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The consequences of urban sprawl and densification are rising surface temperatures and decreased ventilation, which trigger intense urban heat island (UHI) effects. Improving natural ventilation is key for mitigating UHI effects. If policymakers lack foresight into the land-use changes, it may lead to uncontrolled expansion, threatening ventilation potential. Thus, focusing on land-use changes for urban planning goals, this study innovatively proposed the ventilation potential (VPT) simulation by 2030 under scenarios of business as usual (BAU), rapid urban sprawl (RUS), farmland preservation (FLP), and forest preservation (FTP). A model built on the random forest was used to simulate VPT under multiple scenarios. The results indicated that: (1) VPT was mainly influenced by roughness length and land surface temperature gradient, compared to forest canopy density, elevation variation coefficient, and slope. (2) The VPT in 2030 differed considerably between scenarios. Areas with high VPT exhibited a significant declining trend. Spatially, the Fen River and mountainous regions showed high VPT, while the VPT in the northern and southern plains was relatively low. (3) In the FLP scenario, the area with extremely low VPT increased by 476.83 km2 from 2020 to 2030, which was 2.7 times that of the 2010–2020 period. It has a high and extremely high VPT of 1063.82 km2, second to the FTP scenario. (4) In the FTP scenario, the area with high and extremely high VPT decreased by 70.43 km2 and 109.28 km2, from 2020 to 2030. It had the largest area of high and very high VPT among all scenarios, covering 1123.3 km2. The model supports data updating as well as provides scalability of the indicators. With the refinement of this model, the study is expected to offer spatial forecasting tools for urban planning, guiding the development of livable environments in rapidly urbanizing cities to cope with climate change. • Machine learning reveals the spatio-temporal dynamics of ventilation potential. • Rapid urban sprawl without restriction threatens the high ventilation areas. • Protecting forests and water bodies was key to improving ventilation potential. • Farmland in plains disturbs cool winds blowing into the built-up area. [ABSTRACT FROM AUTHOR]

As an important ecosystem of the planet, wetlands play a pivotal role in carbon storage. For alpine regions, safeguarding wetland carbon storage (WCS) has become an integral aspect of sustainable development. To explore the correlation between WCS and sustainable development, we predicted wetland patterns and WCS on the Qinghai-Tibet Plateau (QTP) for 2030 under four scenarios. Utilizing the spatial boundaries of protected areas (PAs), we evaluated current and future changes in the representation and effectiveness of WCS protection. Furthermore, a coupling coordination degree (CCD) model was used to identify the relationship between WCS protection and Sustainable Development Goals (SDGs). The results showed that lakes and reservoirs/ponds were the largest and smallest wetland types on the QTP, respectively, and both displayed an increasing trend from 2000 to 2020, while other wetland types mostly exhibited an opposite trend. Scenario analysis revealed the largest increase in river area compared to 2020 under the comprehensive development scenario (CDS), reaching 6.88%. Across all scenarios, lakes would increase by approximately 6%, primarily due to distance to water and population density. The economic development scenario (EDS) experienced the greatest reduction in swamps. Under these four scenarios, compared to 2020, WCS hotspots displayed varying degrees of decline, with the ecological conservation scenario (ECS) experiencing the most significant reduction (4.2%) and the EDS experiencing the least reduction (0.14%). Only swamps and rivers conservation representation can be improved in 2030. For WCS outside PAs, the most significant enhancement was achieved under ECS for all wetlands except rivers. 6 classes of seriously, moderate, slight incoordination and barely, moderate, high coordination areas were detected based on the CCD analysis. Among the above zones, over 65% of prefecture-level municipalities on the QTP exhibited better than barely coordination levels in 2010, and by 2020, the figure had exceeded 69%. This study deepens understanding of the relationship between WCS and sustainable development in alpine plateaus, and provides decision-making support for coordinate regional development and wetland conservation. [Display omitted] • Assessing the wetland carbon storage on the world's highest plateau. • The conservation representation of swamps and rivers might be improved in 2030. • 69% of cities on the QTP exhibited better CCD than barely coordination in 2020. • Ecological conservation scenario improves wetland carbon storage more. [ABSTRACT FROM AUTHOR]

• Using multiple models to analyze the driving mechanisms of wetland spatiotemporal changes. • The natural wetlands in the research area have decreased by 20 % in the past 30 years. • PLS-SEM reveals the interactive mechanism between natural conditions and human activities on wetland changes. • Urbanization and climate change play a negative role in the indirect effects of wetland changes. • The trend of wetland degradation is inevitable in different development scenarios. Wetlands are among the most productive ecosystems and play crucial roles in relation to biodiversity conservation and various ecosystem services. However, rapid urbanization and environmental changes have led to the loss of a significant number of wetlands, making it imperative to understand the driving forces behind wetland changes. This study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) and the Patch-generating Land Use Simulation (PLUS) model to investigate the influences of natural factors and urbanization on wetland distribution. Based on the driving factors, simulations were conducted for three scenarios—Natural Increase Scenario (NIS), Economic Development Scenario (EDS), and Wetland Protection Scenario (WPS)—projecting the wetland distribution in the Sanjiang Plain until 2050. Results indicate that from 1990 to 2020, the wetland area increased by 9,548.58 km2, with paddy fields increasing by 12,995.73 km2 and marsh wetlands decreasing by 1,031.9 km2. The factors driving wetland distribution varied across different periods. Between 1990 and 2000, topography and urbanization significantly influenced wetland distribution, whereas climate factors became gradually more significant between 2010 and 2020. Furthermore, in addition to exerting direct impacts on wetland distribution, urbanization and climate factors can indirectly affect wetland distribution by influencing topography and soil. Future development scenarios indicate an inevitable increase in paddy field areas and decrease in wetland areas. This framework provides an effective approach for exploring regional wetland changes and supporting regional wetland conservation and future sustainable development. [ABSTRACT FROM AUTHOR]

• Exploring the impact of ecological protection red line on carbon sources and sinks. • Accurate modelling of carbon emissions using Bi-LSTM network. • Projections of carbon budgets in pilot cities for peak carbon. • Combining multiple models for carbon balance prediction and giving suggestions. Under the "dual carbon" goals, targeting issues such as the difficulty in changing the high-carbon economic development model in pilot cities and the inability of previous prediction models to meet current needs, this paper provides an in-depth analysis of carbon stocks and emissions in a peak pilot City spanning from 2000 to 2020. Utilizing the PLUS model, this study forecasts land use/cover data under diverse future scenarios, encompassing natural development (ND) as well as ecological protection (EP). Moreover, the Bi-LSTM deep learning model is developed using six influencing factors to simulate carbon emissions. The research also examined the spatiotemporal changes in carbon budget and balance. The findings of the study reveal several significant conclusions:(1) The PLUS model demonstrated high predictive accuracy in forecasting future land-use types, achieving an average overall accuracy exceeding 0.89 and a Kappa value of 0.8568; The Bi-LSTM model achieved the highest accuracy among all competing models, with an R 2 score reaching 0.864. (2) Under the EP scenario from 2020 to 2030, the rate of decline in carbon storage has slowed down (6.44 × 10 6 t of carbon storage have been avoided from disappearing), and land use efficiency has significantly improved. Due to the protection of ecological land, a certain carbon sink effect has been generated, resulting in lower regional carbon emissions compared to the ND scenario, emphasizing the importance and necessity of setting ecological red lines for carbon stock optimization. (3) Carbon payment areas are primarily concentrated in urban centers, and over time, these areas and carbon compensation zones each account half of the total area. (4) Under different scenarios, the carbon balance of built land has been partially mitigated, and the overall trend is developing favorably. [ABSTRACT FROM AUTHOR]

[Display omitted] • Independently assessed human footprint and grazing intensity's impacts on habitat risks. • Ecological conservation measures on the QXP have had certain effects. • Ecological protection scenario is likely the most probable development path for QXP in the future. • The central and eastern QXP may continue to experience a rising trend in habitat risk. The Qinghai-Xizang Plateau (QXP), the highest plateau in the world, boasts a diverse array of ecological landscapes shaped by extreme climatic conditions; however, it is currently facing significant ecological challenges. In recent years, an increase in human activities, particularly the expansion of the human footprint and grazing intensity, has significantly exacerbated the pressures on habitat risk in the region. In this context, the future habitat risk trend under different scenarios on the QXP require further investigation. To address this gap, a comprehensive multi-scenario habitat risk prediction methodology was developed to fill this gap by integrating the InVEST model, the patch-generating land use simulation model, and the multilayer perceptron model, which combined land use and land cover data with human footprint index and grazing intensity data for a thorough assessment and prediction of habitat risk. Specifically, spatiotemporal changes in habitat risk on the QXP from 2000 to 2020 were analyzed, future indicators were projected, and spatiotemporal variations in habitat risk were evaluated under multiple scenarios. The findings indicate that high-risk areas experienced a significant increase of 39% in 2005; however, this was subsequently mitigated by protective measures. In the Ecological Protection scenario, high habitat risk was reduced by over 74%, while the Urban Development scenario saw an increase of 81% in high habitat risk. The alterations in habitat risks observed between 2005 and 2010 indicate that ecological conservation efforts on the Qinghai-Xizang Plateau have been effective. Among the various development pathways, the Ecological Protection scenario appears to be the most viable for the QXP. Nonetheless, the central and eastern regions of the QXP may continue to face an upward trend in habitat risk. [ABSTRACT FROM AUTHOR]

Understanding the intricate changes in land use and land cover (LULC) transformations, as well as accurately quantifying the ecosystem services value (ESV), holds paramount importance in achieving sustainable development goals. However, previous studies have notably neglected conducting empirical evaluations across various LULC prediction models under identical conditions within the same geographical region. Additionally, the majority of relevant studies primarily concentrate on local scales. In this study, we used CA-Markov, Future Land Use Simulation (FLUS) and Patch-generating Land Use Simulation (PLUS) models to simulate the dynamics of LULC, respectively. Subsequently, we successfully projected the future LULC patterns and corresponding ESV within the Harbin-Changchun Urban Agglomeration (HCUA), China. During the period spanning from 2000 to 2020, a persistent reduction of 2067 km2 in farmland was witnessed within the HCUA, while an accompanying expansion of 4081 km2 in built-up land occurred concurrently. The ESV in HCUA experienced a fluctuating trend. There was an initial decline of 7.443 × 109 yuan during the first decade, which was subsequently followed by an increase of 4.615 × 109 yuan during the latter decade. PLUS, FLUS, and CA-Markov models can all simulate the LULC of HCUA, but in decreasing order of accuracy and ease of use, with OA values of 0.8987, 0.8944 and 0.8651, and Kappa values of 0.8217, 0.8150 and 0.7860, respectively. The PLUS model was chosen to predict the future LULC. Then four development scenarios were set. Our optimization results indicate that it is advisable to restrict the area of built-up land within 17000 km2 in 2030. Moreover, under the economic and ecological balance (EEB) scenario, both ESV and economic benefits are projected to increase compared to the business as usual (BAU) scenario. This study offers valuable insights and serves as a significant reference for future research endeavors focused on optimizing land use. • CA-Markov, FLUS, and PLUS model are used to simulate land use and land cover change. • The simulation results of three different models are compared and validated. • The PLUS model optimizes land use while predicting ESV for the Harbin-Changchun Urban Agglomeration, China. • Taking into account both ecological and economic benefit, four development scenarios are set up. • Exploring each driving factor of each land use type expansion makes the analysis more practical. [ABSTRACT FROM AUTHOR]

[Display omitted] • A comprehensive economic risk assessment framework for BTSSCP is constructed. • Combined risk probability and ecological loss to calculate landscape ecological risk. • Predicts the evolution of landscape ecological risk for multiple development scenarios. • Make recommendations for the BTSSCP Sustainable Development Programme. The comprehensive effect of multi-source factors has altered the landscape pattern and ecological processes within the Beijing-Tianjin Sandstorm Source Control Project (BTSSCP) area, resulting in a fragile environment. Scientific evaluation of the landscape ecological risk (LER) in the project area and identification of the drivers of landscape ecological risk are crucial for preventing and resolving ecological risks and protecting the ecosystem in northern China. This study aims to establish an ecological risk assessment framework, analyze the spatiotemporal changes in the LER in the BTSSCP area from 2000 to 2020, evaluate different factors in depth using the Geodetector model, and predict the LER in 2030 under multiple development scenarios using the patch-generating land use model. The results showed that (1) the dominant land use type in the BTSSCP area was grassland, accounting for more than 50 % of the total area, followed by cropland, unused land, and woodland. (2) The average LERI values in the BTSSCP area for 2000, 2010, and 2020 were 0.023, 0.022, and 0.021, respectively. This demonstrates that the LER in the study as a whole was low and steadily declined. (3) The LER in the project area was influenced by multiple factors. Overall, the evolution of the LER in the study area was primarily affected by natural factors, and the amount of interaction among the multiple factors increased over time. Locally, the normalized difference vegetation index and mean annual temperature were both important factors in this area. [ABSTRACT FROM AUTHOR]

• Constructed a more realistic ecosystem development model based on circuit theory. • The projected land use and cover changes in 2035 under the four development scenarios provide more adequate data support. • The ecological security pattern restriction scenario (S4) has the highest ecological safety index. • S4 has the best ecological effect and the widest range of high-grade habitats. With the development of the social economy, ecological environment damage has become increasingly serious, and how to better protect ecological security has gradually attracted people's attention. This paper takes Hubei Province in China as the research object, using the PLUS model version 1.4 to design four development scenarios to predict land use and land cover changes (LUCC) in 2035: the natural development scenario (S1), the cultivated land protection scenario (S2), the ecological protection area restriction scenario (S3), and the ecological security pattern (ESP) restriction scenario (S4). The study evaluates the ecological effects under these four different scenarios using Conefor Sensinode 2.6 software, Fragstats v4.2.1 software, and the InVEST model. The conclusions are as follows: (1) ESP has better ecological landscape connectivity. (2) Comparing the ecological security indices of the four scenarios, they are 0.5378, 0.5288, 0.5318, and 0.5405, respectively, with the S4 scenario showing the best protection effect. (3) Comparing the habitat quality of the four scenarios, high-grade habitats degrade under S1 and S2 scenarios; homogenization occurs under S3 and S4 scenarios, but the retention rate of high-grade habitat areas is the highest under the S4 scenario. In conclusion, compared to natural progression and prioritizing cultivated land protection, implementing ecological protection policies yields better ecological effects, and a planned ESP provides more targeted policy recommendations. [ABSTRACT FROM AUTHOR]

• The relationship between land type change and carbon stock change was analyzed. • Analyze the spatial and temporal changes of carbon storage from 2000 to 2030. • The carbon density data were corrected for precipitation and temperature in Dalian. • Carbon storage has a faster recovery under the scenario of ecological protection. Carbon storage in terrestrial ecosystems varies with land use changes, and exploring the impact of land use changes on carbon storage in regional terrestrial ecosystems is important for maintaining regional carbon balance. Data on Dalian City's land use types from 2000 to 2020 are used in this research, to evaluate the spatio-temporal evolution of carbon storage in Dalian. Furthermore, with the scenarios of urban development, natural development, cultivated land protection, and ecological protection in 2030, this study combines the PLUS and InVEST models to emulate the dynamic adjustment at land-use types and the spatio-temporal evolution regarding carbon storage in Dalian City. The investigation shows that: 1) The carbon storage of terrestrial ecosystem in Dalian has been altered as a consequence of changes in land use, and now it shows a general decline during 2000–2020, with reductions amounting to 5.39 × 106 t. 2) From 2000 through 2020, Dalian's land resources that are utilized for farming, forestry, and grassland decreased to different degrees. The total construction land area increased by 796.47 km2, or 6.38 %, whereas there has been no substantial improvement in water or unused land. 3) The carbon storage reduction in 2030 in comparison to 2020 for the natural development, cultivated land protection, and urban development scenarios, among which the urban development scenario was the largest, was 1.36 × 106t. It suggests that the rapid rate of urbanization and expansion of construction land is an important cause of the decline in carbon storage. 4) The cultivated land protection scenario (CPS) yields the smallest reduction of 6.50 × 105t. The structure of Dalian's land use type is optimum under the ecological protection scenario (EPS), as seen by the 3.90 × 105t increase in carbon storage under this scenario. It speeds up the rate of recovery of carbon storage and improves the function of carbon sinks in urban terrestrial ecosystems. Hoping to provide the reference to decision makers for ecosystem carbon storage optimization from the view of land use, which is vital for making future land use policies and realizing the "dual carbon" strategic goal. [ABSTRACT FROM AUTHOR]

• The method of selecting the optimal time span provides a higher level of prediction accuracy. • Comparative analyses of multi-contextual simulations are used to explore patterns of short-term variability, and analyses of the evolution of spatial and temporal patterns are used to explore patterns of long-term stability. • The distribution and causes of landscape ecological risks are more effectively described in combination with the pattern of land use change. • Identify the impact of regional policies on patterns of land use change. Land use change in emerging nations raises landscape ecological risks (LERS), hastens the deterioration of urban and rural ecosystem services, endangers human well-being, and undermines sustainable development in the face of rapidly increasing urbanization. Here, using the Chengdu Plain as the study area and long time series data from 2000 to 2020, the optimal time span is selected for multi-context spatio-temporal simulation. The land use map of Chengdu Plain in 2025 under the four scenarios of "Natural Development" (ND), "Economic Priority Development" (END), "Ecological Priority Development" (ELD), and "Sustainable Development" (SD) was simulated, and the multi-indicator landscape ecological risk index (ERI) was generated to compare and analyze the differences between land use and landscape ecological risk under different policy preferences. Subsequently, the land use data from 2025 to 2040 were simulated, the landscape ecological risk pattern was mapped, and the spatial and temporal evolution analysis from 2010 to 2040 was conducted to explore the spatial evolution law of land use change and landscape ecological risk. Based on the results, the high ecological risk aggregation areas are prone to appear in END scenarios, whereas medium-ecological risk aggregation areas are more likely to appear in ELD scenarios, and the government should focus its policy on arable land protection. Moreover, the land use pattern of cultivated land surrounding construction land and forested land surrounding cultivated land, caused by the irrational single-core development pattern and the policy of returning farmland to forests, has exacerbated the landscape ecological risk of the Chengdu Plain, constituting a unique landscape ecological risk pattern. It's also important to remember that the Chengdu Plain's less economically developed regions need to focus on the high-quality development of ecological land use. We adopted high-precision simulation methods to simulate the complex land use changes in rapidly urbanizing areas and explored the spatial evolution law and causes of landscape ecological risk evolution in the context of land use changes, with the intention of offering a solid theoretical foundation for such areas' future planning in developing nations. [ABSTRACT FROM AUTHOR]

• The VORSB farmwork can displayed the actual EH status than traditional method. • Land use change had significant spatiotemporal differences under a multi-scenario perspective. • The land development scenarios with target ecological protection increased EH. • The conversion of farmland to forest land had the greatest positive contribution to EH. • Future attention should be paid to the deterioration of EH caused by urban sprawl in metropolitan developed circle. Land-use changes dominated by high-intensity human activities have seriously threatened regional ecosystem health (EH) and will continue to increase in the future, especially in mountainous cities. Therefore, there is a need to systematically assess the contribution and spatial effects of future land use conversion on EH from a multi-scenario simulation perspective, which is essential for ecological conservation and management. For this purpose, taking Chongqing as an example, this study assessed the static distribution and dynamic evolution of EH over historical periods (2000–2020) and future multi-scenarios in 2030 using the vigor-organization-resilience-ecosystem services balance (VORSB) framework and patch-level land use simulation (PLUS) model, then analyzed the influence of land use conversion on EH and identified sensitive areas under multiple scenarios based on the contribution index and ecological sensitivity index. The results showed that Chongqing ecosystems were generally at a moderate healthy level during 2000–2020, with an increasing trend in EH level, with high-EH located in the eastern mountainous areas, while low-EH clustered in the western urban core and its peripheral areas. From 2020 to 2030, the EH level was improved by about 0.21% under the ecological protection scenario due to the transformation from farmland to forestland, which has the largest positive contribution of 0.111. In contrast, the EH level under the natural development and economic development scenarios declined by 1.95% and 3.07%, especially in the metropolitan developed circle, which was significantly related to the occupation of farmland resources by urban land, with negative contribution of −0.103 and −0.189, respectively. In the future, these regions should strictly control the urban expansion scale and strengthen high-quality farmland protection to achieve the balance of ecological protection and economic development. The findings will provide scientific guidance for the regional ecosystem conservation, land use planning, and urban sustainable development of mountainous cities. [ABSTRACT FROM AUTHOR]

Ecosystem service functions are significant in responding to future LUCC for urban sustainability. Unfortunately, the present works are absent from the coupling effects of resource utilization intensity, climate and environmental changes, and various socio-economic development patterns, failing to clarify the dynamic response of ecosystem service functions to LUCC. To address this gap, we propose a new integrated framework to achieve multi-scenario simulation of future LUCC and assessing ecosystem services from the dual perspectives of land demand structure and function. On this basis, taking the BTH region as an example, we first explore ecosystem services response to future LUCC under multiple scenarios, then discuss the impact of LUCC on ecosystem services across different situations, and provide recommendations and research directions. The main findings show that: (1) The coupling of the multi-objective programming (MOP) and system dynamics (SD) models can better predict the future development trend from the dual perspectives of structure and function. (2) The SSP126 scenario is optimal in terms of preserving farmland, forest, and grassland or restricting built-up land expansion, which aligns better with the development of LUCC under the coordinated development. (3) With regard to ecosystem services, the SSP126 scenario outperforms the SSP245 and SSP585 scenarios. • We investigate ecosystem services response to future LUCC under multiple scenarios. • The coupling models can better predict the development of land use from the perspectives of structure and function. • The SSP126 scenario is optimal in terms of preserving farmland, forest, and grassland or restricting built-up land expansion across the three scenarios. • The SSP126 scenario outperforms the SSP245 and SSP585 scenarios in terms of ecosystem services. [ABSTRACT FROM AUTHOR]

Vegetation productivity is crucial for human production and livelihoods. Understanding net primary productivity (NPP) in historical contexts and predicting its future fluctuations is imperative for assessing the environmental sustainability of a region. However, relatively few researches have been conducted on predicting NPP, requiring further development and refinement of NPP prediction methods and models. This study introduces a novel approach that discretely couples the PLUS and CASA models for NPP prediction, and it validates the applicability of this approach in the research area. The objective of our study is to analyze the spatiotemporal patterns of NPP change in the Beijing-Tianjin-Hebei (BTH) region from 2001 to 2020, predict NPP under three different climate scenarios (SSP 1-2.6, SSP 2-4.5, SSP 5-8.5) in 2030, and identify an appropriate path for the future development of this region. The results indicate:(1) From 2001 to 2020, NPP in the research area has shown a gradual improvement trend and maintained a certain spatial distribution pattern in general. (2) The study discovered a correlation coefficient of 0.83 and an RMSE of 102.86 between predicted and actual NPP for 2020. This suggests that the method introduced in our study is suitable for predicting NPP in the research area. (3) NPP in the study area is predicted to decline in 2030 compared with 2020 under all three scenarios. Moreover, the SSP 1-2.6 scenario, representing a low-emission scenario, is suitable for the BTH region compared with other climate scenarios. This research sheds light on NPP variations in the BTH region over the past 20 years and the next 10 years, offering a scientific basis for relevant departments to formulate future policies. [Display omitted] • We discover that there is a progressive increase in NPP in the BTH region from 2001 to 2020. • This study proposes a new approach to predict NPP by discretely coupling the PLUS model and the CASA model. • According to our research, the predicted NPP in the BTH region will decrease in 2030 compared with 2020. • We find that in 2030, the SSP5–8.5 scenario has the highest NPP, followed by the SSP2–4.5 scenario and the SSP1–2.6 scenario. [ABSTRACT FROM AUTHOR]

Construction land development suitability (CLDS) assessment holds paramount importance in contemporary urban planning and management. Previous CLDS studies have faced challenges such as insufficient evaluation indicators, model complexity, and limited interpretability. To address these gaps, this study applies three simplistic yet mature models from the field of geological hazard assessment - Weight of Evidence (WOE), Information Value (IV), and Frequency Ratio (FR) - to evaluate the CLDS in Wuhan, China, and examine their feasibility. In parallel, a comparative analysis with the Patch-generating Land Use Simulation (PLUS) model was conducted. The WOE, IV, and FR models demonstrate a gradual decrease in CLDS from the city center and the Yangtze and Han rivers towards the periphery. Conversely, the PLUS model indicates the highest suitability around the city's development boundaries, followed by the city center, with suburbs displaying lower suitability. In terms of accuracy, the PLUS model's CARS module outperforms others, particularly for micro-level urban expansion simulations. The IV and WOE models follow closely, manifesting a preference for macro-level urban planning. Additionally, this study pinpoints key drivers influencing CLDS, notably population density, distance to social service Points of Interest (POI) and proximity to road networks. The cross-validation of the WOE, IV, and FR models underscores their reliability, with their straightforward principles positioning them as valuable tools in urban development planning. This comparative study validates the application of geological hazard models in urban contexts and diversifies CLDS assessment methodologies. [Display omitted] • Transplantation and Application of Geological Hazard Models. • Comprehensive Indicator System Incorporating Multivariate Driving Factors. • Multi-Model Assessment of Construction Land Development Suitability. • Spatial Prediction of Construction Land under Quantity Constraints. [ABSTRACT FROM AUTHOR]

[Display omitted] • The intensity map model effectively reveals the complex patterns of land use change. • Urbanization and agriculturalization are the primary manifestations of changes in LULC. • The response mechanism of ESV to changes in LULC is analyzed. • Multi scenario simulation of future LULC and ESV based on Markov-PLUS model. • Ecological restoration measures have a curbing effect on the degradation of ESVs. Changes in land-use patterns are the main driving factors of ecosystem service values (ESVs). The quantitative evaluation of ESVs is significant for the sustainable development of ecologically fragile areas. In this study, the Chishui River Basin (CRB) in China was selected as the study region, and an intensity map (IM) was used to analyze the transformation of land use/land cover (LULC). The modified equivalent coefficient value method was used to evaluate the ESVs based on the 2000, 2010, and 2020 land use datasets. The spatial and temporal distributions of ESV and its response to changes in LULC were analyzed using the Getis-Ord Gi* statistical method and Spearman's rank correlation analysis. Moreover, spatial and temporal changes in LULC and ESV over the next 30 years in the four development scenarios were simulated using the Markov-PLUS model. The following results were obtained: 1) The farmland and forestland were the dominant LULC categories, and that the LULC pattern dramatically changed in the study area; 2) the total ESV of the CRB decreased significantly from 23.21 billion yuan in 2000 to 22.29 billion yuan in 2020; and 3) the ecological conservation scenario significantly promoted the total ESV, and the town development scenario was more conducive to the urbanization process. Therefore, although the ESV of the CRB showed a decreasing to slowly increasing trend in the context of a series of ecological restoration measures, scientific ecological protection and development policies must be continuously implemented to achieve harmony between ecological service improvement and urbanization development. Our results provide important information for making land-use decisions and facilitating sustainable development in ecologically protected basins. [ABSTRACT FROM AUTHOR]

[Display omitted] • Carbon emissions are forecasted under different development scenarios. • The Moran's I was positive and increased gradually from 2010 to 2020. • The carbon emission risks vary significantly across geographical areas in Yaan. • Low-carbon optimization can reduce 24.674 × 104 t of land use carbon emissions. Land use and cover change (LUCC) is a major driver of this rapid increase in atmospheric carbon. To reasonably plan various types of land use areas and mitigate the rate of growth of carbon emissions, this study takes Yaan, Sichuan province, as a case study. First, the calculation of Yaan's land use carbon emissions (LUCE) was approached by taking land use structure into account. Subsequently, the spatiotemporal distribution of LUCE was evaluated by employing the carbon emission risk index and the Moran index. Finally, the multi-objective linear programming (MOP), the Markov chain, and the PLUS model were used to predict the spatial distribution of LUCC in 2030, including natural development scenarios (NDS) and low-carbon optimization development scenarios (LODS). According to the findings, the impervious surface is identified as the principal contributor to LUCE, while the forest is recognized as the principal absorbers of carbon. The carbon emissions in typical mountainous areas are distributed in cities and generally concentrate towards the plains in the northeast direction. Under the LODS, LUCE decrease significantly. For both NDS and LODS, the overall trend of land development direction in Yaan is "northeast-southwest" from 2020 to 2030. These results could provide some suggestions for low-carbon land use in cities like Yaan. [ABSTRACT FROM AUTHOR]

Understanding the relationship between land-use patterns and regional carbon storage, as well as predicting future land-use changes for regional carbon sink and emission management, are of immense significance. This study utilized land-use data from 1990, 2000, 2010, and 2020, as well as the InVEST model, to evaluate the spatiotemporal evolution of carbon storage in the Sanjiangyuan area over the past three decades. Furthermore, predictions for carbon storage in 2035 were presented using the PLUS model. The findings revealed the following key results: (1) the land types in the Sanjiangyuan area are mainly low cover grassland, medium cover grassland and unused land, among which unused land decreased significantly from 1990 to 2020, and the area of low cover grassland and wetland increased, which is the main reason for the increase of carbon storage. (2) Climatic-environmental and social-economic factors jointly influenced the land-use change in the Sanjiangyuan area. Except for the three types of grassland, the expansion of other land types was mainly influenced by climatic and environmental factors. (3) During 1990–2020, carbon storage in the source region of Sanjiangyuan area showed an overall upward trend, with a total increase of 39.97 × 107 t, and land-use change had a positive potential impact on carbon storage as a whole. (4) Under the natural change scenario, both carbon storage and regional carbon density increased in the simulation of 2035, and the potential impact of land-use change on carbon storage is positive. On this basis, the paper puts some suggestions forward to improve the carbon storage capacity of the Sanjiangyuan area in the future. This study provides valuable scientific insights for land-use management decision-making and promotes sustainable development of carbon storage functions in this region. • Total carbon storage increased between 1990 and 2020. • The simulation predicts higher carbon storage in 2035 than in 2020. • Ecological protection policies have a crucial contribution to improving carbon storage. • Regulating regional Socioeconomic activities is an effective measure. [ABSTRACT FROM AUTHOR]

Dramatic land cover changes related to the accelerated urbanization process have led to habitat fragmentation and loss, resulting in biodiversity loss. Ecological Networks (ENs) have been seen as an effective solution for ecological conservation targeting habitat connectedness and ecosystem functions. The EN research is, however, generally depicted by current or historical landscape data, devoid of the potential future disturbances, which is detrimental to maintaining EN's stability and sustainability. This study combines the system dynamics (SD) model and patch-generating land use simulation (PLUS) to simulate land use patterns in Wuhan urban agglomeration (WUA), China. The simulated land use data were incorporated into EN modeling to assess the long-term dynamics of EN in WUA, considering two scenarios related to human activities and climate change. In parallel, a landscape graphs approach is used to estimate the spatial priority of EN for conservation in landscape dynamics. The results show that: (1) The grassland decreased from 2000 to 2020 and is expected to increase from 2020 to 2035. The area of construction land would reach its peak in 2035 while cultivated land would hit a low point. (2) Analysis of EN reveals habitat fragmentation and reduced connectivity from 2000 to 2020. From 2020 to 2035, an increase in EN connectivity is expected to be observed in the SSP5–8.5 scenario, while SSP2–4.5 is the reduced scenario. (3) Southern and eastern WUA exhibit high conservation priority. The hotspots of local landscape changes are mainly the corridors that traverse through human activity areas and the edges of core habitats, which is critical to conserving. (4) The impact of natural and socioeconomic factors on EN exhibits spatial heterogeneity. This paper provides new insights to protect habitats and biodiversity to mitigate the challenge of human activities and climate change. [Display omitted] • Scenario simulation evaluates the impacts of human and climate change on ecological network. • The SSP5-8.5 indicates an increase in connectivity of the ecological networks. • The impact of urban development on the ecological network varies depending on urban structures. • More emphasis should be focused on the hotspot areas where the local landscape changes. • A scenario of increased connectivity does not imply that it should be prioritized. [ABSTRACT FROM AUTHOR]

• Interactions between LULC and ESV in arid and semi-arid regions were studied. • Different development scenarios were created using a multi-objective planning algorithm. • Ecosystem services revealed from a socio-ecological perspective. This study aimed to investigate the interrelationships between land use/land cover (LULC) and ecosystem services value (ESV) in arid and semi-arid regions, with a specific focus on the Kashgar region in Xinjiang, China. Four distinct development patterns (BAU, RED, ELP, and EBB) were derived using a multi-objective planning algorithm (MOP), and the relationship between LULC and ESV was analyzed using three methods: the random forest algorithm, the PLUS model, and the ecosystem service equivalence method. The findings indicated a significant projected expansion of LULC in Kashgar by 2030, primarily concentrated in arable and construction land. The ELP scenario demonstrated the lowest growth in cultivated and urbanized land, while the BAU and RED scenarios exhibited higher increments. Notably, the expansion of arable and construction land was concentrated around the urban agglomeration of the Kashgar region, whereas changes in forest land were concentrated near the Kunlun Mountains. Regarding ESV, grassland and watersheds played a significant role, accounting for 45 % and 30 % of the total, grasslands and watersheds emerge as pivotal components in supporting biodiversity, soil preservation, water regulation, and purification. The study underscores the necessity of conserving these ecosystems. This study highlights the trade-offs between economic development and ecological/environmental protection. The RED scenario, driven by rapid economic growth and urbanization, has resulted in a significant decline in ESVs, underscoring the urgency of sustainable land use practices. The MOP-PLUS-ESV model used in this study provides a powerful framework for decision makers to make informed choices in land use planning. By prioritizing a balance between economic development and ecological preservation, the model contributes to sustainable community and regional growth, emphasizing the preservation of important ecosystems. The findings suggest that Kashgar needs to adopt a sustainable land use strategy that balances economic development and ecological/environmental protection to maximize the provision and protection of ESV. The pathway emphasizes the integrated consideration of ESV, rational land use policies, and enhanced ecological protection to achieve an ecological civilization. [ABSTRACT FROM AUTHOR]

[Display omitted] • We proposed a framework integrating SSP-RCP scenarios, PLUS model and InVEST model. • The trends of land use and WESs under the three future SSP-RCP scenarios were different. • It was found that LUC was not the main influencing factor for the change of WESs in the PYLB. A scientific understanding of the trends of water-related ecosystem services (WESs) under different scenarios is crucial to improving WESs and maintaining ecological security. However, there is a lack of high-resolution land use simulation and assessment of WESs under the SSP-RCP scenarios, and the impacts of different land-use change (LUC) on WESs are not clear. This study focused on the Poyang Lake Basin (PYLB), utilizing the SSP-RCP scenarios, the PLUS model and the InVEST model to explore the dynamic changes of land use and WESs historically and in the future, and to reveal the impacts of specific LUC on WESs from 2000 to 2020. The results demonstrated that: (1) The forest land increased under both SSP1-2.6 and SSP2-4.5 scenarios but increased first and then decreased under SSP5-8.5 scenarios; Cropland increased significantly under SSP5-8.5 scenarios, and the construction land showed an expansion trend under the three scenarios. (2) From 2000 to 2020, only the water purification capacity decreased, while the rest of the WESs increased. Under the SSP1-2.6 scenario, the overall benefits of the WESs in the PYLB were the highest. (3) Between 2000 and 2020, deforestation in the PYLB brought about the greatest increase in the water yield (+9.06 × 108 m3). The increase in the construction land brought about the most water conservation loss (−18.19 × 108 m3). Additionally, the forest expansion and cropland reduction brought about the largest increase in soil retention (+3.94 × 105 t and +4.79 × 105 t) and enhanced water purification, and the opposite was true for deforestation. The conclusions can provide an important basis for the ecological protection and high-quality development of the PYLB. [ABSTRACT FROM AUTHOR]

• Simulate future land use under various scenarios. • Analyze urban expansion, Ecological Security Patterns, and ecological health dynamics. • Integrate the dynamic ESP and EH to optimize the current ecological security configuration. Urbanisation affects the health and stability of ecosystem significantly. Constructing a scientific ecological security pattern (ESP) is of paramount importance for safeguarding the health of ecosystems within a region, optimising ecological spaces, and ensuring sustainability. To investigate the effect of urbanisation on the ESP, we utilised the Vigour–Organisation–Resilience-Services (VORS) model to analyse the changes in ecosystem health (EH) and identify degraded areas in the city of Chengdu. In this case study. We used the Patch-generating Land Use Simulation (PLUS) Model to predict the urban expansion trends in 2035 and evaluate the changing ESP. Additionally, we used the minimum cumulative resistance (MCR) model and circuit theory to construct an ecological network to facilitate multilayer planning of ESP. We identified an ecological source area of approximately 4484.29 km2 and a recovery zone of 1608.35 km2 for managing EH degradation within the ecological source. An ecological conservation zone of 987.48 km2 with restricted development outside the ecological source, and a restoration zone of 71.66 km2 to mitigate the impact of urban expansion on ecological security were also identified. Seven stable corridors with consistent spatial patterns and pressure levels and six potential corridors await restoration. Based on the analysis of changes in ecosystem health and dynamic ESPs, different scenarios were simulated for 2035. The findings suggested significant variations in EH and ESP around 2010 despite rapid expansion in Chengdu. The ecological environment was partially restored by increasing the land area and controlling its contraction. Therefore, scientific planning of ESPs, limiting the boundaries of urban expansion, and accurately assessing the health of ecosystems are crucial for ensuring ecological security. [ABSTRACT FROM AUTHOR]

• Wetlands have degraded in the YRD, resulting in a decline in HQ. • Land subsidence and SLR will expose the YRD to huge risks of seawater inundation. • The future HQ will be underestimated when seawater inundation is not considered. • EPs can minimize losses caused by seawater inundation. Accurately assessing future land use/cover change (LUCC) and habitat quality (HQ) is vital for ensuring sustainable use of coastal ecosystem services, but most studies ignore the effects of seawater inundation. This study developed a framework based on the PLUS model and InVEST-HQ model that considers seawater inundation due to sea level rise (SLR) and land subsidence. We used this framework to simulate future LUCC and HQ under different scenarios in the Yellow River Delta (YRD). The results showed: (1) From 1991 to 2020, natural wetlands decreased by 39.87 %, non-wetlands decreased by 3.06 %, and artificial wetlands increased by 730.71 %. The overall HQ showed a decreasing trend, with the largest decrease in non-wetlands. (2) Land subsidence occurred in 93.26 % of the YRD, with a subsidence rate of −36.55 mm/year. Underground brine mining is the most important driving factor. About 6.81 %∼11.16 % of the area will be inundated in 2035, and about 9.39 %∼19.27 % of the area will be inundated in 2050. (3) Future multi-scenario simulations show that the Ecological-Protection scenario can minimize the ecological losses caused by seawater inundation. The simulation of future HQ will be underestimated when seawater inundation is not considered. Our study shows that seawater inundation caused by land subsidence and SLR must be taken into account when simulating LUCC and HQ in coastal areas. [ABSTRACT FROM AUTHOR]

• Incorporate the ecological security pattern into the constraints of future land use simulation. • Integrate future building land expansion with the ecological security pattern to identify ecological early warning areas. • Considering land use types, propose ecological restoration strategies for ecological restoration and early warning areas. The scientific determination of crucial regions for ecological land restoration and reasonable early warnings for ecologically weak areas are vital for implementing land ecological restoration. Five major plateau lake basins in central Yunnan (China) are selected as the study area in this research. An ecological security pattern (ESP) is constructed using the source-resistance surface-corridor-pinch point framework to effectively identify crucial areas for ecological restoration. Finally, the land use/cover change (LUCC) in the study region in 2030 is simulated in terms of the natural development prospect (NDP), with priority given to urban development (PUD) and priority given to ecological protection (PEP) scenarios, and identify areas where future urban expansion poses a threat to current ecological source areas and corridors as early warning regions. The results indicate the following: (1) There are 15 ecological source regions in the Five Lakes Basin, mainly forestland and waters, with a total area of 787.54 km2. The ecological corridor spans 245.72 km, with a total area of 439.90 km2. (2) The key ecological restoration areas include 72.87 km2 of ecological pinch points, 70.46 km2 of barrier points of ecological, and 71 breakpoints. (3) The ecological land under the NDP scenario and the PUD scenario were damaged to varying degrees. The ecological land dominated by forestland and water area under the PEP scenario is effectively protected. (4) The seven ecological protection space early warning points are mainly distributed in the eastern part of Dianchi Lake and the northern part of Fuxian Lake, which have good economic development and better habitat quality. The comprehensive analysis identified key ecological restoration areas and identified future ecological stresses due to land use change in the Five-Lakes Basin. Restoration strategies are proposed based on current land use and future scenarios to enhance the ESP in central Yunnan's Five Lakes Basin. [ABSTRACT FROM AUTHOR]

A critical step in alleviating the contradiction between human activities and land systems is to project and analyze land use change traits in various scenarios to furnish a basis for formulating economic development and ecological conservation strategies. However, few studies have examined land use change using the system dynamics (SD) model and patch-generating land use simulation (PLUS) model in the Chinese Tianshan mountainous region (CTMR) affected by different economic growth patterns and climate change contexts. Therefore, based on the Shared Socioeconomic Pathways and Representative Concentration Pathways (SSPs-RCPs) scenarios, we attempted to construct a regional SD model (RSDM) including population, economic, land, and climate subsystems. Then, the coupled model by combining RSDM and PLUS was employed to simulate and project land use/cover changes (LUCC) in the CTMR at the regional level to explore the spatial distribution of land and its pattern of change in different climate contexts. The SD model is an effective method that can simulate the nonlinear behavior of a complex system and predict its evolution through the interactions and feedback relationships between different influencing factors. The PLUS model is an effective tool that can be used to simulate the evolution of land patches and capture the extent to which the driving factors contribute to LUCC. The relative errors were less than 5%, and the total accuracy of PLUS model was 91.77%. The above results demonstrated the effectiveness of RSDM and PLUS model in modeling LUCC across the CTMR. From 2005 to 2020, there was an expansion trend in the area of forest and construction land as well as in the area of cultivated land, while the grassland area displayed a significant decline. By 2040, the area of unused land, grassland, and water is expected to demonstrate a decreasing trend while other land types increase, with construction land showing the most significant increase of 101.37% under the SSP585 scenario. It is anticipated to expand mainly to cultivated land and grassland around cities. The cultivated land is expected to primarily encroach on the regions of unused land and grassland under the three scenarios, reaching the expansion demand. As opposed to the scenarios of SSP126 and SSP245, the SSP585 scenario distribution of the cultivated land patches will be more compact and denser. The SSP126 and SSP245 scenarios will exhibit similar patterns of future spatial distribution of land. The SSP585 scenario is anticipated to display marked differences. According to the three scenarios, grassland degradation will be severe and require increased grassland protection. The findings can offer novel perspective concepts with regard to future ecological and environmental management, judicious distribution of land resources, and sustainable progression in the CTMR. • Coupled the SD model and PLUS model to enhance the simulation accuracy. • Considering socioeconomic pathways and climate conditions influences in Modeling. • Land use change trends were projected in the CTMR under SSP-RCP scenarios. • Predicting an expansion trend for construction land, forest and cultivated land. • Unused land, water, and grassland are predicted to decrease. [ABSTRACT FROM AUTHOR]

[Display omitted] • A framework for evaluating ecological impacts of GDP growth was developed. • GDP growth is the potential driving force behind changes in ecosystem services. • Trade-offs between GDP growth and ecosystem services were identified. • Balancing economic growth and ecological protection prioritizes ecologically fragile areas. The rapid growth of gross domestic product (GDP) in developing countries may lead to the overconsumption of ecosystem services (ESs). This situation presents as the imbalance of ecological conservation and economic development, as is the case in areas of West China, such as Guiyang city. This study utilized the PLUS model to simulate future land use/land cover (LULC) scenarios and the InVEST model to assess the ESs in relation to rapid GDP growth in Guiyang city. The research findings reveal the following: 1) the growth of developed land contributes to ecosystem degradation and increased potential ecological hazards. The implementation of GDP growth policies may be the potential driver of land use change and a factor influencing changes in ESs. For example, between 2010 and 2020, the area of developed land increased by 339%, but the soil retention and carbon storage decreased by 2.04% and 3.26%, respectively. 2) The changes in GDP and ESs showed spatial heterogeneity. From 2020 to 2030, the general hot spot distribution of ESs and GDP was consistent, which was closely related to land use change. 3) Trade-offs and synergistic effects exist between GDP and ESs, including a trade-off between GDP and soil retention and synergy between GDP and water yield. GDP growth comes at the expense of ESs. The study emphasizes the need to prioritize ecological conservation in the degraded areas of southern Guiyang city. It urges stronger management of ecological redlines, stricter construction land policies, and a balanced approach to economic development and ecological protection. [ABSTRACT FROM AUTHOR]

The accurate assessment of ecosystem service value (ESV) changes driven by land use is the key to land remediation planning and ecologically sustainable development. The Zoigê Plateau is a typical ecologically fragile area in the upper reaches of the Yellow River. In recent years, human activities and economic development have put tremendous pressure on the land and ecological environment in the region. To quantitatively assess the ESV of the Zoigê Plateau, this study accounted for, analysed and predicted the ESV of the study area based on the land use change pattern of the Zoigê Plateau from 2000 to 2020 using dynamic attitude analysis, the equivalent factor accounting method, correlation analysis and the Patch-level Land Use Simulation model (PLUS). The results showed that the ESV was 150.4 billion, 157.28 billion and 156.54 billion CNY in 2000, 2010, and 2020, respectively, with a trend of first decreasing and then increasing. The interaction between ecosystem services had a significant impact on the spatial distribution of ESV. Based on predictions made by the PLUS model for multiple scenarios, different scenarios resulted in different ESV change trends and, from 2020 to 2030, the ESV continued to decline under the natural development and urban construction scenarios. The ESV value was the smallest under the urban construction scenario, while the ESV continued to increase under the ecological protection scenario. This study demonstrated how dynamically ESV responded to land use change, which is crucial for improving both the ecological service function and the spatial pattern of the land of the Zoigê Plateau. • Comprehensive assessment of ESV trends in the Zoigê plateau over the last 20 years. • Three distinct land-use scenarios were simulated and converted into ESV projections using the PLUS model for the Zoigê Plateau. • Explore the links between ecosystem functioning and the spatial distribution of ESV. [ABSTRACT FROM AUTHOR]

• Incorporating regional development heterogeneity as a new way to model urban growth. • Denoising small patches in each round reduces simulation noise and boosts accuracy. • New model improves the simulation, yields reliable results to aid urban planning. • The city, especially new city areas, experienced notable growth, but will decelerate. • Shrinking land availability and economic transformation caused growth deceleration. Rapid global urban expansion necessitates accurate simulations to comprehend future growth patterns and their implications. Cellular automata, such as the widely used patch-generating land use simulation (PLUS) model, ensure reliable accuracy in urban growth simulations. However, previous studies have overlooked the development heterogeneity amongst sub-regions by treating the study area as the homogenous. Based on the PLUS model, this study introduces a new model coupling regional development heterogeneity and noise reduction (RDHNR-PLUS), which is an enhanced model that incorporates relative development coefficients derived from nighttime light data to capture regional heterogeneity. It also employs noise reduction techniques inspired by image classification's small patch processing method. Results demonstrate that the relative development coefficients effectively reveal the potential of different regions, while the noise reduction process mitigates simulation noise. The combined approach enhances overall accuracy, figure of merit, and structural similarity by 4.56 %, 20.44 %, and 5.06 %, respectively. Additionally, we simulate and analyse the built-up area of Zhengzhou from 2000 to 2030. The findings indicate rapid past growth, particularly in new urban areas, with projected future expansion likely to slow down. However, built-up areas dominated by medium to high and high densities will occupy three-quarters of the region. These results underscore the sustainability challenges faced by Zhengzhou, including disaster risk, traffic congestion, and air and noise pollution. [ABSTRACT FROM AUTHOR]

• Use Budyko method and the WEP hydrological model to assess the effects of climate change and underlying surface changes on runoff. • Predict future land use change using PLUS model. • Prediction of future runoff change in different scenarios. It is necessary to comprehend the impacts of climate change and human activities on hydrological processes to effectively manage water resources. This study focuses on the Huangfuchuan Basin and investigates changes in hydrology and land use within the basin. The Budyko method and the water and energy processes (WEP) hydrological model were employed to assess the effects of climate change and underlying surface changes on runoff. The results showed that: (1) Runoff in the Huangfuchuan Basin exhibited a pronounced decreasing trend between 1960 and 2015, with an annual average runoff of 42.82 m3/s. (2) According to the Budyko method, the underlying surface change had the highest contribution rate to runoff at 83.54 %, followed by rainfall at 12.28 %. (3) Based on the simulation of the WEP hydrological model, climate change contributed to 22.08 % of the runoff change. Land use change accounted for 65.95 % of the runoff change. (4) Various future climate change scenarios were examined in this study. The maximum average runoff simulated by the model occurred when rainfall increased by 20 % and temperature decreased by 20 %, resulting in a 13.485 m3/s increase compared to the base scenario. (5) The simulated annual runoff, from highest to lowest, was as follows: urban development scenario (19.71 m3/s) > ecological protection scenario (18.68 m3/s) > baseline scenario (13.17 m3/s). This study enhances our understanding of runoff variation in the Huangfuchuan Basin and provides a valuable foundation for water resource management and conservation on the Loess Plateau, China. [ABSTRACT FROM AUTHOR]

• Integrate PLUS model and ecological network. • Analysis of influencing factors of land surface temperature. • Construct cold-heat island network to alleviate urban heat island effect. • The results of the study can guide the planning of eco-cities. Many studies on mitigation of the surface urban heat island (SUHI) are conducted from the perspective of landscape patch allocation, and few studies have investigated the overall impact of network connectivity on SUHI. In this study, an ecological network framework is proposed to identify the key patches and cooling corridors. Based on surface temperature inversion data, morphological spatial pattern analysis (MSPA) and landscape connectivity indexes are used to identify heat island and cold island patches with high ecological value on which to construct the network. The innovative patch-generating land use simulation (PLUS) model is introduced to construct a resistance surface, and Circuit theory (CT) is used to connect cold islands and heat islands in cooling corridors. The results show that from 1999 to 2019, land surface temperature (LST) increased significantly in the city of Haikou, the extreme LST became more and more significant, and the area with the highest temperatures showed a southward trend. The connectivity between cold and heat island patches declined, and the Loop, Bridge and Branch areas in heat islands increased. The latter scenario is conducive to the construction of cooling corridors. The land cover index had a great influence on SUHI, and the resistance surface presented a distribution pattern with high values in the northwest and low values in the southeast, which is consistent with the distribution of LST. Finally, we extracted the resultant cold-heat island cooling network, which was mainly concentrated along the southern edge of the study area, and found that corridor construction faced fewer obstacles in 2019 than in 1999. This study can guide urban planners to reinforce the parts of ecological networks that will mitigate the urban heat island effect. [ABSTRACT FROM AUTHOR]

• Evaluated the spatio-temporal distribution of ecological risk under different scenarios on the QTP from 2000 to 2030. • Using the Sharpe ratio of future uncertainty to assess ecological risk. • Spatial heterogeneity in the ecosystem service values on the Qinghai-Tibet Plateau under future scenarios. • Discussing the different impacts of uncertainty in integrated scenario-based risk assessment of the Qinghai-Tibet Plateau. As one of the world's critical ecological regions – often called the "Third Pole" – the Qinghai-Tibet Plateau (QTP) has outstanding ecosystem service values (ESV). However, its variable climate and fragile environmental conditions make it vulnerable to disturbance by human activities. Based on land use data from 2000, 2010, and 2020, we developed three simulated scenarios of land use distribution on the QTP: business as usual (BAU), farmland protection (FP), and ecological protection (EP). Finally, we employed the Sharpe Index to evaluate ecological risk across the QTP. The results showed that from 2000 to 2020, land use change was mainly in the form of conversion of grassland to unused land, totaling an area of 63,717 km2. The ecosystem service value showed an increasing trend, from US$752.6 billion to US$783.0 from 2010 to 2020. The simulation results from the three scenarios revealed significant differences. Farmland area shows a declining trend in both the EP and BAU scenarios, while exhibiting an increasing trend in the FP scenario. Forest area on the plateau experiences a decreasing trend in the EP and BAU scenarios, but shows an increase in the FP scenario, predominantly in the southeastern region, including Sichuan and Yunnan provinces. The ecological risk assessment results indicate that the eastern region has higher ecological risk compared to the western region, highlighting the western region as a priority area for risk control. The expansion of built-up land and unused land has had significant impacts on regional ecological risk. Integrating risk assessment outcomes with land use planning to identify focal areas can provide guidance for the sustainable development of this globally important ecoregion. [ABSTRACT FROM AUTHOR]

[Display omitted] • The land use carbon emissions (LUCE) in the Yellow River Basin (YRB) showed an increasing trend. • The results indicate that there was a general correlation between LUCE of cities in the YRB. • In 2030, the LUCE in the YRB showed an increasing trend, with the minimum increase under ecological protection scenario. Carbon dioxide emission is an important driving factor of global warming and it has threatened the ecological environment and human survival. Among them, land use has led to significant carbon emissions that profoundly affect climate system change. The Yellow River Basin (YRB) is one of the regions with the most concentrated contradictions in population, resources, and environment in China; thus, studying the current situation and land use carbon emissions (LUCE) is significant for mitigating global warming, promoting coordinated emission reduction among different regions in the basin, and achieving ecological conservation and high-quality development of the YRB. This study based on land use and socio-economic data, and is carried out from the perspective of social network analysis. The spatiotemporal variation of LUCE in the YRB was analyzed using the carbon emission coefficient method. The spatial spillover effects of LUCE were discussed using social network analysis methods. The PLUS model was used to simulate the differences in LUCE under different scenarios. The results indicate that: (1) The LUCE in the YRB showed an increasing trend during the study period, with significant differences in spatial distribution. (2) There is a significant spatial spillover effect and correlation between cities in the YRB LUCE network, and cities with superior economic had a greater impact on other cities. (3) In 2030, under the ecological protection scenario, the LUCE in the YRB were the lowest, with a reduction of 2.7 × 106 tons compared to the natural development scenario, further illustrating the importance of ecological land. Compared with previous studies, this study explores the spatial correlation between LUCE in various cities of the YRB from a new perspective of social network analysis. On the other hand, it makes land use prediction for 2030 by setting different land use development scenarios. The research results have broadened the application scope of social network analysis methods, and have important practical significance for promoting carbon reduction in major river basins and scientifically formulating land use policies. [ABSTRACT FROM AUTHOR]

[Display omitted] • The decrease of carbon storage is mainly affected by construction land. • In 2030 and 2050, carbon reserves in Henan Province will continue to decrease. • Clarify the scenario of effectively maintaining carbon storage. • Some policy recommendations for carbon management in Henan Province are proposed. The carbon storage service of terrestrial ecosystems has an veritable impact on the global carbon cycle and, in turn, on global climate change. Hence, both assessing and predicting the impact of land use changes on carbon storage are necessary to reduce carbon emissions and mitigate climate change. Therefore, using integrated valuation of ecosystem services and tradeoffs (InVEST) model with remote sensing data, this study systematically analyzes the land use/cover change (LUCC) and the carbon storage response characteristics of land types in Henan Province, China in the 1990–2020 period. The study also uses patch-generating land use simulation (PLUS) model to predict the LUCC and carbon storage in Henan Province from 2023 to 2050 under different scenarios, including Business as Usual (BAU), Ecological Conservation (EC), and Urban Development (UD) scenarios. The following results are noted: (1) The LUCC mainly comprises the conversion of farmland to construction land. Presently, Henan Province's carbon storage is found to have decreased by 339.72 Tg due to LUCC, which is characterized as "high in the west and low in the east." (2) Regarding the three aforementioned scenarios, the province's construction land is predicted to increase to its greatest extent under the UD scenario. Under the EC scenario, its woodland and farmland areas will be effectively protected. Therefore, the highest level of carbon reserves will likely be found in the EC scenario, followed by that in the BAU scenario, while the lowest level of carbon reserves should be seen in the UD scenario. The carbon reserves of Henan Province in 2050 will be 312.07 Tg, 233.43 Tg, and 394.49 Tg lower than that in 2020 under the BAU, EC, and UD scenarios, respectively. In sum, this study provides the scientific basis of the decisions aimed at the facilitation of low-carbon development, the optimal utilization of land spaces, and the development of an ecological civilization in Henan Province. [ABSTRACT FROM AUTHOR]

• A framework is proposed to integrate machine learning, ecological footprints and PLUS models. • Coupling of multiple data sources with machine learning algorithms improves classification accuracy. • The random forest algorithm is optimal for comparison accuracy. • Improved ecological footprint models to improve the accuracy of ECC. • Restoration of forest land with the highest ECC potential. Ecological carrying capacity is key to evaluating sustainable development capacity, and land use change has varying degrees of impact on ecosystems. This study explores the ecological carrying capacity based on land use change, which is important for the conservation and scientific and rational use of ecosystems. Therefore, in this study, three machine learning classification 3algorithms, namely support vector machine, random forest and artificial neural network, were selected for accuracy comparison and analysis based on multi-source data, using Southwest Guangxi Karst-Beibu Gulf as the study area. The Patch-generating Land Use Simulation Model is used to dissect the spatial and temporal changes in ecological carrying capaciyt from 1990 to 2040 and future trends. The results showed that (1) Coupling multiple sources of data and machine learning classification algorithms can ultimately improve land use classification accuracy. The RF is compared and found to be the optimal classification algorithm for this study. (2) The area of arable and grassland gradually decreases between 1990 and 2040, mainly encroached upon by build land; the area of forested land gradually recovers, the watershed fluctuates up and down, and the area of build land gradually increases. (3) The ecological carrying capacity from 1990 to 2040 shows a trend of decreasing and then increasing, and the area of low and medium–low decreases from 2020 to 2040, with arable land and forest land having a stronger potential to increase ecological carrying capacity. Nanning City, Qinzhou City and Chongzuo City are severely damaged. The framework provides an effective tool for exploring future ecological carrying capacity to support the ecological conservation and future sustainable development of the region. [ABSTRACT FROM AUTHOR]

• The spatial and temporal variation of ecosystem service value (ESV) was reflected. • Identifying key influencing factors of ESV by using Deep Forest model. • The PLUS model was used to simulate the future trends of ESV under five SSPs scenarios. The ecosystem services value (ESV) is an important basis for measuring ecological environment quality and efficient management of ecosystems. Although there have been many studies devoted to the measurement of ESV, the research on the key influencing factors of ESV and the prediction of future development scenarios is still limited. This study coupled the Deep Forest model and Patch-generating Land Use Simulation (PLUS) model to identify the key factors of ESV, and simulated the change trend of ESV under the Shared Socioeconomic Pathways (SSPs). Taking the cluster cities around the Yellow River floodplain area as the research object, this study quantitatively analyzed the spatiotemporal evolution characteristics of its ESV from 2000 to 2020, and identified the key factors affecting ESV using the Deep Forest model. The results showed that: (1) The ESV showed an overall upward trend from 2000 to 2020, with strong spatial heterogeneity; (2) The key factors affecting ESV were construction land ratio, distance to railway, SHDI, etc.; (3) The best development pathway of ESV in 2025, 2030 and 2035 would be SSPs5, SSPs2 and SSPs4 respectively. This study can provide theoretical support for the management of maximizing the overall benefits of ecosystem services in the study area. [ABSTRACT FROM AUTHOR]

[Display omitted] • Relative effects of climate change and anthropogenic activities on paddy expansion in NSP were studied. • Four indicators based on scenario analysis and PLUS model were used to analyze the relative importance and combined effects. • Climate change played slightly larger effect than anthropogenic activities on regional paddy field expansion. • Anthropogenic activities contributed more than climate change to paddy field expansion in most grids. Since the changes in paddy areas would significantly affect food security and agricultural sustainability, it has received worldwide attention guided by the United Nations 2030 Sustainable Development Goals. However, the process of paddy field change was complex, which was affected by both climate change and anthropogenic activities. Most existing studies focused on the spatial–temporal evolution of paddy field in different regions, while the quantitative separation of climatic and anthropogenic contributions to paddy field expansion was rare but imperative. This study adopted the patch-generating land use simulation (PLUS) model to simulate the paddy field expansion under different scenarios. Based on satellite-based land use data, meteorological data, socioeconomic data, physical geographical data, and transport data, it proposed four indicators, including ACI (anthropogenic contribution index), CCI (climatic contribution index), RII (relative importance index), and CEI (combined effects index) to quantitatively disentangle the climatic and anthropogenic contribution at different scales, and further determined the relative importance and combined effects of climate change and anthropogenic activities. These indicators were applied to the case of northern Sanjiang Plain of China and found that the total area of paddy fields in this area expanded greatly from 2638.88 km2 in 1995 to 19363.80 km2 in 2020. 1) At the regional scale (the northern Sanjiang Plain of China), the effect of climate change was slightly larger than that of anthropogenic activities on the paddy field expansion, with an inhibitory interactive effect of climate change and anthropogenic activities. 2) At the city scale (Hegang, Jiamusi and Shuangyashan), the effect of climate change was slightly stronger than anthropogenic activities in Hegang and Jiamusi, whereas Shuangyashan was the opposite. 3) At the county scale (15 counties), paddy field expansion of the central NSP was dominated by anthropogenic activities, while the northern part was disturbed more by climate change. 4) At the grid scale (30-m resolution), 51.17% of the grids had anthropogenic activities contributing more than climate change to paddy field expansion, and 88.60% of the grids presented an inhibitory interactive effect of climate change and anthropogenic activities. Thus, the indicators established for in this study can not only provide a better understanding of the relative effects of climate change and anthropogenic activities on paddy field expansion, but also give some policy implications for sustainable agricultural practice in both China and other developing countries. [ABSTRACT FROM AUTHOR]

• Cropland and built-up land were the most significant changed from 2000 to 2020. • Carbon storage was clustering and lost 47.96×106Mg from 2000 to 2020. • Simulated carbon storage (under different scenarios) were lower than that in 2020. • Ecological priority scenario is the most suitable path for future planning. • Optimization of cropland, built-up land and wetland are effective measures. Changes in land use and land cover (LULC) promote regional carbon storage capacity or trigger carbon depletion, which in turn exhibited significant impact on global climate change. Understanding the impacts of LULC on changes of carbon storage in coastal areas plays a critical role in the conservation of regional ecosystems and sustainable socio-economic development. The present study acted the coastal area of Shandong Province as an example to analyze the relationship between LULC and carbon storage combined with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Patch-generating Land Use Simulation (PLUS) model. We further predicted the variation of carbon storage through the change of LULC types under three scenarios in 2030. Our results showed that cropland (which decreased by 9.41%) and built-up land (which increased by 7.66%) underwent the most significant changes over the past 20 years, while forest, grassland, wetland, water and bare land underwent less changes. As the dominant land type, cropland was also the most important carbon pool with medium carbon storage. Areas with high carbon storage were distributed in the mountains and hills, where the main land types were grassland and forest. In addition, wetland located in the Yellow River Delta also stores large amounts of carbon. Accordingly, areas with low carbon storage were widely distributed in built-up land of urban metropolitan regions. We pinpointed that the carbon storage in the coastal area of Shandong Province lost 47.96×106Mg due to the increasing of built-up land and the decreasing of cropland and forest, while ecological protection measures would effectively enhance regional carbon storage. Specifically, the regional carbon storage could be increased by 6.64×106Mg when the conversion of cropland, forest and grassland into built-up land was reduced by 20% and the conversion of wetland and water into built-up land was reduced by 30% (under the ecological priority scenario (EP)). We believe the present study could be a valid reference for administrators to develop policies in more reasonable planning of land use and urban development to achieve carbon peaking and carbon neutrality ("Dual Carbon" goals). [ABSTRACT FROM AUTHOR]

[Display omitted] • Integrating the Ecological Security Pattern and the PLUS Model. • The impact of future land changes on wetland landscape patterns. • Establish wetland ecological networks and identify potential key points. • The results of the study can guide the planning of eco-cities. The construction of wetland ecological security pattern has important guiding significance for balancing urban development and ecological restoration. In this paper, the PLUS model was used to simulate the land use change under the business as usual scenario (BAU), economic development scenario (ED) and expansionary conservation scenario (EC) in 2030. Coupled with the wetland ecological security pattern, four wetland ecological networks were constructed for vertical and horizontal comparative analysis. The optimal network was selected and ecological pinch points and obstacles were identified. The results showed that: (1) The land use change mainly occurred in the main urban area of Haikou. Under BAU and ED scenarios, the area of construction land increased greatly. Under EC scenarios, the overall ecological land in Haikou would expand, but the area of wetland showed a downward trend. (2) In 2030, the overall ecological wetland network will be improved, the number and length of corridors will increase significantly, and the network structure under EC scenario will be more stable. (3) The number and area of ecological pinch points and obstacle points under the EC scenario in 2020 and 2030 increased significantly, and this area should be regarded as a priority area for ecological protection. This study provides a new perspective for ecological protection and restoration, and provides a reference for clarifying the direction of wetland ecological restoration work and formulating urban construction and development policies. [ABSTRACT FROM AUTHOR]

• Jinan City is a typical with contradictions between development and protection. • Fusion of Markov Chain Model and Path-generating Land Use Simulation Model. • Major factors driving the changes of urban green space in Jinan City are explored. • Simulated predictions under free inertia scenario and ecological protection scenario. • Unused land is the key to solving the contradictions. The study of long-term changes to urban green space reveals the reasons for changes in the spatial pattern of urban green space and predicts the future development trends, which is of great importance for urban green space protection and integrated urban development. This study used Markov Chain and PLUS models to explore the spatial and temporal patterns of changes to green space in urban and rural areas in Jinan City during recent rapid urbanization and the driving forces behind them. The results show that from 2000 to 2020, the decrease in urban green space in Jinan City slowed down gradually, and that elevation and population density were the primary factors influencing changes in urban green space. In the simulation projections, the ecologically protected development scenario had a relatively low rate of site change and was more protective of arable land and green space. Ecological conservation development was predicted to result in a decrease in unused urban land and to reflect the advantages of intensive land use. The findings will provide decision-makers with ideas related to the sustainable development of urban green space. [ABSTRACT FROM AUTHOR]

• We propose a framework for predicting regional land use carbon emissions. • The case of UANSTM illustrates how this framework can guide future spatial planning. • Grassland plays a main role in the carbon neutrality of UANSTM. • It is expected to achieve carbon peaking in UANSTM around 2028. Changes in land use significantly contribute to carbon emissions and other environmental problems. Regional carbon emissions changes from land use have been affected by rapid urbanization. To dynamically assess land use change and the spatiotemporal characteristics of carbon emissions from 1990 to 2020, this study used the PLUS, grey back-propagation neural network, and related carbon emission accounting models as well as four distinct 2030 scenario simulations. According to the findings, the urbanization of the urban agglomeration on the northern slope of the Tianshan Mountains (UANSTM) developed rapidly from 1990 to 2020 with a noticeable transfer of diverse types of land. In particular, the quantity of construction land and cropland belonging to carbon source land increased by 153.271% and 55.072% respectively. Simultaneously, carbon emissions showed a trend of continuous increase and demonstrated an S-shaped curve growth, with relatively rapid growth from 2000 to 2015, that has tended to be stable in recent years. If this carbon emission trend continues, an inflection point will appear around 2028. Land use simulations for 2030 reveal that the ecological security (ES) scenario, which slows the expansion of construction land and cropland while increasing ecological land, is most likely to reduce the negative environmental consequences of urbanization. This is because higher potential peak carbon emissions per unit area that may be obtained with carbon sink land. Consequently, the ES scenario of the study region is comparable to the future urban agglomeration development model. The results provide a reference for territorial space planning and dual carbon target recommendations in the UANSTM. [ABSTRACT FROM AUTHOR]

• Exploration and forecast of the spatiotemporal changes from 2000 to 2060 in four cultural heritage protected cities. • Urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity. • Altitude, socioeconomic conditions, and land policies are all important influencing factors. • Land use pattern and the landscape pattern will become more complex significantly in the future. In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal changes from 2000 to 2060 in Pingyao, Gucheng, She and Langzhong, where the Four Ancient Cities of China are located. First, we found the spatiotemporal changes and the driving factors with land use transfer matrix, landscape metrics and a random forest analysis strategy. Furthermore, we simulated and predicted the spatiotemporal patterns in 2030 and 2060 by applying a CA model and landscape indexes, testing the carbon peak and carbon neutralization target achieved. The results demonstrate that urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity, as well as adversely affecting the landscape pattern of ecological land. Altitude, socioeconomic conditions, and policies regarding the development and utilization of land resources all significantly impact the four cities' spatiotemporal changes. Both the land use pattern and the landscape pattern will become more complex significantly in the future. This study offers a new insight to compare and analyze the spatiotemporal changes of different CHPCs. [ABSTRACT FROM AUTHOR]

• A multi-scenario ecosystem service value assessment framework for mining-dominated watersheds was established. • Ecosystem service value change was evaluated under four development models. • The role of mining activities in affecting land use/cover change characterized by grassland and cropland loss. Exploring future land use/cover change (LULC) and ecosystem service values (ESV) dynamics is crucial for sustainable development from regional to global scales. However, ESV dynamics is significantly affected by economic development and policy changes, and future projections of ESV are generally characterized by large uncertainties due to complexity in LULC dynamics. Mining activities are supposed to exert significant effects on ESV dynamics, while the patterns and controls of ESV in mining-dominated basins are still less understood, especially under different land-use scenarios. Here, based on multi-source remote sensing data and land-use data in the Fenhe River Basin, we integrated the SD model, Markov model and PLUS model to simulate LULC in the Fenhe River Basin under four scenarios, i.e., the economic development priority (EDP), natural development priority (ND), cultivated land protection priority (CLP), and ecological protection priority (EPP). Based on ESV equivalent coefficient method and geographical detector, we further determined the patterns and controls of ESV. Results showed that construction land and cultivated land were mainly concentrated in the central parts of the basin, and grassland and woodland were concentrated in the edge area of the basin. Over the past two decades, construction land and woodland have experienced significant expansion, while the areas of grasslands and cultivated lands have declined due to mining activities. The high-value and sub-high-value areas of ESV were concentrated in woodland, grassland, reservoir and concentrated water area of mainstream and tributary. The low-value area was mainly located in the gathering area of construction land. The total ESV showed a downward trend with time, and the highest decline in the total ESV under the four land use scenarios was the EDP, while the lowest drop was the EPP. The highest contribution rate of ESV was woodland, which was equivalent to the contribution rate of cultivated land, grassland and water area, totally accounting for 58.54% of the whole ESV. The geographical detector method indicated that distance to the residential area, soil erodibility, distance to the river, soil type and annual average temperature were the main driving factors affecting the spatial patterns of ESV. Our results highlighted the fundamental role of mining activity in affecting LULC characterized by grassland and cultivated land shrinkage, and suggested that mining areas rehabilitation should be given priority in terms of further improving ESV in mining-dominated basins. [ABSTRACT FROM AUTHOR]

• Analysis on Land Use Change of Terrestrial Ecosystem. • Determine the relationship between different land types and driving factors. • Analyze the spatial and temporal changes of carbon stocks from 2000 to 2030. • The change of carbon storage caused by land type change was studied and analyzed. As the largest global carbon pool system, terrestrial ecosystems have an important role to maintain the stability of ecosystems. Human activities affect the structural changes in the ground surface and interfere with terrestrial ecosystem evolution, and consequently, carbon stock is changed in the region. Therefore, forecasting future carbon stock changes under different land use scenarios has important research implications for promoting stable evolution and cycling of terrestrial ecosystems. This study is conducted with the land use data from 2000 to 2020, and incorporates the Patch-generating Land Use Simulation model with the Integrated Valuation of Ecosystem Services and Trade-Offs model to analyze the changes in land use in Hefei, and its influence on the carbon stock in Hefei in various scenarios. During the study period, the mutual conversion between different land types in Hefei City made the land structure change within the study area more significant. The rapidly evolving surface structure is the reason for the decrease of carbon storage in terrestrial ecosystems, with a cumulative decrease of 1.2 × 108 t. The spatial distribution in carbon storage in the study area shows a distribution pattern of low in the north and high in the south. The high carbon storage area is obviously banded in the study area. The area with obvious changes in surface structure has more obvious changes in carbon storage. Compared with the natural development scenario, the downward trend of carbon storage in the ecological protection scenario and the comprehensive development scenario has slowed down due to the restrictions on the structural transformation of land types and the implementation of relevant ecological protection policies. Therefore, this study will support the future management and policy making of Hefei City with the background of China's "double carbon" target and the significant position of Hefei City. [ABSTRACT FROM AUTHOR]

[Display omitted] • Land use/cover change characterized by cropland loss and expansion of other lands. • Urbanization grew exponentially, while other land changes peaked in 1995–2005. • Land use/cover had two conversion patterns before and after 175 m impounding. • Cropland will drop by 1094 km2 by 2030, which is mainly converted to built-up land. • Most land use/cover changes are altitude-sensitive and supplemented by other factors. Coordination of economic development and ecological conservation in land use/cover (LULC) remains a great challenge, particularly in eco-fragile areas. A holistic understanding of LULC change is a premise for coordinating the conflict. In this study, we elucidated the spatiotemporal evolution of LULC in China′s typical eco-fragile area-the Three Gorges Reservoir area during different periods of Gezhou Dam-Three Gorges Dam (GZD-TGD) construction and impoundment (1982–2020), and predicted LULC in 2030 with the patch-generating land-use simulation (PLUS) model. In 1982–2020, the LULC changes mainly included cropland loss, forestland restoration, urban development and water expansion, among which cropland decreased by 4688 km2, while forestland, built-up land and water increased by 3273, 1002 and 272 km2, respectively. For most LULC types, the most significant change occurred in 1995–2005, whereas the built-up land increased exponentially from 0.41% to 5.06% during the entire study period, which was mainly derived from cropland. Under a natural development scenario, cropland would drop continuously by 1094 km2 till 2030. In addition, there were significant interconversions between various land types before GZD-TGD impoundment of 175 m, particularly vegetation, while only built-up land increased dramatically by occupying 2.66% of cropland thereafter. Contributions of various driving factors to LULC changes varied across different periods due to the direct/indirect effects of GZD-TGD construction and impoundment. Most changes in LULC were elevation-sensitive, and supplemented by other factors. Furthermore, the expansion of various LULC types tended to occur more often in areas with low elevations and gentle slopes. The results may assist decision-makers in formulating more reasonable policies to alleviate the conflicts between land utilization and ecological protection, and facilitate the realization of China′s ecological civilization construction goals. [ABSTRACT FROM AUTHOR]

• The LER pattern has significant positive spatial autocorrelation, but the autocorrelation decreases with the development of the city. • Ecological driving factors are the main driving factors of landscape ecological risk pattern, but the impact of social driving factors on LER is growing with time. • Under different scenarios in 2030, the spatial and temporal changes of landscape ecological risk are various. Urban land has been expanding under the background of rapid urbanization, which leads to the increasingly prominent problem of regional ecological security in multi-mountainous cities. In order to scientifically formulate land use policies and maintain regional ecological security pattern, it is necessary to assess regional landscape ecological risk (LER), explore its influencing factors, and simulate the LERs under different scenarios in the future. This study takes Guiyang, a typical mountainous city in the karst area of southwest China, as the study area. Based on the three-phase remote sensing images, the landscape pattern index and the Geodetector method (GDM) were used to assess LER and the corresponding driving factors from 2000 to 2020, and the PLUS model was used to simulate LER under different urban development scenarios in 2030. The results showed: (1) The average landscape ecological risk index (LERI) in 2000, 2010, and 2020 were 0.0341, 0.0320, and 0.0304, respectively. This shows that the overall LER of Guiyang is low and gradually decreases over time. (2) The LER pattern has significant positive spatial autocorrelation, but the autocorrelation decreases with the development of the city. (3) From 2000 to 2020, ecological driving factors were the main influencing factors of LER, but the impact of social driving factors on LER was growing with time. (4) The LER change of Guiyang in 2030 varies significantly under different scenarios, among which the area of the risk up zone in the natural development scenario is the largest, followed by the farmland protection scenario, and the ecological priority scenario is the smallest. This study will provide a scientific basis and reference for the overall development planning of multi-mountainous cities, regional ecological protection planning, and the formulation of relevant land use policies. [ABSTRACT FROM AUTHOR]