Multiple scenarios-based on a hybrid economy–environment–ecology model for land-use structural and spatial optimization under uncertainty: a case study in Wuhan, China

Ma, Yuxiang; Wang, Mengcheng; Zhou, Min; Tu, Jiating; Ma, Cong; Li, Siqi

doi:10.1007/s00477-022-02176-4

Cited by 11 publications

(6 citation statements)

References 67 publications

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“…The difference between the expected demand and the actual space allocated in the study area was calculated using the adaptive inertia coefficient. On that basis, site-specific development trends that contradicted the expected demand were automatically adjusted and thus corrected in the next iteration [34,35,67]. The formula is as follows:…”

Section: 14 X For Peer Reviewmentioning

confidence: 99%

“…Through application to landuse simulations [20][21][22] and urban expansion simulation and urban growth boundary delineation [31][32][33], it has been shown that, at this stage, among the subsequent improvements of multiple cellular automata, the FLUS model integrates a top-down system dynamics model and a bottom-up cellular automata, and establishes adaptive inertia and competition mechanisms to deal with the complex competition and interactions between different land-use types [31], which can better capture the uncertainty and stochasticity of development in the study area. Among the current studies using the FLUS model, Jiang [5], Penny [34] and Ma et al [35] used the FLUS model to study land use and spatial patterns considering natural, economic and cultural factors. Xu [36], Mansour [37] and Ye et al [38] mainly conducted simulations and monitoring in the urban context using the FLUS model.…”

Section: Introductionmentioning

confidence: 99%

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Spatial Simulation of Land-Use Development of Feixi County, China, Based on Optimized Productive–Living–Ecological Functions

et al. 2022

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Rural revitalization places higher demands on the productive–living–ecological (P-L-E) spaces of towns and cities. It is necessary, therefore, to identify, evaluate, and optimize P-L-E spaces to better guide spatial planning. Existing studies typically evaluate a single space, lacking a comprehensive consideration of whole-area integration. This study, therefore, developed a coupled spatial/developmental suitability evaluation system for Feixi County, Anhui Province, China, combining spatial quality evaluation, a coupled coordination model, and future land-use simulation (FLUS) model. The spatial quality of Feixi County in 2010, 2015, and 2020 was obtained by applying the evaluation system to the spatial development pattern. The results were analyzed and verified using the landscape pattern index and development suitability evaluation. The results showed the following: (1) The coupling coordination degree of the region increased from 0.131 to 0.372, changing from low to moderate coordination. (2) Based on the FLUS model to better capture the uncertainty and stochastic basis of the development in the study area. The kappa coefficient and Figure of Merit (FoM) index of the land-use simulation accuracy verification index were 0.7647 and 0.0508, respectively, and the logistic regression ROC values were above 0.75, thus meeting accuracy requirements. This demonstrated that the simulation model—based on a factor library of the evaluation of resource and environmental carrying capacity and suitability for development and construction—could better reflect future land-use changes. (3) The simulation showed that under the baseline development scenario, the area’s spatial layout is too concentrated in terms of construction land, ignoring P-L-E coordination. Under the ecological optimization scenario, high-quality ecological space is ensured, but other types of spaces are lacking. Under the comprehensive guidance scenario, lagging ecological space is optimized and P-L-E spatial development is enhanced through aggregation, clustering, concentration and integration. This way, the spatial quantity structure and distribution form can meet P-L-E spatial development needs in Feixi County. In this study, on the basis of scientific assessment of the current P-L-E space, the FLUS model was applied to carry out a scenario simulation according to different objectives. Moreover, based on the construction of the coupling system of human–nature system, the driving factors were improved to enhance the prediction accuracy of the FLUS model. This study’s findings can help improve the scientificity, flexibility and management efficiency of Feixi County’s P-L-E spatial layout, thereby supporting its sustainable development.

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Section: 14 X For Peer Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial Simulation of Land-Use Development of Feixi County, China, Based on Optimized Productive–Living–Ecological Functions

et al. 2022

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“…For example, Cheng et al [30] optimized the spatial structure of mountain-abandoned-mine land reuse by combining system dynamics and the CLUE-S model. Ma et al [31] combined an uncertain mathematical model with the FLUS model to solve the problem of the planning system with uncertainty of the land system and applied it to structural and spatial patterns. The coupled model balances macro policy effects and micro driving mechanisms, so it is widely used in the research of land-use optimization [32,33].…”

Section: Introductionmentioning

confidence: 99%

Land-Use Optimization Based on Ecosystem Service Value: A Case Study of Urban Agglomeration around Poyang Lake, China

et al. 2022

Sustainability

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The optimal allocation of land use is a promising approach to achieving the sustainable use of land resources, to weigh ecological protection and economic development. The urban agglomeration around Poyang Lake is a crucial plate for implementing the spatial planning policy of the national urban agglomeration and supporting the development of the Yangtze River Economic Belt. Based on the ecosystem service value (ESV), we utilize the minimum cumulative resistance (MCR), the gray multi-objective planning (GMOP) and the future land-use simulation (FLUS) model to optimize the quantitative structure and spatial pattern of the land use in 2030. The present study designs four scenarios of baseline development (BD), ecological conservation (EC), economic priority (EP) and coordinated development (CD) to discuss how to optimize land-use allocation while considering ecological security and economic development. The result suggests that the land-use structure and spatial layout in the CD_scenario are relatively reasonable, and the overall eco-economic benefits and landscape pattern levels are better than those of the other three scenarios. Additionally, the ecological security and landscape pattern indices are optimized, landscape fragmentation decreases and aggregation degree increases. This study is instructive to promote the sustainable development of urban agglomeration and land spatial planning.

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“…Tang et al [ 21 ] used CA-Markov and CLUE-S models to predict land use in Changli County, China, in 2028 and to predict the spatial and temporal changes in habitat quality and future development trends constrained by land use in order to provide a scientific basis for regional natural environmental protection and land use planning. Ma et al [ 22 ] used an uncertainty model coupled with a spatial allocation model (GeoSOS-FLUS) to optimize for three different land use scenarios in Wuhan, China, and quantified the inherent uncertainty of land use to determine its optimal spatial distributions. These models were based mainly on historical land use conversion patterns in making predictions and were not capable of optimizing land use patterns for user-specified conditions.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Spatial Land Use Patterns with Low Carbon Target: A Case Study of Sanmenxia, China

Chen

Wang

2022

IJERPH

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Land use change is an important factor in atmospheric carbon emissions. Most of the existing studies focus on modeling the land use pattern for a certain period of time in the future and calculating and analyzing carbon emissions. However, few studies have optimized the spatial pattern of land use from the perspective of the impact of carbon emission constraints on land use structure. Therefore, in this study, the effects of land use change on carbon emissions from 1990 to 2020 were modeled using a carbon flow model for Sanmenxia, Henan, China, as an example. Then, the land use carbon emission function under the low carbon target was constructed, and the differential evolution (DE) algorithm was used to obtain the optimized land use quantity structure. Finally, the PLUS model was used to predict the optimal spatial configuration of land use patterns to minimize carbon emissions. The study produced three major results. (1) From 1990 to 2020, the structural change of land use in Sanmenxia mainly occurred between cultivated land, forest land, grassland and construction land. During this period of land use change, the carbon emissions from construction land first increased and then decreased, but despite the decrease, carbon emissions still exceeded carbon sinks, and the carbon metabolism of land use was still far from equilibrium. (2) Between 2010 and 2020, the area of cultivated land began to decrease, and the area of forest land rapidly increased, and land-use-related carbon emissions showed negative growth. This showed that the structural adjustment of energy consumption in Sanmenxia during the period decreased carbon emissions in comparison with the previous period. (3) A comparison of predicted optimized land use patterns with land use patterns in an as-is development scenario showed a decrease in construction land area of 23.05 km2 in 2030 with a steady increase in forest land area and a decrease in total carbon emission of 20.43 t. The newly converted construction land in the optimized land use pattern was concentrated in the ribbon-clustered towns built during urban expansion along the Shaanling basin of the Yellow River and the Mianchi–Yima industrial development area.

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Multiple scenarios-based on a hybrid economy–environment–ecology model for land-use structural and spatial optimization under uncertainty: a case study in Wuhan, China

Cited by 11 publications

References 67 publications

Spatial Simulation of Land-Use Development of Feixi County, China, Based on Optimized Productive–Living–Ecological Functions

Spatial Simulation of Land-Use Development of Feixi County, China, Based on Optimized Productive–Living–Ecological Functions

Land-Use Optimization Based on Ecosystem Service Value: A Case Study of Urban Agglomeration around Poyang Lake, China

Optimization of Spatial Land Use Patterns with Low Carbon Target: A Case Study of Sanmenxia, China

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