2020 through nighttime and remote sensing images, and simulating the urban development boundaries of Wuhan from 2025 to 2035. The results show that: (1) the scales of Wuhan City’s built-up areas in 2010, 2015, and 2020 were 500 km2, 566.13 km2, and 885.11 km2, respectively, and the trends of expansion run to the east and southeast, and (2) on the basis of the MCR model, the urban development boundary scale of Wuhan City in 2025, 2030, and 2035 from the perspective of actual supply will be 903.52 km2, 937.48 km2, and 1021.44 km2, respectively, and based on the CA-Markov model, the urban development boundary scales of Wuhan City in 2025, 2030, and 2035 from the perspective of ideal land demand will be 912.75 km2, 946.40 km2, and 1041.91 km2, respectively. By combining the results of the two methods, we determined areas of 901.62 km2, 944.39 km2, and 1015.36 km2 as the urban development boundaries of Wuhan City in 2025, 2030, and 2035, respectively. According to the principle of supply–demand balance, the urban development boundary delineated by the integration of the MCR model and CA-Markov model, which is in line with the spatial expansion trend of growing cities, could optimize the urban development pattern; solve the contradiction between urban development, farmland protection, and ecological protection; and provide a methodological reference and decision-making basis for planning practice.

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Section: Comparison With Existing Researchsupporting

confidence: 90%

Section: Strength and Limitationsmentioning

confidence: 99%

A New Perspective for Urban Development Boundary Delineation Based on the MCR Model and CA-Markov Model

Yong

2022

Land

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“…Then, using the CARS module, simulate the land-use pattern in 2030 based on the ecological restoration scenario. Previous research has demonstrated that the PLUS model can simulate multiple types of land-use change at the patch level with more precision and a more realistic landscape pattern [ 22 , 60 ]. Thus, using the PLUS model for land-use simulation in this study is highly suitable.…”

Section: Discussionmentioning

confidence: 99%

Integrating the Ecological Security Pattern and the PLUS Model to Assess the Effects of Regional Ecological Restoration: A Case Study of Hefei City, Anhui Province

Cao

Liu

et al. 2022

IJERPH

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Most studies in the field of ecological restoration have only focused on repairing damaged land and have made no attempt to account for the impact of high-intensity land use on future landscape patterns. The purpose of this study was to propose a framework for evaluating the expected effects of ecological restoration based on land-use change and the ecological security pattern. Therefore, we integrated the PLUS model with the ecological security pattern and used Hefei City as a case study to conduct research. The results showed that from 2020 to 2030, land-use changes would occur primarily in the main urban area of Hefei and along the eastern shore of the Chaohu Lake watershed. Under the ecological protection scenario, arable land would be converted to construction land and woodland. Additionally, there would be an increase in ecological sources and pinch points in the area, and the number and area of the barriers would show a certain degree of reduction. The ecosystem quality, ecological integrity, and landscape connectivity of Hefei would be improved. This study offers a novel perspective for evaluating the expected effects of regional ecological restoration and provides an important reference for the dynamic formulation of multilevel ecological restoration policies.

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“…For example, one land use simulation using a Markov-CA model in the rapid urbanizing areas in Central Iran has a Kappa coefficient of 0.82 [ 53 ]. Another two examples are the land use change simulation in the whole of Wuhan using the FLUS model, which has an overall accuracy of 0.75 [ 54 ], and the land use simulation using the LCM model in the Greater Accra Metropolitan Area, which has a kappa coefficient of 0.76 [ 55 ]. Moreover, our simulation can reflect the land use changes inside the Wuhan city with a relatively high spatial resolution.…”

Section: Discussionmentioning

confidence: 99%

Land Use Change Simulation in Rapid Urbanizing Regions: A Case Study of Wuhan Urban Areas

Zhang

Hou

Dong

et al. 2022

IJERPH

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Until now, few studies have used the mainstreaming models to simulate the land use changes in the cities of rapid urbanizing regions. Therefore, we aimed to develop a methodology to simulate the land use changes in rapid urbanizing regions that could reveal the land use change trend in the cities of the regions. Taking the urban areas of Wuhan, a typical rapid urbanizing region in China, as the study area, this study built a Markov chain–artificial neural network (ANN)–cellular automaton (CA) coupled model. The model used land use classification spatial data with a spatial resolution of 5 m in 2010 and 2020, obtained by remote sensing image interpretation, and data on natural and socio-economic driving forces for land use change simulation. Using the coupled model, the land use patterns of Wuhan urban areas in 2020 were simulated, which were validated in comparison with the actual land use data in 2020. Finally, the model was used to simulate the land uses in the study area in 2030. The model validation indicates that the land use change simulation has a high accuracy of 90.7% and a high kappa coefficient of 0.87. The simulated land uses of the urban areas of Wuhan show that artificial surfaces will continue to expand, with an area increase of approximately 7% from 2020 to 2030. Moreover, the area of urban green spaces will also increase by approximately 7%, while that of water bodies, grassland, cropland, and forests will decrease by 12.6%, 13.6%, 34.9%, and 1.3%, respectively, from 2020 to 2030. This study provides a method of simulating the land use changes in the cities of rapid urbanizing regions and helps to reveal the patterns and driving mechanisms of land use change in Wuhan urban areas.

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Understanding Spatio-Temporal Patterns of Land Use/Land Cover Change under Urbanization in Wuhan, China, 2000–2019

Cited by 108 publications

References 46 publications

A New Perspective for Urban Development Boundary Delineation Based on the MCR Model and CA-Markov Model

A New Perspective for Urban Development Boundary Delineation Based on the MCR Model and CA-Markov Model

Integrating the Ecological Security Pattern and the PLUS Model to Assess the Effects of Regional Ecological Restoration: A Case Study of Hefei City, Anhui Province

Land Use Change Simulation in Rapid Urbanizing Regions: A Case Study of Wuhan Urban Areas

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