Spatial Optimization Research Articles

Ecosystem Service Optimisation in the Central Plains Urban Agglomeration Based on Land Use Structure Adjustment

By using the methods of scenario analysis, model simulation, and the multi-objective spatial optimisation algorithm Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the Pareto optimal solutions for water supply, water purification (N retention), as well as carbon storage and sequestration service (carbon service) of the Central Plains Urban Agglomeration (CPUA) were sought by adjusting the land use structure. It showed that, to reach the Pareto optimal solution goal, (1) in Scenario 1 (S1), the water supply service needs to increase by 10.682 billion cubic metres, the water purification (N retention) service needs to decrease by 11,400 tons, and the carbon service need to decrease by 2.487 billion tons. In Scenario 2 (S2), the water supply service needs to increase by 8.243 billion cubic metres, the water purification (N retention) service needs to decrease by 11,000 tons, and the carbon service needs to decrease by 2.466 billion tons. In Scenario 3 (S3), the water supply service needs to increase by 4.089 billion cubic metres, the water purification (N retention) service needs to decrease by 10,800 tons, and the carbon service needs to decrease by 2.380 billion tons. (2) After land use optimisation and adjustment, the S3 ecological land structure is complete and consistent with the vision of ecological protection and urban development in the study area, which is the optimal scenario. (3) Optimising the ecosystem service supply pattern through land use structure adjustment could balance the overall ecosystem service supply pattern of the study area In regions wherein ecosystem supply is insufficient and there is a spatial mismatch between supply and demand for ecosystem services, this study can guide regional land planning and assist in the formulation of ecosystem service management policies.

Dynamic Matching and Spatial Optimization of Land Use and Resource-Environment Constraints in Typical Regions of the Yellow River Basin in China

Accurately identifying the matching relationships between territorial space evolution and the resources and environment carrying capacity will directly guide the sustainable use of territorial space. Based on the evaluation of the territorial space dynamics of the lower Yellow River, this paper evaluates the suitability of territorial space development by focusing on ecological protection, agricultural development, and urban construction. Specifically, the resources and environment carrying capacity is estimated by identifying and mediating potential conflicts in the development of territorial space. The matching relationship between the evolution of territorial space and the resources and environment carrying capacity is identified using the matching degree model. The results demonstrated that: (1) Between 2000 and 2020, the agricultural space of the lower Yellow River was relatively stable, while the ecological space was generally shrinking, and the urban space continued to increase; (2) The characteristics of suitability for the agricultural development and urban construction of the lower Yellow River are characterized by landform and land-sea differentiation. The carrying scale of resources and the environment is based on agricultural space and is increasing yearly, followed by ecological space, which is gradually decreasing, and urban space, which first increased and then decreased; (3) Between 2000 and 2020, the matching index of the ecological and agricultural space evolution and the resource and environmental carrying capacity in the lower Yellow River exhibited a downward trend, while the regional difference increased. Furthermore, the matching index of urban space and the resources and environment carrying capacity indicated an upward trend, while the regional difference decreased.

Research on the Impact of Carbon Emissions and Spatial Form of Town Construction Land: A Study of Macheng, China

In the context of low-carbon construction, reducing carbon dioxide emissions from town construction land is the key to mitigating the problems caused by global warming. The influence of spatial form on carbon emissions has been generally recognized, but its influence at the level of town construction land is less explored. Therefore, in this study, in order to investigate the relationship between the spatial form of town construction land and carbon emissions, the relationship between them was analyzed, taking Macheng town of Bengbu city as the research object, selecting spatial form elements and quantifying them, and characterizing and accounting for the carbon emissions from the town construction land by each building’s energy consumption. The study demonstrates that the spatial form elements such as building area and building storeys are important factors affecting the carbon emissions of residential land. Likewise, the building area, building shape coefficient, and floor area ratio are crucial factors impacting the carbon emissions of public lands. This research offers spatial form optimization strategies from a carbon reduction perspective by delving into the inherent relationship between spatial form and carbon emissions in town construction land. Consequently, it provides valuable scientific guidance for quantifying spatial planning and formulating carbon reduction strategies within a low-carbon framework.

Location Suitability Evaluation and Spatial Optimization of Self-Driving Camps in Xinjiang

Irregular tourism seasons and insufficient momentum in the development of new tourism modes disrupt the supply and demand balance between the development of self-driving tourism and the number of corresponding service facilities in Xinjiang. This constrains the growth of regional comprehensive benefits. This paper constructs an index system for evaluating the location suitability of self-driving camps in Xinjiang by the Delphi method; obtains DEM data, GIS data, POI data, and statistical data; and uses a combination of subjective and objective evaluation to calculate index weights. ArcGIS raster analysis and the P-median model were used to study the location suitability and spatial optimization strategies for self-driving tourism camps in Xinjiang. The results of this study are as follows: (1) An evaluation system for the suitability of self-driving camp locations in Xinjiang is constructed from the supply side and the demand side. (2) Self-driving camps in Xinjiang have a large supply capacity gap between counties and cities. (3) The overall suitability of the demand for self-driving camps in Xinjiang is low to moderate. (4) There exists a spatial imbalance in the suitability of the supply and demand for self-driving tourism camps in Xinjiang. (5) A total of 65 campsites were proposed for self-driving tours in Xinjiang considering spatial optimization. (6) Xinjiang should strengthen the matching of self-driving camps with tourism resources and traffic routes, and produce self-driving tour business maps with complete self-driving tour supporting facilities and services.

Research on Local Ecosystem Cultural Services in the Jiangnan Water Network Rural Areas: A Case Study of the Ecological Green Integration Demonstration Zone in the Yangtze River Delta, China

Ecosystem cultural services (CESs) are crucial for rural revitalization and sustainable development. As research on monitoring and mapping CESs continues to increase, there is a relative lack of research perspectives that effectively combine spatial modeling techniques with the local context of CESs in rural areas. Rural areas in China face challenges such as the encroachment of ecological service spaces and the displacement and relocation of their own cultural characteristics during the urbanization process. It is crucial to enhance our understanding of the relationship between CES characterization and rural locality. This paper established a framework for the quantitative research and spatial optimization of local CESs in rural areas. We selected the Ecological Green Integrated Development Demonstration Zone (EGIDZ) in the Yangtze River Delta as the research subject, considering its representativeness of the Jiangnan Water Network Area and the characteristics of integrated ecological development across regions. The Maxent model was utilized to integrate environmental variables with the locations of services, facilitating spatial mapping and quantitative evaluation of CESs, as well as determining the influence of each variable. Additionally, K-means clustering was employed to analyze CES combination patterns. The results indicated significant variations in mean values and spatial distribution within each CES category. The natural environment, spatial distance, and human activities factors all exhibited significant effects on shaping local CESs. Furthermore, the CES clusters were classified into three categories: CES-developed cluster, CES-developing cluster, and CES-potential cluster, accounting for 9.34%, 49.23%, and 41.44%, respectively. Based on these comprehensive findings, we provided insights into optimizing local CESs in the Jiangnan Water Network rural areas.

Study on the Spatial and Temporal Evolution Characteristics and Driving Factors of the “Production–Living–Ecological Space” in Changfeng County

The rapid development of industrialization and urbanization aggravates the tension of human–land relationships, leading to increasingly prominent contradictions and a serious imbalance in the relationship among production–living–ecological space (PLES). The study of county PLES is important for guiding the spatial development and layout optimization of national land as well as promoting the integrated development of urban and rural areas. This can be made more accurate, comprehensive, and visualized by using a land transfer matrix, a land use dynamic attitude, and a barycenter migration model. Research results have shown that the spatial type of Changfeng County was dominated by production space and living space from 2000 to 2020. The production space area decreased the most, to 16.3044 km2, and the ecological space area increased by 50.175 km2, within which the single dynamic attitude was first positive and then negative, with more drastic spatial changes and the fastest expansion rate. The transfer relationship was mainly based on the transfer of production space out and ecological space in; the longest distance and most obvious change was in the center of gravity of ecological space in the first 10 years of the study period, showing a trend toward the southeastern town of Xiatang. In addition, population, the increase in the proportion of tertiary industry structures, and policy regulation are the dominant factors in changes in the PLES in the county. This study provides a basis and support for the rational use of land resources and the balanced and coordinated development of people and land in Changfeng County, which is currently implementing unbalanced development.

Integrating wildfire resistance and environmental concerns into a sustainable forest ecosystem management approach

This research aims at presenting landscape management planning methods to help stakeholders select forest ecosystem management plans that may address concerns with wildfire risk and with the environmental impacts of clearcuts. Specifically, we develop mixed integer programming models for spatial optimization that incorporate a wildfire resistance index as well as constraints on the size of clearcut openings. The former is used to enforce a minimum level of resistance to wildfire while the latter limits the size of openings, in each period of the planning horizon. Timber volume even flow is another concern that is also taken into account. This research is applied to the Zonas de Intervenção Florestal (ZIF) de Paiva and de Entre-Douro e Sousa (ZIF_VS) which are located in northwestern Portugal.

Exploring the impact of explicit and implicit urban form on carbon emissions: Evidence from Beijing, China

Urban form (UF) is an important factor influencing carbon emissions (CE), and it is necessary to fully understand the complex relationship between different UF and CE. The study estimates CE using a grid as a unit and depicts the spatiotemporal pattern of CE in Beijing from 2000 to 2020. Then, based on the demand for sustainable urban development, UF is defined as explicit urban form (EUF) and implicit urban form (IUF), and the effects of different UF on CE are explored using stepwise panel regression models. The results show that (1) from 2000 to 2020, CE in Beijing showed a decreasing trend, with an average annual decrease of 57.09 × 104 t and a decrease rate of 38.58 %. Spatially, the CE gradually decreases from the east-south direction to the surrounding area, and the overall performance shows that the high CE area shrinks and the low CE area expands. (2) The influence of EUF on CE is robust, and the influence of IUF on CE is relatively large but vulnerable to other factors. (3) In EUF, urban patchy connectivity, and agglomeration have a suppressive effect on CE, while urban complexity and expansion have a positive effect on CE, reflecting that regular and compact cities are the direction of low-carbon city construction. (4) In IUF, population density (PD), economic agglomeration (EA), land use diversity (SHEI), and road density (RD) can effectively reduce CE, while industrial structure (IS) greatly contributes to the growth of CE, indicating that IUF significantly affects CE by influencing the daily energy consumption and utilization efficiency, thus has a greater potential for CE. The study reveals the influence of EUF and IUF on CE and provides a scientific basis for policy formulation in urban spatial optimization and low-carbon city construction.

Assessment of Urban Forest Ecological Benefit Based on the i-Tree Eco Model—A Case Study of Changchun Central City

Urban forests are one of the most ecologically significant systems in urban ecosystems. To make the layout and input–output ratio of urban forests more economically rational for sustainable strategic planning, it is necessary to assess the ecological benefits and ecosystem services of urban forests according to the local geographical characteristics of different cities and analyse their cost–benefit relationships. In this study, the i-Tree Eco model was used to assess the ecological benefits of urban forests in terms of four aspects: carbon sequestration and oxygen release, energy saving, rainwater retention, and air quality improvement. To translate them into economic benefits, using mathematical and statistical analysis, the cost–benefit relationship of urban forests with different tree and shrub proportions was analysed, and the impact range of urban forests with different layout types was compared. The research found that: (1) tree species are the main influencing factor of urban forest ecological benefits, (2) linear urban forests have a wider impact range, (3) if the proportion of trees in urban forests in the research area is adjusted to 0.36, the ecological benefits can increase by RMB 0.061 billion per year. We provide efficient and convenient research paths and tools for studying the cost–benefit relationship. By using an i-Tree Eco model, we realized the economic characteristics of urban forests. This research provides quantitative support for the balanced construction of urban ecological civilization and economic benefits. It can provide quantitative support for a balance between urban ecological development, economic development, and spatial optimization.

Understanding supply-demand mismatches in ecosystem services and interactive effects of drivers to support spatial planning in Tianjin metropolis, China

Metropolitan areas are being challenged by the disparity between growing societal needs and dwindling natural resource provision. Understanding the supply-demand mismatches of ecosystem services (ES) and their drivers is essential for landscape planning and decision-making. However, integrating such information into spatial planning remains challenging due to the complex nature of urban ecosystems and their intrinsic interactions. In this study, we first assessed and mapped the supply, demand, and mismatches of six typical ES in Tianjin, China. We then clustered numerous townships based on their corresponding spatial characteristic of ES supply-demand mismatches. We also used Random Forest regression to examine the relative importance of drivers and applied Partial Least Squares structural equation modelling to decouple their interactions. The results showed that, the distribution of ES supply and demand showed obvious spatial heterogeneity, with a common surplus of ES supply in highly natural mountainous region and an excess of demand in urban centre. Additionally, all towns were classified into four spatial clusters with homogeneous states of supply-demand mismatches, serving as basic units for spatial optimization. Moreover, the interactions between drivers affected ES supply-demand mismatches in a coupled manner, including the direct effects of the socioeconomic factor (−0.821) and landscape composition (0.234), as well as the indirect effects of the biophysical factor (0.151) and landscape configuration (0.082). Finally, we discussed the utility of analysing the spatial mismatches between ES supply and demand for integrated territorial planning and coordinated decision-making.

Optimal siting of onshore wind turbines: Local disamenities matter

The deployment of onshore wind power is an important means to mitigate climate change. However, wind turbines also produce local disamenities to residents living next to them, mainly due to noise emissions and visual effects. Our paper analyzes how the presence of local disamenities affects the socially optimal siting of onshore wind power. The analysis builds on a spatial optimization model using geographical information system (GIS) data for more than 100,000 potential sites in Germany. Our results indicate a major spatial trade-off between the goals of minimizing electricity generation costs and disamenity costs. Considering disamenity costs substantially alters – and in fact dominates – the socially optimal spatial allocation of wind power deployment. This is because in Germany a) the spatial correlation between generation costs and disamenity costs is only moderately positive, and b) disamenity costs exhibit a larger spatial heterogeneity than the generation costs. These results are robust to variations in the level and slope of the disamenity cost function that we assume for the modeling. Our findings emphasize the importance of supplementing support schemes for wind power deployment with approaches that address local disamenties, e.g., compensation payments to local residents or differentiated setback distances to settlements.

Spatial optimization of rural settlements in ecologically fragile regions: Insights from a social-ecological system

Rural areas in ecologically fragile regions face obstacles of underdeveloped social economies and poor natural conditions. Existing studies on the optimization of rural settlements in ecologically fragile areas have mainly focused on regional ecological protection and have paid inadequate attention to social-economic dimensions and their interaction with ecological dimensions. We propose an analytical framework for the spatial optimization of rural settlements from a social-ecological perspective. Using Kaitong Town, located in western Jilin Province, China, as a case study, we analysed the development capacity in different villages and evaluated ecosystem resilience. Based on different spatial combinations of rural development capacity and ecosystem resilience, we divided the study area into four zones: relocation and merger; aggregation and promotion; key development; and stabilization and improvement. Rural settlements within the relocation and merger zone were identified as requiring resettlement. Two optimization directions are suggested: one to the key development zone within an adjacent village and the other to the aggregation and promotion zone within the same administrative village. The proposed analytical framework provides a scientific basis for optimizing the layout of rural settlements in ecologically fragile regions and can play an important role in realizing the sustainable development of rural areas.

Hybrid optimal design method for magnetic field coils under magnetic shielding boundary

A novel strategy for designing uniform magnetic field and gradient magnetic field coils considering the boundary effect of magnetic shielding is proposed in this study. This strategy uses intelligent optimization algorithm to skillfully transform the complex coil design problem into the spatial optimization problem of individual population. The mirror method is combined with Green’s function to accurately calculate the magnetic field, and the target field method (TFM) is combined with the whale optimization algorithm to optimize the stream functions using adaptive ridge regression. The minimum fitness function is defined as the real-time magnetic field relative error, and the optimal ridge coefficient is continuously obtained by determining the current density coefficient. The proposed method significantly reduces the magnetic field deviation in the target area compared to the conventional TFM, with reductions ranging from 12.2% to 0.11% (Bx coil), 0.3% to 0.02% (Bz coil), 20% to 10% (dBx/dz coil) and 2.9% to 2.4% (dBz/dz coil). The strategy has been effectively validated by analytical simulations and experimental results, and is expected to be applied to the design of uniform field coils and gradient coils for ultra-high precision atomic sensors.

Development of a spatial optimization model for MSW management by hydrothermal carbonization: A case study on Dhaka

Hydrothermal carbonization (HTC) is a promising solution to cope with the large amount of municipal solid waste (MSW) produced in densely populated metropolitan areas of developing countries. But technical and logistical limitations typically necessitate optimal plant locations and a strong supply chain for MSW-based HTC plants to be economically attractive. To that end, a novel linear programming (LP)-based spatial optimization model has been developed that takes multiple critical constraints (biomass availability, hydrochar yield, market demand, costs of transporting and handling biomass and hydrochar, and land cost) into account to maximize the net profit of HTC plants. Dhaka, being a mega city, is burdened with the issue regarding disposal of large quantity of MSW. A case study was conducted based on the MSW management system of Dhaka North City Corporation (DNCC) for two schemes, a single (79.26 MWthermal) plant and a double (39.63 MWthermal) plant, in Dhaka city and its surrounding area. The model showed that the single plant scheme generated a higher profit (~18.5 million USD) than the double plant scheme (~17.7 million USD). Locations within Dhaka city near the secondary transfer stations were found to be favorable for plant establishment in both schemes. Further analysis revealed that plants' net profit is highly dependent on their optimal locations, with total transportation cost being the most significant location-sensitive element. Standardized coefficients suggest that for a single plant scheme, total transportation cost will always have a more dominant effect than land cost. This model will be able to guide the policy makers to take necessary steps for proper management of ever-growing city waste by setting up HTC facilities at optimal locations.

Coverage Maximization of WSNs in 3D Space Based on Hybrid Lion Swarm Optimization

The wireless sensor network (WSN) collects all the physical information required by the user for the target area and transmits the data to the sink or base station via multihop communication. With a limited number of nodes, it is important to reduce the overlapping area between nodes to improve coverage. However, increasing the coverage rate tends to create isolated points, which reduces the connection efficiency. Therefore, considering coverage and connection efficiency simultaneously is a challenging optimization task. In order to solve the above problems, this paper proposes a spatial configuration optimization strategy based on the hybrid lion swarm optimization (HLSO) algorithm. The proposed algorithm is experimented on a large number of benchmark graphs. The experimental results prove very competitive with and even better than different algorithms. Finally, in order to avoid isolated points in the node deployment process, the optimal deployment scheme of the nodes is found by considering both conditions of node coverage and connection efficiency at the same time.

Spatial Optimization of the Groundwater Quality Monitoring Network in the Kingdom of Bahrain

Groundwater resource development, management, and planning essentially rely on their quantitative and qualitative monitoring. The information obtained from the monitoring networks of a given groundwater resource is used as a significant indicator for the status of that resource, and management schemes are subsequently made in order to develop and utilize this resource on a sustainable basis. In this study, the performance of the existing monitoring network of the quality of groundwater in Bahrain was evaluated and was spatially optimized using the geostatistical method of kriging. The estimation variance was used as a criterium in the design process, and variance reduction was used to measure the network performance. The process resulted in an increase in the number of observation points from 15 currently monitored wells to 91 wells, with 74% of these being augmented industrial and commercial wells that were to be self-reported to internalize the cost of groundwater management in their users. It is recommended that temporal optimization procedures for the groundwater level are conducted and that monitored groundwater quality data are stored in a dedicated groundwater management information system (MIS) along with the monitored data of groundwater levels and abstraction to effectively support the process of decision making for groundwater planning and management.

Spatial accessibility analysis and location optimization of emergency shelters in Deyang

The selection and planning of the location of emergency shelters have a crucial impact on the safety of residents and cities. In this paper, based on multivariate open geographic data, the Gaussian two-step floating catchment area method, K-means clustering, and particle swarm optimization algorithm methods are utilized to carry out a spatial accessibility analysis and location optimization of emergency shelters in Deyang City, Sichuan Province, China. The study shows that: (1) Deyang City’s emergency shelters are higher than the government’s relevant standard requirements in terms of major indicators such as single building area, total area and per capita shelter area. (2) The spatial distribution of emergency shelters in the study area is uneven and unreasonable, with accessibility from the urban center outwards, exhibiting a “high-low” distribution pattern. (3) The study suggests that 10 new emergency shelters can reduce the number of accessible blind areas by 43.31%. The study recommends that the assessment and construction of emergency shelter facilities in rural areas in China and globally should be emphasized. Reliable recommendations for improvement of emergency shelter planning in Deyang city are provided in the study results.

Optimizing the Implementation Plan of Watershed Best Management Practices With Time‐Varying Effectiveness Under Stepwise Investment

AbstractOptimizing the spatial configuration of diverse best management practices (BMPs) can provide valuable decision‐making support for comprehensive watershed management. Most existing methods focus on selecting BMP types and locations but neglect their implementation time or order in management scenarios, which are often investment‐restricted. This study proposes a new simulation‐optimization framework for determining the implementation plan of BMPs by using the net present value to calculate the economic costs of BMP scenarios and the time‐varying effectiveness of BMPs to evaluate the environmental effectiveness of BMP scenarios. The proposed framework was implemented based on a Spatially Explicit Integrated Modeling System and demonstrated in an agricultural watershed case study. This case study optimized the implementation time of four erosion control BMPs in a specific spatial configuration scenario under a 5‐year stepwise investment process. The proposed method could effectively provide more feasible BMP scenarios with a lower overall investment burden with only a slight loss of environmental effectiveness. Time‐varying BMP effectiveness data should be gathered and incorporated into watershed modeling and scenario optimization to better depict the environmental improvement effects of BMPs over time. The proposed framework was sufficiently flexible to be applied to other technical implementations and extensible to more actual application cases with sufficient BMP data. Overall, this study demonstrated the basic idea of extending the spatial optimization of BMPs to a spatiotemporal level by considering stepwise investment, emphasizing the value of integrating physical geographic processes and anthropogenic influences.

Assessing multivariate effect of best management practices on non-point source pollution management using the coupled Copula-SWAT model

Best management practices (BMPs) have wide application in non-point source (NPS) pollution abatement in agricultural watersheds. Multivariate analysis of BMPs reduction effects taking their randomness and correlations into account is significant to spatial optimization of BMPs configuration. However, quantifying the correlations among high-dimensional random variables of BMPs effects is challenging and remains unexplored thoroughly. This study coupled the SWAT with the Vine Copula model to conduct multivariate analysis of BMPs reduction effects considering their randomness caused by hydro-meteorological variability along with correlations among different indicators (ammonium nitrogen, NH3-N; and total phosphorus, TP) and BMPs. The coupled model was applied to evaluate the multi-indicator effect of individual BMP and combined effect of various BMPs in the upper Boyang River basin, China. Results showed that bivariate copulas and three-dimensional vine copulas can efficaciously describe the dependence of BMPs effects. Simulation results indicate 43–100% probabilities of 45% NH3-N loads reduction, while 0–79% probabilities of 45% TP loads reduction for combined BMPs scenarios. Besides, the joint probabilities of different indicators in combined BMPs scenarios are generally lower than separate probabilities with 0–21% decrease, which is similar to individual BMP. Generally, joint probabilities using copulas can provide more accurate and factual knowledge of the risk and dependability of implementation of BMPs than univariate variables. The proposed model can conduct multivariate analysis of BMPs reduction effects and has great prospect in the future risk-based decision-making of NPS pollution management.

Spatial analysis and optimization of raingauge stations network in urban catchment using Weather Research and Forecasting model

Spatial analysis and optimization of raingauge stations network in urban catchment using Weather Research and Forecasting model