Modelling scenarios of land use change in northern China in the next 50 years

He, Chunyang; Li, Jinggang; Shi, Peijun; Chen, Jin; Yaozhong, Pan; Li, Xiaobing

doi:10.1007/bf02872683

Cited by 7 publications

(3 citation statements)

References 4 publications

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“…This indicates that when coupling the PLUS model simulation based on the GLC30 calibrated data and the sensitivity analysis method, selecting some of the drivers with larger contributions can achieve better land use simulation. When simulating land use in a large study area such as when He [58] studied the loss of natural habitats and endangered species caused by global urban expansion, efficiency can be improved by conducting land use simulations after the screening of driving factors. When the study area is large, the factors must meet the requirements of accessibility, spatial difference, consistency, correlation, and quantification.…”

Section: Comparison Of Driver Contributionsmentioning

confidence: 99%

Coupling the Calibrated GlobalLand30 Data and Modified PLUS Model for Multi-Scenario Land Use Simulation and Landscape Ecological Risk Assessment

Wang,

Guo,

Zhang

et al. 2023

Remote Sensing

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Rapid economic growth and urbanization have significantly changed the land use distribution and landscape ecological structure, which has a profound impact on the natural environment. A scientific grasp of the characteristics of land use distribution and its impact on landscape ecological risk is a prerequisite for sustainable urban development. This study aimed to calibrate GlobalLand30 data using the normalized difference impervious surface index (NDISI) obtained from Landsat images, thereby providing a more precise foundation for land simulation. Additionally, it sought to improve the accuracy of the patch-generating land use simulation (PLUS) through parameter sensitivity analysis. Building upon this, the research also simulates future land use in Beijing. Lastly, this study introduced an LER index to assess ecological risk in the current and future urban landscapes. The results showed that the GlobalLand30 data were calibrated and PLUS model accuracy was improved to more than 86%. The accuracy of the modified PLUS model based on a Morris sensitivity analysis was increased, and the kappa coefficients were increased by approximately 3%. The results of the multi-scenario simulation showed that under the SSP126-EP scenario, future land use in Beijing could balance urban development and ecological protection, and thus would be more suitable for sustainable development. In the other two scenarios, ecological land will be encroached by urban development. From 2000 to 2020, the degree of LER was generally lower, moderate, or higher, and the overall level of LER showed a downward trend continuing until 2100 in the SSP126-EG scenario. Future land use simulations and LER assessment under multi-scenarios could help decision makers develop multi-scale landscape protection strategies.

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Section: Comparison Of Driver Contributionsmentioning

confidence: 99%

Coupling the Calibrated GlobalLand30 Data and Modified PLUS Model for Multi-Scenario Land Use Simulation and Landscape Ecological Risk Assessment

Wang,

Guo,

Zhang

et al. 2023

Remote Sensing

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“…For spatial simulation, common models include cellular automata (CA) [7], the Conversion of Land Use and its Effects modeling framework (CLUE) [8], Future Land Use Simulation (FLUS) [9], and the Patch-generating Land Use Simulation (PLUS) Model [10]. The system dynamics (SD) model is particularly effective in representing the nonlinear, systematic, complicated, and dynamic features of the LUCC process, making it a valuable tool for simulating land use scenarios [11,12]. The FLUS model has demonstrated excellent simulation accuracy compared to classic models such as CLUE-S, ANN-CA, and Logistic-CA [9].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Simulation of Land Use and Habitat Quality Assessment in Baiyangdian Basin Using the SD-PLUS Coupled Model

Han,

Li,

Han

et al. 2024

Water

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The physical foundation and environmental assurance provided by the regional habitat are crucial for the survival and sustainable development of organisms. Land use change, as a significant manifestation of human activity, is a crucial factor in habitat quality. An SD-PLUS coupled model was developed to simulate land use change in the Baiyangdian(BYD) Basin using data on land use, socio-economic factors, and the climatic environment from 2000 to 2020. The InVEST model was employed to assess the habitat quality of the basin from 2000 to 2050. The findings indicated the following: Between 2020 and 2050, the predominant land use changes across the three scenarios involve the conversion of farmland to construction land and grassland to woodland. The magnitude of these changes steadily declines over time. The magnitude of change in land use for all kinds was greater under SSP5 compared to SSP1 and SSP2. The movement of habitat quality grades primarily occurred from higher grades to lower grades. In 2050, the habitat quality is projected to improve compared to 2020 under three different scenarios. The highest improvement is expected in SSP5 with a 0.60% increase, followed by SSP2 with a 0.42% increase and SSP1 with the smallest increase of 0.23%.

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“…The SD method is based on cybernetics, system theory and information theory, which its main characteristic is its ability to reflect the interactions between structures and behaviors of complex dynamic systems, real dynamic simulation, and estimating the behaviors of the system under different scenarios (Sterman, 2000). A great deal of research work has shown that the SD method can be used in many areas, including agricultural systems (Saysel et al, 2002;Teimoury et al, 2013), environmental management (Turner et al, 2013;Mashayekhi, 1990), ecological modeling (Kopainsky, 2015;Wu et al, 1993), water resource planning (Aivazidou et al, 2015;Niazi et al, 2014), and can be regarded as a useful tool for scenario analysis in the land use researches (He et al, 2005;Rasmussen et al, 2012;Liu et al, 2013). Despite numerous studies in recent years in the field of agricultural land use change modeling using system dynamics technique (Shi and Gill, 2005;Luo et al, 2010;Rozman et al, 2013), but there is still research gaps on SD models using macro socio-economic driving factors in an open economy and at national level to predict the future agricultural land use change and assess the effects of improvement policies.…”

Section: Introductionmentioning

confidence: 99%

System Dynamics Modeling for National Agricultural System With Policy Recommendations: Application to Iran

Mesgari¹

2017

PAKJAS

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Using system dynamics (SD) approach, this paper develops a simulation model to study the behaviors and relationships within the agricultural system at national level and analysis the future scenarios. The proposed model considers three major sub-systems: demand side (population and income), supply side (land use, water resources, and productivity), and regulatory side (barriers, incentives, and support). Iranian agricultural system is modeled using this approach and the future conditions are simulated under three if-then scenarios up to 2040. The results show that under the policies as current conditions, the demand for the agricultural products will rapidly increase due to the population growth and economic development. However, agricultural land use and domestic supply does not experience much growth because of crucial limitations in the climatic conditions, available water resources, and rather low productivity; therefore, the gap will be compensated through an ever increasing import. The suggested SD model helps policy makers to identify the bottleneck points in the system based on simulation results and then, improvement policies can be made according to these bottlenecks. Some improvement policies for supply side have been proposed and effectiveness of them on increase in production and agricultural land use development has been demonstrated. By improving supply side policies alone, the Iranian government's goal of agricultural self-sufficiency is not likely to be achieved and it is essential to improve the demand side policies in this regard. The suggested model has proven to be useful for Iranian agricultural system, and its methodology could be used as a decision support tool for land use planning, policy making and managements of agricultural sector.

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Modelling scenarios of land use change in northern China in the next 50 years

Cited by 7 publications

References 4 publications

Coupling the Calibrated GlobalLand30 Data and Modified PLUS Model for Multi-Scenario Land Use Simulation and Landscape Ecological Risk Assessment

Coupling the Calibrated GlobalLand30 Data and Modified PLUS Model for Multi-Scenario Land Use Simulation and Landscape Ecological Risk Assessment

Dynamic Simulation of Land Use and Habitat Quality Assessment in Baiyangdian Basin Using the SD-PLUS Coupled Model

System Dynamics Modeling for National Agricultural System With Policy Recommendations: Application to Iran

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