Future Land Use Simulation Research Articles

Impact of land use change on regional carbon sink capacity: Evidence from Sanmenxia, China

Regional carbon sink fluctuations are largely influenced by land use. To enhance regional carbon sink and inform sustainable land management practices, it is critical to elucidate the influence of land use changes on carbon sink dynamics. Employing historical data on carbon sink in Sanmenxia region, this study analyzed alterations in land use and carbon sink between 2000 and 2020. The Future Land Use Simulation (FLUS) model was used to predict the impacts of land use type changes on regional carbon sink under three development scenarios (urban priority, cultivated land priority, and ecological priority).The result shows that:(1) From 2000 to 2020, cultivated land (with an increase of 3.26%) and construction land (with an increase of 22.85%) showed the most significant changes, with the main source of increase being grassland, while other land types showed little change. The southern part of the study area was mainly forest land and grassland, with higher carbon sink value than the northern part. (2) The simulation study of the three scenarios found that the development scenarios of ecological priority and cultivated land priority would be conducive to improving regional carbon sink value by 2040. Specifically, regional cropland, forest, and grassland were preserved due to the ecological red line and the restriction of basic farmland. This would increase the carbon sink value of the study area by 145 thousand tons and 171 thousand tons, respectively, compared with 2020. (3) The prediction results of the three development scenarios all showed that the carbon sink of the study area would decline first and then increase from 2020 to 2040. The carbon sink of the urban priority scenario would reach the lowest value in 2030, and the other development scenarios would reach the lowest value around 2028, and then increase significantly.

Potential impact of future land use/cover dynamics on the habitat quality of the Yayo Coffee Forest Biosphere Reserve, southwestern Ethiopia

Human activities, including agricultural expansion, urbanization, and industrial advancement, have led to land use/cover change (LULCC). These changes have had negative consequences, such as the loss of species and the degradation of forest areas. The Yayo Coffee Forest Biosphere Reserve (YCFBR) is undergoing changes due to forest fires and encroachment from coffee plantations, which are predicted to increase in the future. The objective of this study was to simulate the dynamics of LULCC and its impact on habitat quality in the area over the next three decades. The study used classified land cover (LC) maps of 1992, 2022, and 2052 (predicted), as well as factor and constraint maps of the area. In addition, household surveys, key informant interviews (KII), and focus group discussions (FGD) were conducted to understand the factors influencing changes in habitat quality. Habitat quality was simulated under three different future scenarios (Business as Usual; S1), conservation scenario (S2), and development scenario (S3) using CA-Markov, Future Land Use Simulation (FLUS), and Integrated Valuation of Environmental Services Tradeoffs (InVEST) models. The result showed a 28% increase in open forest and a 35% increase in agricultural area under S1, with a minimal increase in built-up area. The medium-level habitat quality increased from 11.3% in 1992 to 27.8% in 2052 S3. The highest average haitat quality value was 0.62 in S2, while the lowest was 0.51 in S3. If S3 is the case, this value is expected to fall below 40%, indicating the lowest possible level of habitat quality in the future. The model also predicts a 7% increase in high forest areas in S2, indicating the possibility of an alternative path to save high forest loss in the area. The main causes of habitat quality deterioration include population growth, agricultural land expansion, a lack of diverse incomes, land tenure issues, and settlement expansion. Based on the findings, S2 appears to be the best future scenario for maintaining habitat quality. This study provides useful information that will help planners and decision-makers effectively prepare future conservation strategies.

Evaluating the impact of simulated land use changes under multiple scenarios on ecosystem services in Ji'an, China

Ecosystem services (ES) play a crucial role in the sustainable development of human society. It is essential to clarify the impact of land use changes on ES to facilitate sound land spatial planning. This study focuses on the Ji'an area of Jiangxi Province as the research subject. The Future Land Use Simulation (FLUS) model is employed under the 'Production-life-ecological space' (PLES) policy scenario to simulate land use changes in the Ji'an area from 2020 to 2040. A comprehensive evaluation index for ecosystem services (CES) is constructed based on existing policies and ecological conditions in Ji'an City. It is then integrated into the FLUS-InVEST framework to simulate various development scenarios in the future. The results reveal that under the living space priority (LSP) scenario, construction land exhibits the highest growth rate, reaching 59.8%. Under the ecological space priority (ESP) scenario, the forest area is projected to increase by 0.54%. Only under the Productive Space Priority (PSP) scenario will cultivated land experience an increase, at a rate of 3.69%. Notably, CES remains relatively stable only in the ESP scenario, while declining in all other scenarios (ranging from 1.19% to 1.83%). Based on the simulation calculations, a Comprehensive Development (CD) plan for Ji'an is proposed, aiming to optimize the coordination among production, living, and ecological spaces and facilitate the restoration of ecosystem services. Compared to the 'business as usual' (BAU) scenario, the CES value of the CD scenario is expected to increase by 0.61%. In summary, this paper presents an exploratory study that combines the FLUS-InVEST framework with the unique development scenario of the Ji'an region in an innovative way. The proposed planning and recommendations for future sustainable development contribute to a deeper understanding of the impact of socio-economic activities on the ecological environment.

Data-Driven Projections Demonstrate Non-Farming Use of Cropland in Non-Major Grain-Producing Areas: A Case Study of Shaanxi Province, China

The non-farming use of cropland has led to food insecurity in China due to drastic land use (LU) changes under the stresses of ecological restoration and urbanization, particularly in non-major grain-producing areas. Questions were raised about spatiotemporal cropland losses/gains and their drivers in these areas in the future for sustainable development of the agriculture sector. However, the answers to these questions have not been well acknowledged. This study, therefore, presents analyses of cropland area change from 1990 to 2018 and from 2018 to 2051 in Shaanxi province based on the Future Land Use Simulation (FLUS) model that follows the integration of the Shared Socioeconomic Pathway 2 and the Representative Concentration Pathway 4.5 (SSP245) within the International Coupled Model Intercomparison Project 6 (CMIP6). The results highlight that ecological restoration and fast-paced urbanization mainly drove the alarming non-farming use of cropland. The per capita cropland area is projected to increase, but the cropland loss will still occur, which potentially causes food insecurity. Thus, food security will be a challenging issue in the near future. The quantitative findings call for careful designs of LU policies, taking into account cropland protection, socio-economic development, and ecological restoration.

Impact of Land Use Change on Carbon Storage Based on FLUS-InVEST Model: A Case Study of Chengdu–Chongqing Urban Agglomeration, China

Land use change is one of the main factors driving changes in terrestrial carbon storage, which comprises the storage of vegetation carbon and soil carbon. Selecting the Chengdu–Chongqing urban agglomeration (CCUA) as the study area, land use and carbon storage from 2010 to 2030 were analyzed by combining the Future Land Use Simulation (FLUS) model and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The main types of land use in CCUA are farmland and forest. The conversion of farmland to built-up land was the most important form of land use transfer between 2010 and 2020. Each type of land use shows the smallest change under the ecological protection scenario, and the degree of the comprehensive land use dynamic is only 0.19%. Under the natural development scenario, the areas of built-up land, wetland, and forest land will increase in 2030. Under the urban development scenario, the built-up land area will increase by 751.24 km2, an increase in more than 10.08%, but farmland, forest, and grassland will decrease. The spatial pattern of carbon storage is “high in the east and west, low in the middle”; farmland accounts for the largest proportion of carbon storage at over 60% of the total. Carbon storage decreased by 29.45 × 106 Mg from 2010 to 2020. Grassland showed the most significant decrease in carbon storage, with the proportion decreasing from 7.49% in 2010 to 6.09% in 2020. In 2030, the total carbon storage will reach 1844.68 × 106 Mg under the ecological protection scenario, slightly higher than that in 2020, while it will show a downward trend under the natural development and urban development scenarios.

Coupled MOP and PLUS-SA Model Research on Land Use Scenario Simulations in Zhengzhou Metropolitan Area, Central China

Land use simulations are critical in predicting the impact of land use change (LUC) on the Earth. Various assumptions and policies influence land use structure and are a key factor in decisions made by policymakers. Meanwhile, the spatial autocorrelation effect between land use types has rarely been considered in existing land use spatial simulation models, and the simulation accuracy needs to be further improved. Thus, in this study, the driving mechanisms of LUC are analyzed. The quantity demand and spatial distribution of land use are predicted under natural development (ND), economic development (ED), ecological protection (EP), and sustainability development (SD) scenarios in Zhengzhou based on the coupled Multi-Objective Programming (MOP) model and the Patch-generating Land Use Simulation model (PLUS) considering Spatial Autocorrelation (PLUS-SA). We conclude the following. (1) The land use type in Zhengzhou was mainly cultivated land, and 83.85% of the land for urban expansion was cultivated land from 2000 to 2020. The reduction in forest from 2010 to 2020 was less than that from 2000 to 2010 due to the implementation of the policy in which farmland is transformed back into forests. (2) The accuracy of PLUS-SA was better than that of the traditional PLUS and Future Land Use Simulation (FLUS) models, and its Kappa coefficient, overall accuracy, and FOM were 0.91, 0.95, and 0.29, respectively. (3) Natural factors (temperature, precipitation, and DEM) contributed significantly to the expansion of cultivated land, and the increase in forest, grass, and construction land was greatly affected by socioeconomic factors (population, GDP, and proximity to town). (4) The land use structure will be more in line with the current requirements for sustainable urban development in the SD scenario, and the economic and ecological benefits will increase by 0.75 × 104 billion CNY and 1.71 billion CNY, respectively, in 2035 compared with those in 2020. The PLUS-SA model we proposed had higher simulation accuracy in Zhengzhou Compared with the traditional PLUS and FLUS models, and our research framework can provide a basis for decision-makers to formulate sustainable land use development policies to achieve high-quality and sustainable urban development.

Maintaining key ecosystem services under multiple development scenarios: A case study in Guangdong–Hong Kong–Macao greater bay Area, China

Effective land use management can better maintain ecosystem services, especially in urban agglomerations. However, rational urban scale systems and landscape patterns to maintain key ecosystem services (ESs) in highly urbanized areas remain poorly understood. Taking the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a study area, we quantified the spatio-temporal change of key ESs from 2000 to 2020 by the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) model, and simulated land use change prior considering ES conservation priority areas under different multiple development scenarios in 2050 by adopting the future land use simulation (FLUS) model. The main findings were as follows: (1) From 2000 to 2020, natural habitat, water retention and carbon sequestration decreased by 5.5%, 7.9%, and 3.9%, respectively, while the soil conservation increased by 63.7%. (2) The proportion of different conservation priority areas ranged from 10.6% to 22.6%, which were mainly located in the mountainous region. (3) The urban land area would increase from 4286.00 km2 to 4802.25 km2 between 2020 and 2050 in the GBA, with a growth rate of 12.05%. Under the simulation scenarios, the new urban land was mainly distributed in megacities and supercities. (4) Under the integrative conservation scenario, the habitat quality index, water conservation, soil conservation and carbon sequestration would increase by 0.036, 7 × 104 t, 5.11 × 106 t and 0.93 × 106 t, respectively. To maintain the key ESs, we recommend optimizing the urban scale system, making it compact at the city scale and scattered at the regional scale, and strictly restricting the conversion of forestland and farmland adjacent to megacities into urban land. These findings were beneficial to achieve regional high-quality development and sustainable development via rational urban system and landscape management.

Assessing current and future soil erosion under changing land use based on InVEST and FLUS models in the Yihe River Basin, North China

The Yihe River Basin is a key area for water conservation and soil erosion control in northern China. The excessive development of land resources is a major factor causing soil erosion and ecological degradation. However, the impacts of land use change on soil erosion in the basin are not yet clearly. Understanding the complex relationship between land use and soil erosion is an important way to promote the development of land resources utilization and ecological construction from cognition to decision-making. This study simulated the temporal-spatial changes of soil erosion in the basin from 1956 to 2020 using Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, and evaluated the changes of soil erosion under different land use scenarios from 2020 to 2050 using Future Land Use Simulation (FLUS) model. From 1956 to 2020, the overall soil erosion intensity showed a slight decreasing trend, and the average annual soil erosion modulus was 38.21 t/ha/year. Soil erosion intensity was higher in the central and northern mountainous areas, while it was lower in the flat alluvial plains in the south. Arable land (4.07 t/ha/year) was the largest contributor to the amount of soil erosion, and land use changes caused the soil erosion intensity to fluctuate and decrease after 1995. From 2020 to 2050, soil erosion varied widely under different land use scenarios, and the land use pattern targeting ecological priority development would effectively mitigate soil erosion. Therefore, optimizing land use patterns and structures are critical initiatives to prevent soil erosion.

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.

An integrated model chain for future flood risk prediction under land-use changes

Flood is a very destructive natural disaster in the world that is strongly influenced by land-use change. Therefore, a comprehensive flood risk modeling considering the change in land-use is essential for understanding, predicting, and mitigating flood risk. However, most existing single modeling ignored the derivative effect of land-use change, which may reduce the reality of results. To further address the issue, this study presented an integrated model chain by coupling the Markov-FLUS model, the multiple linear regression and the improved TOPSIS model. By applying it in Guangdong Province, the future land-use simulation, spatialization of hazard-bearing bodies, and determination of flood risk were realized. The results show that the coupled model chain allows for good prediction of flood risk under different scenarios, which could be expressed by flood risk composite index (FRSI). In the natural growth scenario, the flood risk will show markedly increasing trend from 2020 to 2030 (FRSI = 2.06), with the high and highest risk zones will expand significantly. Spatially, these increased high flood risk zones mainly distributed on the periphery of existing built-up lands. On the contrary, the flood risk in ecological protection scenario tends to stabilize (FRSI = 1.98), which may be a reference for alternative development paths. These dynamic information identified by this model chain provides a deeper insight into the spatiotemporal characteristics of future high flood risk areas, which can facilitate reasonable flood mitigation measures to be developed at the most critical locations in the region. In further applications, more efficient spatialization models and climate factor are suggested to be introduced.

Exploring the impact of integrated spatial function zones on land use dynamics and ecosystem services tradeoffs based on a future land use simulation (FLUS) model

Spatial function zones (SFZs) provide an effective means to determine the function of spatial zone and to optimize land use layout. China has initiated a series of spatial planning policies to delineate SFZs, which influence not only land use configuration but also the structure and function of ecosystems as well as the services ecosystem provides. Taking Wuhan city, China as an example, this study explored the impact of integrated spatial function zones (ISFZs) on four selected ecosystem services (i.e., crop production, CP; water yield, WY; carbon storage, CS; and erosion prevention, EP) and their synergies and tradeoffs. Specifically, by incorporating different spatial functional zones into the land use simulation model, we simulated land use under both business as usual (BAU) and integrated spatial function zones (ISFZs) scenarios. Then, we assessed and compared the ESs and their correlations under the two scenarios. The results showed that compared to the BAU scenario, in the ISFZs scenario, quantities of farmland and forests would be increased by 410.99 km2 and 28.49 km2, while construction land would be decreased by 342.45 km2; average CP, CS and EP would be improved by 0.05, 2.23 t/ha, and 7.3 t/ha, while average WY would be reduced by 6.4 mm; synergies between most pairs of ESs would be slightly promoted. It is concluded that ISFZs are beneficial to sustainable improvement and balanced development of multiple ESs. This study provides theoretical and technical references for the formulation of spatial regulation policy and ecosystem-based management.

Scenario-based urban growth simulation by incorporating ecological-agricultural-urban suitability into a Future Land Use Simulation model

China's rapid urbanization has imposed a considerable strain on land resources and infrastructure, resulting in environmental deterioration, food shortage, traffic congestion, and various other challenges. The urban growth boundary (UGB) is regarded as an important policy instrument for managing and curbing urban sprawl. Previous studies on UGB have focused on the quantity and spatial constraints of built-up land concerning natural resources conservation. However, achieving a balance between urban conservation and development by easing the conflict between land functions is not yet well understood. To bridge this gap, combining “bottom-up” local spatial simulation with “top-down” regulation and human constraint, this study simulated multi-scenario urban expansion and UGB in Jiangsu Province, China in 2035 using ecological-agricultural-urban suitability assessment and a Future Land Use Simulation (FLUS) model. The results show that the maintenance of different land functions will have a significant impact on the number, spatial distribution, and landscape characteristics of UGB. Under the integrated development scenario, UGB will have the largest area (27,893.33 km2) with the most significant agglomeration characteristics. The delineated UGB, coupling ecological-agricultural-urban suitability, will reflect regional heterogeneous resource endowment and can further alleviate conflicts between multiple objectives. For fairness and equality between cities, future urban expansion should emphasize the development of less-developed areas. This study expands a new insight for simulating urban expansion and offers practical recommendations for orderly urban growth and sustainable urban management in other cities.

Assessing and simulating changes in ecosystem service value based on land use/cover change in coastal cities: A case study of Shanghai, China

The rapid economic development of coastal cities causes frequent land use/cover change (LUCC), which has a significant negative impact on the functions and services of coastal ecosystems. In this paper, we considered Shanghai, China, as the study area and assessed its ecosystem service value (ESV) using the equivalence coefficient table method based on land use data from 2000, 2010 and 2020. Multi-scenario simulations of LUCC and ESV in 2030 were carried out by establishing a future land use simulation (FLUS) model. The results showed that from 2000 to 2020, the most obvious features of LUCC in Shanghai included an increase in built-up land (an increase of 1388.09 km2) and a decrease in cultivated land (a decrease of 1355.85 km2). Wetland, woodland and grassland maintained a steady growth trend. During these two decades, the ESV in Shanghai decreased from 322.8417 million yuan to 311.8970 million yuan. In terms of the spatial distribution of LUCC and ESV, coastal areas had the most frequent occurrence of LUCC and contributed the most to the ESV. The multi-scenario simulation results showed that there was a significant improvement in the ESV of the ecological priority scenario (2.01% and 4.06% higher than the benchmark scenario and development priority scenario, respectively). In addition, several policy recommendations for the development and utilization of land in coastal cities are proposed, and the significant contribution of coastal areas to the ecological benefits of coastal cities is empirically demonstrated. These results can provide a theoretical basis and decision support for sustainable land management in coastal cities.

Construction of ecological security pattern adapting to future land use change in Pearl River Delta, China

Land use and cover change (LUCC) can often threaten urban ecological space and cause enormous impacts on the ecosystem, and sustainable ecological security patterns (ESPs) should receive more attention in urban landscape planning to adapt to future environmental changes. Thus, this research explored a multi-scenario framework of ESP by coupling the Future Land Use Simulation (FLUS) and Minimum Cumulative Resistance (MCR) models for long-term sustainable ecological security in the Pearl River Delta (PRD), China. The results show that areas of ecological sources in 2030 under the natural development scenario (NDS), economic development scenario (EDS), food security scenario (FSS), and ecological priority scenario (EPS) will account for 11.58%, 3.71%, 10.55%, and 16.50% of the total area, respectively. 45 ecological corridors under NDS, EDS, FSS, and EPS will be 8573.07 km, 7970.54 km, 9197.15 km, and 7769.24 km, respectively. The future corridors, that will be annularly in the periphery of economic development zones, can better balance economic development and ecological protection. Under the EPS scenario, the constructed ESP will have the best network structure and can effectively protect ecological land and reduce damage. This work provides a valuable reference for ecosystem conservation and land resource management under the rapid urbanization process.

Optimization of spatial layout based on ESV-FLUS model from the perspective of “Production-Living-Ecological”: A case study of Wuhan City

As the ecological problems deteriorated through the progress of modernization, exploring the optimization strategy from the ecological perspective is of great significance. Ecosystem Services (ESs) bridge the ecological and social systems, and planning geographical spatial patterns with consideration of reliable Ecosystem Service Value (ESV) assessment can improve land use efficiency and harmonize the human-environment relationship. This study aims to explore the spatial layout optimization strategy under the "Production-Living-Ecological" (PLE) space perspective. Taking Wuhan as the study area, we constructed ecological scenarios according to the synergies and trade-offs mechanism among different ecosystem services, and further combined the scenario restraints with economy, population, traffic, and environment factors to simulate the future geographical spatial layout of Wuhan. The methods of Ecosystem Service Value (ESV) assessment, Future Land-Use Simulation (FLUS) model, GIS technologies and scenario analysis were applied in this study. In this study, we evaluated the ESV of Wuhan and then established a natural growth scenario and two ecological scenarios to simulate the spatial layout of Wuhan in 2035. Meanwhile, we evaluated the carbon emissions to further examine the contributions of our ecological scenarios. The results showed that: (1) From 2010 to 2018, the spatial layout transformation of Wuhan was primarily from ecological to production space, and the high ESV area was mainly in the East Lake District. (2) Without effective consideration for ecological constraints, the living and production space in Wuhan will expand excessively in 2035. (3) The regulation-provision scenario had the highest ecosystem service value and the smallest carbon emissions. In conclusion, introducing ecosystem services into the FLUS model impact factor system is conducive to improving the ecological benefits of China's spatial pattern under scenario simulations.

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.

Simulating the impact of land use change on ecosystem services in agricultural production areas with multiple scenarios considering ecosystem service richness

Agricultural land is a complex seminatural and semiartificial ecosystem that is affected by both human activities and natural factors. Clarifying land use and ecological health conflicts in agricultural areas is important for maintaining ecosystem services. Thus, taking the Henan section of the Yellow River (HSYR) as the study area, this study constructed an ecosystem service index (ESI) assessment model to explore the impact of land use change on ecosystem services from 1980 to 2020. Then, the future land use simulation (FLUS) model was used to simulate the effects of different development patterns on ecosystem services heterogeneity in 2035. The results showed that, from 1980 to 2000, the ESI increased from 0.520 to 0.649, but then decreased to 0.509 by the end of 2020 in the HSYR. In any simulation scenarios, urban land expansion continued to encroach on cropland, resulting in the loss of ecosystem services. Especially in the natural development scenario (ND), the ESI may be reduced by up to 2.55%. The results also emphasized that ecosystem services can be protected in the cropland protection scenario (EC). The results of this study enrich the understanding of the impact of human activities on ecological services in agricultural areas and provide new insights into grasping regional food security and ecological stability.

Modeling the Impact of Investment and National Planning Policies on Future Land Use Development: A Case Study for Myanmar

Land use change (LUC) can be affected by investment growth and planning policies under the context of regional economic cooperation and development. Previous studies on land use simulation mostly emphasized the effects of local socioeconomic factors and planning constraint areas that prevent land conversions. However, investment and national planning policies that trigger regional LUC were often ignored. This study aims to couple the economic theory-based Computable General Equilibrium of Land Use Change (CGELUC) model and the cellular automata-based Future Land Use Simulation (FLUS) model to incorporate macroscopic impacts of investment into land use simulation, while proposing an updated mechanism that integrates into the FLUS model to consider the local impacts of planning policies. Taking Myanmar as a case, the method was applied to project the land use patterns (LUPs) during 2017–2050 under three scenarios: baseline, fast, and harmonious development. Specifically, the simulated land use structure (LUS) in 2018 acquired by the CGELUC model was verified by the existing data, and the future LUSs under different scenarios were projected later. Simultaneously, the consistencies between the results simulated by the FLUS model and land use maps in 2013, 2015, and 2017 were represented by the kappa coefficient. The updated mechanism was applied to update the Probability-of-Occurrence (PoO) surfaces based on the planning railway networks and special economic zone. Lastly, the LUPs under different scenarios were projected based on the future LUSs and updated PoO surfaces. Results reveal that the validation accuracy reaches 96.87% for the simulated LUS, and satisfactory accuracies of the simulated LUPs are obtained (kappa coefficients > 0.83). The updated mechanism increases the mean PoO values of built-up land in areas affected by planning policies (increasing by 0.01 to 0.21), indicating the importance of the planning policies in simulation. The cultivated land and built-up land increase with investment increasing under all three scenarios. The harmonious development scenario, showing the least forest encroachment and the highest diversity of LUP, is the optimal approach to achieve land sustainability. This study highlights the impacts of investment and planning policies on future LUCs of Myanmar, and a dynamic simulation process is expected to minimize the uncertainties of the input data and model in the future work.

Modeling trade-offs among ecosystem services for agriculture in the “sisal belt” of Kilosa, central Tanzania

Exploring ways to maintain a biophysically functioning environment while improving human welfare based on competing stakeholder land uses is critical for sustainable development, especially under the context of a surging “global land rush”. This research (1) integrates different stakeholders’ perceptions of human-environmental conditions and dynamics in the “sisal belt” of Kilosa, Tanzania, in terms of three alternative development visions or scenarios of land uses and covers, and (2) demonstrates the trade-offs and synergies among several ecosystem and economic outcomes at a landscape level. Two spatially explicit modeling tools, Future Land Use Simulation (FLUS) and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST), are combined to assess future land-use and -cover patterns and project changes in four ecosystem services, including provisioning commodity production, under the three stakeholder-defined scenarios for the study area up to 2030. Each scenario had higher commodity production values relative to the baseline conditions of 2018 but lower levels of ecosystem services addressed at the level of the Kilosa sisal belt landscape. Carbon and water services may generate synergistic effects provided specific mitigation and payment mechanisms are installed. The spatial distribution of the changes in these services is projected. Our approach provides an empirical-based platform to inform landscape management and planning. It provides a co-designed means to address possible futures of human-environmental conditions affecting sustainability, in this case for food production, resource use, poverty alleviation, and environmental conservation.

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.