Future Land Use Simulation Model Research Articles

Simulating Urban Agglomeration Expansion in Henan Province, China: An Analysis of Driving Mechanisms Using the FLUS Model with Considerations for Urban Interactions and Ecological Constraints

Urban expansion is influenced by complex and variable social, economic, natural, and policy-related factors. Given their nonlinear interactions, accurately modeling these urban expansion processes poses a challenge. While most studies treat the city as an independent entity, prioritizing internal urban factors, urban land expansion is influenced by intercity interactions and the ecological environment. This study proposes a new approach that couples the gravitational field model, ecological constraints, and the Future Land Use Simulation (FLUS) model, comprehensively considering the impact of intercity interaction and the ecological environment. The experiment in Henan Province in China assessed the effects of factors such as basic spatial variables (Slope and distance to the city center), urban gravitational field, and ecological constraints on urban expansion through the optimal parameters-based geographical detector (OPGD) model. The feasibility of the method was confirmed by this case study, which shows that it improves the simulation accuracy of the urban agglomeration scale, particularly for central cities. We identified the urban gravitational field and ecological constraints as two important factors affecting the expansion of urban agglomerations. Areas with stronger urban spatial fields are more likely to attract neighboring resources and promote urban expansion, whereas ecological factors constrain the expansion behavior of cities under the condition of ecological and environmental resource protection needs, and both of them work together to influence the expansion behavior of urban clusters. Therefore, we posit that intercity interactions and ecological constraints are important considerations for the future spatial planning of urban agglomerations and for coordinating the harmonious development of urbanization and ecological conservation.

Assessing the accuracy of sensitivity analysis: an application for a cellular automata model of Bogota’s urban wetland changes

This study analyzes the outcomes of Cellular Automata (CA) with different neighborhood sizes and spatial resolution configurations on the performance of the Future Land Use Simulation (FLUS) model. The analysis is executed using three analogic images to extract the land use/land cover in Bogota, Colombia, for three years: 1998, 2004, and 2010. The FLUS model has an Artificial Neuronal Network model, which was used for calculating the relationships between the land uses and the associated drivers and to estimate the probability of occurrence of each land use. Whenever a CA is used to model and simulate, sensitivity analysis (SA) becomes a crucial step in CA modeling to understand better the influence of parameters’ changes in the simulation outcomes. Therefore, the SA is conducted by varying the neighborhood sizes between 3 × 3, 5 × 5, and 7 × 7 for 5 and 30 meters. In addition, cross-classification maps, Area Under the Curve (AUC) of the Total Operating Characteristic, landscape metrics, the figure of merit, Fuzzy Kappa, and disagreement metrics were calculated to assess how well the model performed. High AUC values and low disagreement results show that, in general, the model performed well, and the accuracy of the outputs improves with a 3 × 3 neighborhood size and 5 meters spatial resolution. This study provides a broad assessment approach to the different methods that must be considered to evaluate the sensitivity of CA models in the simulation of urban wetlands’ spatial-temporal evolution.

Compound Optimization of Territorial Spatial Structure and Layout at the City Scale from "Production-Living-Ecological" Perspectives.

Land-use optimization, as an important resource-allocation method, can be defined as the process of allocating various activities to different geographic units. How to manage and control land expansion has become an urgent issue, leading a series of problems such as environmental damage and a sharp decrease in cultivated land, leading to unfavorable phenomena such as excessive urban expansion, occupation of cultivated land and important ecological spaces, and overheating of real estate development. Based on the land-use data of Wuhan city in 2020, a coupling MOP (Multi-Objective Programming) and FLUS (Future Land-Use Simulation) model was used to examine the national spatial structure and the optimization of the spatial layout. Our results showed that (1) in terms of quantitative optimal allocation, the ecological space and urban space increased, while the agricultural space greatly decreased under the three development scenarios. (2) In the simulation of spatial layout, the urban space mainly expanded vertically in the north-south direction. In the ecological space scenario, the ecological space occupied part of the cultivated land in the northeast of the city, resulting in a high degree of landscape fragmentation, which is not conducive to large-scale agricultural management. However, under optimal comprehensive benefit, part of the fragmented ecological space in the western part of Wuhan was transformed into an agricultural space. (3) A combination of the MOP and FLUS models could effectively determine land-use structure and address spatial layout optimization problems and can project space in the future urban resource configuration mode. This finding can provide a reference for the optimization of the spatial structure and layout of similar cities.

Land-planning management based on multiple ecosystem services and simulation in tropical forests

Forest losses can lead to severe damage to ecosystem services (ESs), especially in the tropics. Tropical forests are widespread in southwestern China, and they experience continual effects of human activities (e.g., rubber boom). However, forest simulations of land planning have not yet been systematically conducted. Based on a future land-use simulation model, here, the spatio-temporal characteristics of four ES (i.e., soil retention, water yield, carbon fixation, and habitat quality) were examined, and three scenarios (i.e., natural development, rubber development, and ecological protection) were designed and evaluated during 2000 for Xishuangbanna (XSBN), southwestern China. The results showed that: (1) from 2000 to 2020, the average values of the ESs declined by 449.1 t for soil retention, 13.4 mm for water yield, 0.1 for habitat quality, and 0.1 kg C/m2 for carbon fixation; (2) the four ESs, with the exception of water yield, had synergistic relationships, and trade-off appeared on the margins of these synergistic relationships; (3) compared with the scenarios of natural development and rubber development, the environmental protection scenario was found to have high efficiency for protecting nature reserves and reducing fragmentation; and (4) the intensity of land-use change will accelerate the decrease of ESs, and it is essential for nature reserves and areas of northern XSBN to improve their level of environmental protection. This work not only further enriches the ES research from the ecological environment and land-planning points of view, but it also provides different planning perspectives for ES and forest scenarios. This is useful in methodical approaches to forest sustainability.

Multi-Scenario Simulation of Land Use and Habitat Quality in the Guanzhong Plain Urban Agglomeration, China.

Regional habitat quality is a proxy of biodiversity. Simulating changes in land use and habitat quality in urban agglomerations is the scientific basis for promoting the optimal allocation of land resources and building ecological civilizations in urban agglomerations. Therefore, we established a research framework mainly consisting of the Future Land Use Simulation (FLUS) model with the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) model to predict the spatial and temporal distribution of habitat quality. In addition, we set three scenarios which were a natural development scenario, a cultivated land protection scenario, and an ecological protection scenario to analyze the changes of habitat quality in the Guanzhong Plain urban agglomeration in 2035. The results showed that: (1) the FLUS model had an excellent effect on the simulation of land-use change in the Guanzhong Plain urban agglomeration, with an overall accuracy of 0.952 and a kappa coefficient of 0.924. (2) From 2000 to 2035, the cultivated land area of the study area, which was mainly transferred into construction land and grassland, shrank due to the process of urbanization. (3) The habitat quality score of this region gradually decreased from 2000 to 2020, and it continued to decrease to 0.6921 in 2035 under the natural development scenario, while it increased under the other two scenarios. The low-value areas of habitat quality were mainly located in the middle of this region with Xi’an as the core, whereas the high-value areas were mainly distributed in the southern Qinling Mountains and the northern Loess Plateau. (4) Of the different scenarios, the ecological protection scenario had the highest habitat quality, while the natural development scenario had the lowest. Besides this, we also found that the cultivated protection scenario had high habitat quality, which was mainly because the rate of occupation of ecological land was controlled. The results are expected to provide a scientific basis for optimizing the spatial allocation of land resources and promoting the sustainable use of land space in other ecologically fragile urban agglomerations.

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

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.

Predicting future urban waterlogging-prone areas by coupling the maximum entropy and FLUS model

• We aim to develop a robust method for predicting future waterlogging-prone areas. • Maximum entropy algorithm and Future Land Use Simulation model were combined. • Dominant driver of waterlogging (land use change) was considered in the prediction. • A high proportion of impervious surfaces may face huge waterlogging risks in 2030. • This method could support future urban design and waterlogging risk prevention. Urban waterlogging is a severe hazard that can directly damage environmental quality and human well-being. It would be desirable for hazard mitigation planning and sustainable urban design if potential waterlogging-prone areas under dynamic land use change could be appropriately predicted. However, previous related studies did not simultaneously consider the reliability of negative samples and the future influence of fine-scale land use change. To fill the knowledge gap, this research has developed a robust method for predicting future waterlogging-prone areas by coupling the maximum entropy (MAXENT) and the Future Land Use Simulation (FLUS) model. The former can ensure that no extra sampling bias will be introduced, while the latter can accurately forecast the spatio-temporal pattern of land use. This case study has confirmed the accuracy and feasibility of this method. It was found that the proportion of impervious surfaces, population density, and proportion of green areas are key spatial drivers behind urban waterlogging issues. In addition, the future hazard potential map provided by the MAXENT and FLUS implies that a large proportion of impervious surfaces will face huge waterlogging risks. Therefore, policymakers should focus more on places with a higher probability of urban waterlogging. In summary, this research is expected to offer a practical tool for future urban design and waterlogging risk prevention.

Spatial and Temporal Variation, Simulation and Prediction of Land Use in Ecological Conservation Area of Western Beijing

Exploring land use change is crucial to planning land space scientifically in a region. Taking the ecological conservation area (ECA) in western Beijing as the study area, we employ ArcGIS 10.2, landscape pattern index and multiple mathematical statistics to explore the temporal and spatial variation of land use from 2000 to 2020. Patch-generating Land Use Simulation (PLUS), Future Land Use Simulation (FLUS) and Markov models were used to simulate and predict the current land use in 2020. The models were evaluated for accuracy, and the more accurate PLUS model was selected and used to simulate and predict the potential land use in the study area in 2030 under two management scenarios. The main findings of this research are: (1) From 2000 to 2020, the construction land increased constantly, and the area of cultivated land and grassland decreased significantly. (2) For predicting the spatial distribution of land use in the study area, the PLUS model was more accurate than the FLUS model. (3) The land-use prediction of the study area in 2030 shows that the area of grassland, forest and water is approximately equal to their corresponding value in 2020, but the construction land increased constantly by occupying the surrounding cultivated land. According to this research, the continuous decrease of cultivated land in favor of increasing construction land will cause losses to the ecological service function of the ECA, which is not beneficial to the sustainable development of the region. Relevant departments should take corresponding measures to reduce this practice and promote sustainable development, particularly in the southern and western areas of the ECA where there is less construction land.

Assessing spatiotemporal variations and predicting changes in ecosystem service values in the Guangdong–Hong Kong–Macao Greater Bay Area

ABSTRACT Rapid economic development and interference by human activities in rapid urbanization regions have caused great land use/land cover change (LUCC), which significantly affects ecosystem functions and services. It is crucial to assess the spatiotemporal evolution of ecosystem service value (ESV) in such regions, especially for the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) in China. In this study, we investigated and predicted the effect of LUCC on the ESV in the GBA from 1990 to 2030 using the latest annual 30 m LUCC database of China, the future land use simulation (FLUS) model, and ecosystem service evaluation approaches. The study period was divided into the historical period (1990–2015) and the forecast period (2015–2030). The results showed that forest and cropland were the dominant land-use types (>77% of the GBA), and the expansion of built-up land (3822.4 km2) was the clearest process during 1990–2015. The reduction of cropland and forest contributed the most to the decrease in the total ESV. Moreover, the results confirmed that the FLUS model is effective at predicting future LUCC in the GBA. The ESV was predicted to decrease to 4962.23 × 100 million yuan in the 2030s under the current development mode if regional forest and waterbody reductions are not constrained. This study provides a reference for promoting the rational use of land resources and ecological construction in the GBA and can help to promote ecological planning and environmental protection.

Land use optimization research based on FLUS model and ecosystem services–setting Jinan City as an example

Environment and development are essential components in the process of human development, and the limitation of land necessitates rational use. To cope with the impact of urban expansion on the environment, in this study, the idea of anti-planning is examined. The ecosystem service function is considered a limiting factor, and it determines 28.94% of the land in the study area as the core eco-land area, setting it as the non-construction area. At the same time, future land use status of the study area in 2025 is determined by planning restrictions and multiyear land use predictions, and finally, optimal allocation of land in the study area is determined by using the FLUS(Future Land Use Simulation) model. The simulation results show that the ecological security pattern and landscape index of the city are optimised, fragmentation of the landscape has decreased, and aggregation degree has increased.

Optimization of cultivated land pattern for achieving cultivated land system security: A case study in Heilongjiang Province, China

The change of cultivated land pattern (CLP) has a significant impact on cultivated land system security (CLSS), and is the foundation of ensuring adequate provision of cultivated land, and the premise of achieving sustainable development of the society. While there is a lack of research on the CLP optimization with the goal of achieving CLSS, particularly lacking research that taking the main grain production areas at the provincial scale as a study area. Hence, taking Heilongjiang Province in China as the study area, this paper uses the regional interpolation of ArcGIS spatial analysis and Auto-Logistics method to diagnose the common driving factors of CLSS and CLP change, and further sets up different development scenarios with the goal of CLSS to carry out the study of CLP optimization through the introduction of Future Land Use Simulation (FLUS) model. The results showed that: Firstly, the dynamic changes of paddy field, dryland and cultivated land were the most intense in the eastern Sanjiang Plain, the second in the western Songnen Plain, the weakest in the north-south axis, and the changes of paddy field and dryland were more intense in the later period (2010–2015) than in the earlier period (1995–2010); Secondly, regional interpolation in ArcGIS and Auto-Logistics method can effectively and reasonably spatialize, and diagnose the key factors (terrain and geomorphology including elevation and slope, socio-economic (distance to residential area, agricultural three wastes index) and farmland productivity potential) which affect the change of CLSS and CLP; Thirdly, the Kappa test coefficient of CLP optimization based on FLUS model is 0.898, with good simulation accuracy, meaning the combination of Auto-logistic and FLUS can achieve high-precision simulation of CLP. The simulation results that under the integrated control scenarios of food security, ecological protection and economic development, the regional food security, ecological protection and economic development are considered comprehensively, and the contradictions among the three are coordinated, which is more reasonable and conducive to the improvement of CLSS. Fourthly, the policies on controlling the growth rate of paddy fields, rationally reducing rural residential areas and decreasing agricultural three wastes should be strengthened to implement the optimal CLP and improve CLSS. The results bestow convincing insights on decision-making for the implementation of the optimal distribution of cultivated land resources and the compilation of the national land space plan, and also provide an important reference for the study area to improve CLSS by optimizing CLP.

The response and simulation of ecosystem services value to land use/land cover in an oasis, Northwest China

The oasis ecosystem is integral to the socio-economic stability and development in arid areas. This study illuminates the relationship between land use/land cover (LULC) and ecosystem services value (ESV) in Zhangye oasis from 1980 to 2015 and predicts changes in ESV in 2030. The coefficients for assessing ESV and the future land use simulation (FLUS) model for LULC simulation were modified by introducing natural geography and socio-economic data. The study found that the patterns of LULC and ESV in Zhangye oasis changed dramatically in 2000. Forest, grassland, and wetland were severely damaged due to the weak awareness of environmental protection, resulting in a significant decline in the ESV before 2000. Thanks to a number of ecological projects that have been put into practice and the improvement in climate conditions since 2000, the ESV has started to recover. The FLUS model reasonably predicted the LULC in 2015, and the kappa coefficient was 0.8991 after comparing with the actual LULC in 2015. On this basis, the land use scenario in 2030 is predicted, and the value of ecosystem services is estimated. The results show that the value of ecosystem services will continue to increase. This study can guide future land-use planning and raise public awareness of the need for ecosystem protection.

Simulation of Land Use Change and Ecosystem Service Value Dynamics under Ecological Constraints in Anhui Province, China.

Land use change has a significant impact on the structure and function of ecosystems, and the transformation of ecosystems affects the mode and efficiency of land use, which reflects a mutual interaction relationship. The prediction and simulation of future land use change can enhance the foresight of land use planning, which is of great significance to regional sustainable development. In this study, future land use changes are characterized under an ecological optimization scenario based on the grey prediction (1,1) model (GM) and a future land use simulation (FLUS) model. In addition, the ecosystem service value (ESV) of Anhui Province from 1995 to 2030 were estimated based on the revised estimation model. The results indicate the following details: (1) the FLUS model was used to simulate the land use layout of Anhui Province in 2018, where the overall accuracy of the simulation results is high, indicating that the FLUS model is applicable for simulating future land use change; (2) the spatial layout of land use types in Anhui Province is stable and the cultivated land has the highest proportion. The most significant characteristic of future land use change is that the area of cultivated land continues to decrease while the area of built-up land continues to expand; and (3) the ESV of Anhui Province is predicted to increase in the future. The regulating service is the largest ESV contributor, and water area is the land use type with the highest proportion of ESV. These findings provide reference for the formulation of sustainable development policies of the regional ecological environment.

Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method

Urban growth boundaries (UGBs) have been commonly regarded as a useful tool for controlling urban sprawl. There is a need to create models that can establish plausible UGBs for fast growing regions. Previous methods have merely focused on establishing a single UGB scenario over different time intervals, but rarely considered the influences of macro policy (e.g., future urban demand) and spatial policy (e.g., master plan) for regional planning. However, the spatial patterns of urban expansion are significantly affected by regional planning. In this paper, a CA-based method called the future land use simulation (FLUS) is applied to the delineation of UGBs. We argue that the delineation needs to integrate the top-down approach with CA for projecting complex land use changes under designed scenarios. The system dynamics model (SD) and cellular automaton model (CA) were interactively coupled in the FLUS model during the projection period. The top-down SD is used to project scenarios that relate to macro policy and socioeconomic status, and the bottom-up CA accounts for urban growth simulations under the influence of different driving factors and spatial planning policies. A morphological technology based on erosion and dilation is further proposed to generate the UGBs from the FLUS model’s simulated urban forms. The proposed UGB-FLUS model was applied to the establishment of UGBs in the Pearl River Delta region (PRD) from 2020 to 2050. The results demonstrate that the method can support urban planning by generating feasible patterns for UGBs under different planning scenarios.