Land Use Simulation Research Articles

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.

Modeling Land Use and Management Practices Impacts on Soil Organic Carbon Loss in an Agricultural Watershed in the Mid-Atlantic Region

Measuring organic carbon (OC) losses from soils presents a challenge because of the intricate interplay of human-induced and biophysical processes. This study employs SWAT-C to simulate particulate OC (POC) and dissolved OC (DOC) losses from the Upper Maurice Watershed in the Mid-Atlantic Region. Simulation outcomes reveal that surface runoff was the primary contributor to the total DOC load (65%), followed by lateral flow (30%), and then groundwater (5%). Meanwhile, POC load was linked to erosion processes induced by surface runoff. Our findings indicate that agricultural land-use types exhibited the highest annual average DOC and POC loads. Forests and grasslands displayed intermediate loads, while barren land had the lowest load. Concerning seasonal fluctuations, agricultural land-use types exhibited distinct DOC and POC load patterns when compared to forest and grassland types, indicating the dominant role of management practices in determining soil OC (SOC) losses. Additional modeling of management practices’ impact on SOC budgets indicates maximal SOC sequestration with full irrigation, no-till (NT), and full fertilization. In contrast, the largest SOC depletion arises from combining conservation tillage (CT) and no fertilization, irrespective of irrigation. This study shows that SWAT-C can be used to simulate land use and management impacts on SOC dynamics.

Land Use Change and Landscape Ecological Risk Prediction in Urumqi under the Shared Socio-Economic Pathways and the Representative Concentration Pathways (SSP-RCP) Scenarios

Understanding land use/cover change (LUCC) and landscape ecological risk change in the context of future climate warming can help adjust socio-economic development policies, optimize regional ecological security patterns, and promote green and low-carbon development on the one hand and provide important supplements and improvements for research in related fields on the other. Taking Urumqi as the study area, based on the Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-modal ensemble data, we used the coupled system dynamics (SD) model and patch-generation land use simulation (PLUS) model to simulate land use change under three SSP-RCP scenarios in 2020–2060, and we predicted trends of landscape ecological risk change in this 40-year period by using the landscape ecological risk index (LERI). The results indicate that woodland and grassland significantly increase under the SSP126 scenario. Unused land is larger in the SSP245 scenario. The expansion trend of construction land toward cultivated land is most obvious in the SSP585 scenario; additionally, the area of water increases more distinctly in this scenario. The overall landscape ecological risk under the three SSP-RCP scenarios is reduced to different degrees; in particular, the risk level of urban built-up areas and nature reserves decreases remarkably, and the area of the highest risk zones of unused land is also gradually narrowed. By 2060, the average LERI under the SSP126 scenario is the lowest. The study findings can help relevant departments formulate reasonable urban development plans, which are of great theoretical and practical significance for guaranteeing regional ecological security.

Land-Use Assessment and Trend Simulation from a Resilient Urban Perspective: A Case Study of Changsha City

As the challenges of globalization and climate change intensify, the importance of urban resilience in city planning is becoming increasingly evident. To adapt to this trend, innovations and improvements are essential in traditional urban land-use patterns to better fulfill the requirements of resilient urban development. In this context, this study constructs an urban resilience evaluation index system from four perspectives: social resilience, engineering resilience, ecological resilience, and security resilience to evaluate the urban resilience of Changsha City. A thorough assessment of the resilience mechanisms in Changsha’s urban layout was conducted, employing the SD-FLUS model. A resilient urban scenario is also established to restrict the conversion of high-resilience land into other land types and to predict urban land-use structures under a resilience-oriented directive. The findings indicate that areas with high ecological and safety resilience in Changsha are primarily located in the western Weishan mountain system, along with eastern mountain systems like Jiuling, Lianyun, and Mufu, forming the “green veins”. The central areas are characterized by “blue veins”, mainly represented by rivers such as the Xiangjiang, Weishui, Longwanggang, Jinjiang, Liuyang, and Laodao. Within the central urban area, high-resilience regions are primarily distributed along a framework consisting of “one ring (the city’s three-ring line), two mains (Xiangjiang and Liuyang rivers), one heart (urban green core), and six wedges”, specifying various green corridors. Under the resilience-oriented scenario, the model predicts that by 2025, the total built-up area in Changsha will be 1416.79 km². Areas with high social and engineering resilience are mainly concentrated in the central urban areas of Changsha, as well as Ningxiang and Liuyang, aligning closely with the objectives of Changsha’s latest round of national spatial planning. The built-up area layout should complement Changsha’s topography and water systems, expanding in a wedge-like manner. Overall, Changsha’s planning has successfully integrated social, engineering, ecological, and safety resilience, enhancing its adaptability and long-term sustainability. This research proposes a land-use simulation method guided by the concept of urban resilience, providing valuable insights for resilience-oriented city planning in Changsha and other cities facing similar challenges.

CMADS and CFSR Data-Driven SWAT Modeling for Impacts of Climate and Land-Use Change on Runoff

Climate and land-use change significantly impact hydrological processes and water resources management. However, studies of runoff simulation accuracy and attribution analysis in large-scale basins based on multi-source data and different scenario projections are limited. This study employed the Soil and Water Assessment Tool (SWAT) model in conjunction with spatial interpolation techniques to evaluate the accuracy of Climate Forecast System Reanalysis (CFSR), China Meteorological Assimilation Driven Dataset (CMADS), and observation (OBS) in runoff simulations, and configured various scenarios using the Patch-generating Land-use Simulation (PLUS) model to analyze effects of climate and land-use changes on runoff in the Jing River Basin from 1999 to 2018. Results demonstrated the superior performance of the CMADS+SWAT model compared to than CFSR+SWAT model, as the latter underestimated peak runoff. Changes in precipitation had a stronger impact on runoff than temperature, with increased flow from farmland and strong interception effects from forestland. Integrated climate and land-use changes led to an average annual runoff reduction of 1.24 m3/s (I2), primarily attributed to climate change (1.12 m3/s, I3), with a small contribution from land-use change (0.12 m3/s, I4). CMADS exhibited robust applicability under diverse scenarios, effectively enhancing runoff simulation accuracy. The findings provide invaluable guidance for water resources management in semi-arid regions.

Spatiotemporal evolution and multi-scenario prediction of habitat quality in the Yellow River Basin

IntroductionThe Yellow River Basin (YRB) is not only a vital area for maintaining ecological security but also a key area for China’s economic and social development. Understanding its land-use change trends and habitat quality change patterns is essential for regional ecological conservation and effective resource allocation.MethodsThis study used the patch-generating land-use simulation (PLUS) and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models to analyze and predict the spatial and temporal trends of habitat quality in the YRB from 2000 to 2030 under natural development (ND) and ecological conservation and high-quality development (ECD) scenarios. The PLUS model was used to predict land-use change in 2030 under different scenarios, after which the InVEST model was used to obtain the habitat quality distribution characteristics from the 2000–2030 period.Results(1) The mean values of habitat quality in the YRB in 2000, 2010, and 2020 were 0.6849, 0.6992, and 0.7001, respectively. The mean habitat quality values were moderately high. Spatial distribution characteristics were high in the west and low in the east and along the water. In 2030, habitat quality (0.6993) started to decline under ND, whereas under ECD, there was an indication of substantial improvement in habitat quality (0.7186). (2) The mean habitat degradation values in 2000, 2010, and 2020 were 0.0223, 0.0219, and 0.0231, respectively. The level of habitat degradation showed a decreasing trend, followed by an increasing trend with a stable spatial distribution pattern. The mean level of habitat degradation in 2030 (0.0241) continued to increase under ND, while a substantial decrease in the level of habitat degradation occurred under ECD (0.0214), suggesting that the level of habitat degradation could be effectively contained under the ECD scenario. (3) During the study period, the conversion of building land—both negative and positive—had the most pronounced impact on habitat quality per unit area. Further, the conversion of grassland was shown to be a key land transformation that may either lead to the deterioration or improvement of the ecological environment. The results provide scientifific theoretical support and a decision basis for ecological conservation and the high-quality development of the YRB.

Simulation of LUCC Dynamics and Estimation of Carbon Stock under Different SSP-RCP Scenarios in Heilongjiang Province

An accurate estimation of carbon stocks in terrestrial ecosystem and their future changes in relation to land use and land cover change (LUCC) is important for regional territorial spatial optimization and low-carbon development. In this paper, we integrated the System Dynamics (SD) model, PLUS model and InVEST model to simulate land use dynamics and corresponding carbon stocks in Heilongjiang Province from 2030 to 2050 under three SSP-RCP scenarios proposed by the CMIP6. The findings revealed significant variations in land use demand projections across different SSP-RCP scenarios, with increases observed in farmland, construction land and unused land while decreases in woodland and grassland, and the SSP585 scenario showed the highest increment or decrease. Under the SSP126 scenario, the expansion of farmland was due to a reduction in construction land, with little change observed in woodland and grassland, which resulted in a carbon stock increase of 102.71 × 106 Mg at the highest rate; conversely, under the SSP585 scenario, rapid expansion of farmland, construction land and unused land came at the expense of forest and grassland, leading to a significant carbon stock decrease of 204.64 × 106 Mg. The increase in farmland and the decrease in woodland under the SSP245 scenario was relatively moderate with little change observed in construction, resulting in a carbon stock increase of 108.10 × 106 Mg. Regardless of any scenario considered here, forests remain an important carbon sink contributing significantly to carbon sequestration as well as other ecosystem services in Heilongjiang Province. Enhancing territorial spatial planning and ecological environment construction, while promoting an eco-economic development model, will significantly contribute to the achievement of carbon neutrality and regional sustainable development goals.

Predicting the ecosystem service values and constructing ecological security patterns in future changing land use patterns

The land use and land cover change (LUCC) associated with climate change and human activities poses a persistent threat to ecosystems, profoundly impacting ecological security. Simulating spatiotemporal changes in ecosystem service values (ESVs) and ecological security patterns (ESPs) under different future land use scenarios is crucial for formulating sustainable development policies. This study introduces a comprehensive framework for multi-scenario analysis, which combines the system dynamics (SD) model, patch-generated land-use simulation (PLUS) model, and minimum cumulative resistance (MCR) model to simulate ESV and ESP changes under future LUCC scenarios using the SSP-RCP scenarios provided by CMIP6. The results show that under the three scenarios (SSP245, SSP585, and SSP126), the ESV for the year 2050 is predicted to be 10.285 billion yuan, 10.248 billion yuan, and 10.327 billion yuan, respectively. Additionally, the area of ecological sources is estimated to be 78.56 km2, 65.90 km2, and 141.38 km2, while the lengths of ecological corridors are predicted to be 428.05 km, 332.45 km, and 527.10 km, and the numbers of ecological nodes are 14, 9, and 15, respectively. Notably, the SSP126 scenario demonstrates a significant improvement in ESP compared to the SSP245 and SSP585 scenarios, indicating effective protection of ecological land. This study provides valuable insights and serves as a crucial reference for future decision-making concerning ecosystem conservation and land resource management at the county and municipal scales.

Tempo-Spatial Landslide Susceptibility Assessment from the Perspective of Human Engineering Activity

The expansion of mountainous urban areas and road networks can influence the terrain, vegetation, and material characteristics, thereby altering the susceptibility of landslides. Understanding the relationship between human engineering activities and landslide occurrence is of great significance for both landslide prevention and land resource management. In this study, an analysis was conducted on the landslide caused by Typhoon Megi in 2016. A representative mountainous area along the eastern coast of China—characterized by urban development, deforestation, and severe road expansion—was used to analyze the spatial distribution of landslides. For this purpose, high-precision Planet optical remote sensing images were used to obtain the landslide inventory related to the Typhoon Megi event. The main innovative features are as follows: (i) the newly developed patch generating land-use simulation (PLUS) model simulated and analyzed the driving factors of land-use land-cover (LULC) from 2010 to 2060; (ii) the innovative stacking strategy combined three strong ensemble models—Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM)—to calculate the distribution of landslide susceptibility; and (iii) distance from road and LULC maps were used as short-term and long-term dynamic factors to examine the impact of human engineering activities on landslide susceptibility. The results show that the maximum expansion area of built-up land from 2010 to 2020 was 13.433 km2, mainly expanding forest land and cropland land, with areas of 8.28 km2 and 5.99 km2, respectively. The predicted LULC map for 2060 shows a growth of 45.88 km2 in the built-up land, mainly distributed around government residences in areas with relatively flat terrain and frequent socio-economic activities. The factor contribution shows that distance from road has a higher impact than LULC. The Stacking RF-XGB-LGBM model obtained the optimal AUC value of 0.915 in the landslide susceptibility analysis in 2016. Furthermore, future road network and urban expansion have intensified the probability of landslides occurring in urban areas in 2015. To our knowledge, this is the first application of the PLUS and Stacking RF-XGB-LGBM models in landslide susceptibility analysis in international literature. The research results can serve as a foundation for developing land management guidelines to reduce the risk of landslide failures.

Evaluating the Effectiveness of Land-Use Policies in Preventing the Risk of Coastal Flooding: Coastal Regions of Helsinki and Espoo

Effectively resolving environmental problems often involves not only technical solutions but also examining and potentially reforming the political and institutional frameworks that govern how societies relate to the environment. Coastal flooding due to rising sea levels, for example, poses a significant threat to waterfront areas. Land-use regulations represent an effective means of mitigating this risk. Despite the multitude of strategies developed for tackling similar problems, relatively few have concentrated on assessing the effectiveness of land-use policies in managing such issues. This study examines a framework for evaluating the effectiveness of land-use policies in preventing sea flood risks in the capital regions of Finland. While the focus of this research is on the coastal regions of the cities of Helsinki and Espoo, its implications extend internationally. By integrating Geographical Information System (GIS) and simulation tools, we simulate future land-use scenarios based on values that reflect the effects of land-use policies. This framework can be applied to other coastal regions worldwide facing similar challenges. Using land cover data and GeoSOS-FLUS software, land-use simulations of the target areas were generated. Land-use planning performance in the target areas exhibited positive changes, as fewer vulnerable land-use types were located within the sea flood risk zones in 2018 compared to 2000. This simulation also shows a strong similarity to actual land-use in 2018, confirming the framework’s reliability. This paper presents a novel framework for evaluating the effectiveness of land-use policies in mitigating coastal flooding risks, focusing on the coastal regions of Helsinki and Espoo, Finland. By integrating GIS and simulation tools, the research demonstrates the utility of these tools in tracking land-use changes and analyzing policy impacts, enabling a nuanced assessment of policy effectiveness. Furthermore, the study highlights the importance of local knowledge and a localized approach to policy development, contributing to a deeper understanding of complex issues in urban planning and land-use management.

Simulation-Based Optimization of the Urban Thermal Environment through Local Climate Zones Reorganization in Changsha City, China with the FLUS Model

Urbanization leads to changes in surface landscapes, such as the increase in built-up areas and the decrease in natural elements, resulting in local changes in land surface temperature, which often create unusually hot weather and affect livability, especially for mid- and low-latitude cities. Therefore, optimizing urban landscapes and adjusting the thermal environment is especially important to improve comfort and to achieve sustainable urban development. Existing studies on optimizing landscapes have considered mainly horizontal land uses/land covers but ignored their elevation. This study considered local climate zones as basic units to describe three-dimensional landscapes; we measured the relationship between local climate zones and land surface temperature, based on which the research further used a genetic algorithm and future land-use simulation models to optimize the spatial layouts of local climate zones in Changsha, China, considering multiple objectives including adjusting land surface temperature without affecting population carrying capacity, economic development, watershed protection, and forest and grass protection. According to the optimization results, the area of open low-rise buildings increased by 5.98% after optimization, and dense trees decreased by 7.64%; open low-rise buildings were suggested to be newly built in the city center and sparsely buildings should be developed in the surrounding administrative district far away from the city center. The optimization results contributed to a −5.2 °C reduction of average land surface temperature, which could significantly improve the thermal environment under the premise of ensuring the population and economic development levels and thus serves as a novel solution for improving urban landscapes to implement sustainable city development.

The water balance analysis of several land uses in Tinalah sub-watershed, Kulon Progo

Tinalah sub-watershed has vulnerable to the threat of erosion and landslides. Erosion in the upstream watershed can trigger catastrophic flooding in the area below it. In addition, the problems that occur every year in the Tinalah sub-watershed are drought during the dry season and flooding during the rainy season. The water balance was analyzed by using Thornthwaite and Matter. The result shows that the dry index increased from June and the highest is in August. The highest runoff is in June (0.93). Mostly the land uses have deficit water during 4 months that are June to September, except the mixed planting has 3 months of deficit, whereas the area of the settlement has a longer deficit until 5 months. The simulation of land use in an agroforestry system shows the decreasing value of the deficit which then it will affect the value of the Drought Index (Ia) which also decreases.

Coupled effects of land use and climate change on water supply in SSP–RCP scenarios: A case study of the Ganjiang River Basin, China

Coupling land use and climate change under shared socioeconomic pathway and representative concentration pathway (SSP–RCP) scenarios can provide more accurate predictions of water supply risks, thereby supporting decision-making for spatial planning with a focus on climate adaptation. Climate change exhibits spatial and temporal differences. To meet the requirements of spatial planning, further research is needed to assess water supply risks at different basin or regional scales. In this study, we selected four SSP–RCP scenarios for analysis, considering the temporal scale of spatial planning. The climate modeling capabilities of five global climate models (GCMs) and a multi-model ensemble (MME) were evaluated using a Taylor diagram, which assesses the performance of climate element simulations. The modeling framework that consisted of system dynamics (SD), patch-generating land-use simulations (PLUS), and Soil and Water Assessment Tool (SWAT) was employed to analyze synergistic changes in climate, land use, and water supply. The Ganjiang River Basin (GRB) serves as a case study for climate-adaptive planning at the basin scale, given its characteristics of high agricultural water demand and vulnerability to droughts and floods. The study aims to provide decision-making support for such planning. In our projections, precipitation in the GRB showed a slightly increasing trend from 2021 to 2050. Monthly precipitation increases during the flood season in August and decreases during the dry season from October to December. The maximum and minimum temperatures showed an increasing trend on both the yearly and monthly scales, with slightly higher increases during fall and winter. During the planning phase, the land use quantities of SSP126 and SSP245 showed similar variations. SSP370 experienced the most significant reduction in farmland, while SSP585 displayed a more scattered and punctuated layout of construction land. The annual water supply in the GRB showed a slightly decreasing trend from 2021 to 2035 and 2036–2050, and the largest reduction was found in SSP370. The trend of variation in the monthly water supply was complex. There was a consistent trend of decreasing water supply during the dry season, whereas the changes during the flood season were more complex. Seasonal variations in water supply are a major water security concern for the basin’s future. It is necessary to strengthen the agricultural water security planning in the northern region of the basin and enhance its ability to adapt to droughts and floods.

Impact of ecological conservation policies on land use and carbon stock in megacities at different stages of development

Urban expansion, especially the construction of megacities, increases carbon emissions and adversely affects the carbon storage of terrestrial ecosystems. However, scientific land-use management policies can increase carbon storage. This study takes two megacities at different stages of development, Beijing and Tianjin, as examples to explore the impact of different ecological conservation scenarios on both urban land use and carbon storage to provide recommendations for the construction planning of large cities with low-carbon development as the goal. Furthermore, we coupled the patch-generating land use simulation (PLUS) model with the integrated valuation of ecosystem services and tradeoffs (InVEST) model to simulate land use and carbon storage under a natural development scenario, a planned ecological protection scenario (PEPS), and a policy-based ecological restoration scenario (PERS). From 2000 to 2020, both cities had different degrees of construction land expansion and carbon loss, and Tianjin's dynamic degree of construction land was 0.94% higher than Beijing's, with a carbon loss 183,536.19 Mg higher than Beijing's; this trend of reducing carbon reserves will continue under the natural development scenario (NDS). Under the PEPS and PERS, the carbon stock of both cities increases, and the impact on Tianjin is greater, with an increase of 4.51% and 8.04%, respectively. Under PERS, the carbon stock increases the most, but the dynamic degree of construction land use is negative for both cities. Beijing's carbon stock is 0.40% lower than Tianjin's, which deviates slightly from the trend of urban economic development. Megacities in the rapid development stage can refer to Tianjin, strictly following the ecological protection land planning scope and vigorously implementing ecological restoration policies to effectively increase regional carbon stock. Megacities in the mature stage of development can refer to Beijing, and flexibly implement ecological restoration policies to increase regional carbon stock without affecting the city's economic development.

Carbon emission prediction model of prefecture-level administrative region: A land-use-based case study of Xi'an city, China

Climate change has become a global concern, and the prediction of carbon emissions is key to achieving carbon-reduction goals. The existing framework cannot accurately reflect the spatial distribution of carbon emissions, making it difficult to guide urban planning and management. Therefore, in this study, a carbon emission spatial simulation and prediction model was established. The model includes the GIS-Kernel Density sub-model for subdividing built-up area, the Land Use-Carbon Emission sub-model for establishing the correlation between land use and carbon emissions, the Multi Objective Programming-Principal Component Analysis-BP neural network sub-model for presetting development scenarios, and the Patch-generating Land-use Simulation sub-model for predicting. Xi'an was chosen as the study site, and two extreme scenarios were determined. A total of 373,318 development paths were segmented from the interval, and the optimal path was selected. All scenarios were simulated, and the carbon emissions and their spatial distribution were calculated. The results showed that the overall accuracy of the simulation exceeded 90%. Under the optimal path, Xi'an's carbon emissions reach 60.6 million tons at peak time, which will be reduced to 47.38 million tons by 2060. In addition, the model analyzed the temporal and spatial changes of carbon sources and sinks and drew up the path of carbon reduction by technology and urban planning. This model can provide a reference for regional carbon-reduction planning and carbon reduction technology implantation. It can propose strategies from the perspective of planning and management.

Simulation of Land Use Based on Multiple Models in the Western Sichuan Plateau

Many single-land-use simulation models are available to simulate and predict Land Use and Land Cover Change (LUCC). However, few studies have used multiple models to simulate LUCC in the same region. The paper utilizes the CA-Markov model, Land Change Modeler (LCM), and Patch-generating Land Use Simulation model (PLUS) with natural and social driving factors to simulate the LUCC on the Western Sichuan Plateau, using Kappa coefficient, overall accuracy (OA), and Figure of Merit (FoM) to verify the accuracy of the model, and selects a suitable model to predict the LUCC and landscape pattern in the study area from 2020 to 2070. The results are as follows: (1) The LCM has the highest simulation effect, and its Kappa coefficient, OA, and FoM are higher than the other two models. (2) The area of land types other than grassland and wetland will increase from 2020 to 2070. Among them, the grassland area will decrease, but is still most prominent land category in this region. The proportion of wetland areas remains unchanged. The fragmentation degree of forest (F), grassland (GL), shrubland (SL), water bodies (WBs), bare areas (BAs), and permanent ice and snow (PIS) decreases, and the distribution shows a trend of aggregation. The dominance of F and C decreases but still dominates in the landscape. The overall landscape aggregation increased and complexity decreased, and each landscape type’s diversity, evenness, and richness increased, presenting as a more reasonable development. Using multiple models to simulate the LUCC in the same region, and choosing the most suitable local land model is of great significance to scientifically manage and effectively allocate the land resources in the field.

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.

Spatial Matrices of Urban Expansion in Lafia, North-Central Nigeria

Rapid urbanisation in African cities has caused considerable problems by hindering their ability to meet infrastructure and service needs, resulting in rising land-use consumption. This study examines how land use/land cover change in Lafia, a city in North-central Nigeria, has impacted the city's boundaries between 1999 and 2019 and includes a projection using GIS simulation of land use/ land cover to 2029. The methodology includes remote sensing techniques, spatiotemporal analysis of geographical measurements, and statistical models. This study involved spatial analysis and projection of city growth from 1999 to 2029 in Lafia using GIS. This analysis focuses on the changes in built-up areas, vegetal cover, bare land, and water bodies using land-use/landcover data. The results indicated significant urban expansion and its impact on the city's spatial patterns. The Urban Expansion Differentiation Index (UEDI) and Urban Expansion Intensity Index (UEII)were used to assess urban sprawl and socioeconomic patterns such as population density and density gradient. High residential and employment densities, varied land uses, continuous development, and multi-modal transportation are all important for sustainable urban growth. The study indicates a direct relationship between population growth and urban expansion, as seen in Lafia. Furthermore, the findings suggest that cities grow beyond their typical boundaries, resulting in peri-urban expansion, as shown in the Alakio districts of the Lafia Metropolis. The study findings have important implications for urban growth policy and land use/land cover change. They will contribute to a better understanding of the effects of urban growth on the spatial matrix and morphology of cities, assisting city planners in recognizing these effects. Furthermore, the study adds evidence to the continuing debate about urban expansion, liveability, and spatial sustainability in African cities. The thorough examination of land use/land cover change in Lafia sheds light on the spatial dynamics of urbanisation and its implications for sustainable urban development.

Identifying the drivers of land expansion and evaluating multi-scenario simulation of land use: A case study of Mashan County, China

To reduce land conflicts and improve the coordination of human activities and land use, it is crucial to conduct thorough research on sustainable land management and optimization. In this study, we introduce a new framework for identifying the drivers of land expansion and evaluating multi-scenario simulation of land use. Using Mashan County in China for a case study, the results indicate that the areas of cultivated land and grassland are gradually decreasing, while the building area is gradually increasing, the development probability of cultivated land and forest land is relatively high. Ecological land is primarily influenced by elevation, population density and temperature. In contrast, the expansion of building land is most significantly influenced by gross domestic product (GDP). The prediction result indicates that building land will continue to expand in the future, occupying more ecological space under economic development scenarios. Forest land is expected to increase under the ecological protection scenario, with the smallest expansion of building land, and cultivated land is likely to become a central area for all stakeholders. Our results suggest that adopting the ecological protection scenario is an appropriate strategy for Mashan County's sustainable development. This study provides a better understanding of the complex conflict between ecology and the economy, and offers policy insights for promoting sustainable land use.

Coordinated Development Path of Cultivated Land Utilization in Henan Section of the Yellow River Basin

Rational differentiated utilization of cultivated land can effectively coordinate the contradiction between ecological protection, cultivated land utilization, and urban development. Therefore, this article adopts the southern section of the Yellow River Basin as an example, starting with vulnerability and resilience and then formulating an index system for evaluating farmland ecological vulnerability and farmland resilience. Moreover, this article combines Future Land-Use Simulation–Urban Growth Boundaries (FLUS–UGBs) to conduct urban development boundary simulations, which take the urban development boundary as restrictions and comprehensive division and determine the differentiated utilization zoning strategies for cultivated land to achieve coordinated development between ecological protection, cultivated land use, and urban development. The following results are presented: (1) The ecological vulnerability of the research area mainly involves low-to-medium vulnerability; the western and middle sections of the research area demonstrate high and low ecological vulnerability, respectively. (2) Areas with high resilience of cultivated land are mainly located in the mid-eastern part of the research area, and those with low resilience mainly involve the western mountains. (3) The four-quadrant method, the PLUS model, and the FLUS-UGB module are employed to determine differentiated usage zones for cultivated land to achieve rational allocation and effective use of resources.