Interoperable scenario simulation of land-use policy for Beijing–Tianjin–Hebei region, China

Liu, Dongya; Zheng, Xinqi; Wang, Hongbin; Zhang, Chunxiao; Li, Jiayang; Lv, Yongqiang

doi:10.1016/j.landusepol.2018.03.040

Cited by 36 publications

(16 citation statements)

References 33 publications

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“…In the generated SD model, four major issues are considered: population, economy, climate, and land use. The population is regarded as the most important factor affecting the increase in built-up areas (D. Liu et al 2018). It, also, influences production and agricultural land, through the increase in demand for food provision.…”

Section: Land-use Demand and Sd Modelmentioning

confidence: 99%

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Exploring an integrated spatially model for land-use scenarios simulation in a metropolitan region

Dadashpoor

Panahi

2021

Environ Dev Sustain

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Spatial simulation of land-use change scenarios in metropolitan areas is essential for analyzing both the causes and consequences of various future scenarios and is also valuable for land-use planning and management. However, current simulation models primarily focus on spatial and rarely on quantitative driving factors. This article aims to simulate future scenarios of land-use changes in the Tehran metropolitan region (TMR) by combining different models to fill this gap. Thus, in the first step, land-use changes were analyzed in the period 1985, 2000, and 2015. Then, by identifying the impact of driving factors and land-use transition potentials with Logistic regression (LR), land-use changes were allocated using the Cellular Automata (CA) method. Finally, with the validation of the model, four scenarios of the current trend(CT), socioeconomic growth(SEG), ecologicaloriented(EO), and integrated development(ID) were suggested with the combination of the System Dynamic (SD) model. The results show that the trend of land-use changes in TMR has led to the destruction of grassland, agricultural, and uncultivated lands and the continuation of this trend will increase the damage of built-up areas on valuable natural and ecological resources. In this way, proximity to roads, distance from built-up areas, and natural factors had the greatest impact on changes. Based on future scenarios in 2030, the change in the SEG-scenario shows a rapid increase in built-up areas (2858km 2) and encroachment on agricultural lands (2171km 2) . In the EO-scenario, destruction of grassland and agricultural lands and the growth of built-up areas will be limited, while CT-scenario leads to the high growth of built-up areas along with destructive impacts on natural and open spaces. In the ID-scenario, the built-up areas and grasslands will increase to 2808km 2 and 7438km 2 , respectively. Accordingly, policy-makers can use simulation of different scenarios to mitigate probable consequences of land-use changes in the metropolitan regions.

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Section: Land-use Demand and Sd Modelmentioning

confidence: 99%

“…In the land-use modeling process, spatial issues are simulated by combining LR and CA, but for quantifying the demand of each land use in the scenarios, the SD model is applied (Liu et al 2018). Over time, land-use demand is used from the SD model as an input of the CA-LR model for simulating land-use patterns.…”

Section: Sd and Ca_lr Modelsmentioning

confidence: 99%

Exploring an integrated spatially model for land-use scenarios simulation in a metropolitan region

Dadashpoor

Panahi

2021

Environ Dev Sustain

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“…In October 2015, the Chinese government put forward the development concept of "innovation, coordination, green development, opening up, and sharing," clearly aiming to shape the new patterns of regional coordinated development. Beijing, Tianjin, and Hebei have been required to plan industrial land as a whole, and control sprawling of urban-industrial land [15]. It is of great significance to explore urban-industrial land efficiency.…”

Section: Introductionmentioning

confidence: 99%

Coupling Coordination Relationships between Urban-industrial Land Use Efficiency and Accessibility of Highway Networks: Evidence from Beijing-Tianjin-Hebei Urban Agglomeration, China

Gao

et al. 2019

Sustainability

100

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The implementation of the Beijing, Tianjin, and Hebei coordinated development strategy has seriously increased the influence of land use and urban traffic. Thus, understanding the coordination between urban land and transportation systems is important for the efficient and sustainable development of cities, especially in this rapidly urbanizing era. Urban–industrial land and highway networks are, respectively, primary types of urban land and transportation systems, and have significant impacts on social and economic development. However, limited studies have been conducted to examine the relationships between urban–industrial land and highway networks. Therefore, this paper aims to examine the coupling coordination relationship between urban–industrial land use efficiency, and the accessibility of the highway networks of cities. Specifically, in the context of the Beijing–Tianjin–Hebei (BTH) urban agglomeration, the coupling coordination between urban-industrial land use efficiency and accessibility of the highway traffic network was empirically analyzed. The results show that: (i) The differences in urban-industrial land use efficiency in the BTH region are significant. Capital cities in the BTH urban agglomeration have higher economic, social, and comprehensive efficiency, while in industrial cities, the use of urban–industrial land should prioritize ecological and environmental issues. (ii) Because of its good geographical location Beijing has the best accessibility, with an accessibility index of 1.416, while Qinhuangdao had the lowest accessibility index of 0.039. (iii) In most BTH cities, the urban-industrial comprehensive land use level has fallen behind the highway network development level. The results of this study can provide references for the coordinated development of the BTH urban agglomeration.

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“…(i) Conversion of Land Use and its Effects at Small Region Extent (CLUE-S) model based on empirical statistics, (ii) Agent-Based Model (ABM) based on multiple agents, (iii) Cellular Automata (CA) model based on neighborhood relationship analysis, and (iv) Dynamics of Land System (DLS) model based on structural changes in land systems and succession of spatial pattern analysis. In various case studies, ecosystem services trade-offs are often simulated by changes of land use/cover types to provide evidence for sustainable development of ecosystems (Grafius et al, 2016;Liu et al, 2018;Wu, 2013). For example, Jra et al (2013) assessed trade-offs and synergies between water quality regulation and 10 other ecosystem services in the Australian Great Barrier Reef considering four different land use scenarios.…”

Section: Introductionmentioning

confidence: 99%

Simulating the impact of Grain-for-Green Programme on ecosystem services trade-offs in Northwestern Yunnan, China

et al. 2019

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One of the main manifestations of the Grain-for-Green Programme (GFGP) is land use change, which will affect the trade-off of ecosystem services. Since the implementation of the GFGP in Dali Autonomous Prefecture in 2000, land use/cover has undergone dramatic changes. This study used the CLUES model to simulate land use change in 2030, and explored the spatial pattern and relationship of different ecosystem services under the four scenarios of GFGP. The results show that, GFGP can help to improve indirect services of ecosystems, such as carbon storage and soil conservation. However, direct services of the ecosystem will decline, such as food production and water yield. Compared with 2010, the overall supply level of the four ecosystem services is the most balanced in the moderate GFGP scenario. In this

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Interoperable scenario simulation of land-use policy for Beijing–Tianjin–Hebei region, China

Cited by 36 publications

References 33 publications

Exploring an integrated spatially model for land-use scenarios simulation in a metropolitan region

Exploring an integrated spatially model for land-use scenarios simulation in a metropolitan region

Coupling Coordination Relationships between Urban-industrial Land Use Efficiency and Accessibility of Highway Networks: Evidence from Beijing-Tianjin-Hebei Urban Agglomeration, China

Simulating the impact of Grain-for-Green Programme on ecosystem services trade-offs in Northwestern Yunnan, China

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