Land Use Simulation Research Articles

Retreat from flood zones: Simulating land use changes in response to compound flood risk in coastal communities

Coastal communities are increasingly vulnerable due to sea level rise and population growth. Managed retreat is commonly recognized as a strategy that yields multifaced benefits in community adaptation. However, limited studies have explored the cumulative effects of sea level rise, population migration, and managed retreat on the community resilience. This study presents a parcel-level land use change model to analysis land-based flood mitigation strategies in Galveston County, Texas. The developed model integrates a Gradient Boosting Decision Tree with a flood risk model and diverse datasets. Our model results reveal the spatial patterns of urban development in Galveston under different relocation policies and the compounding impacts of sea level rise and population growth. Our findings illustrate that elevating the first floors of buildings can significantly mitigate flood risks and associated relocation costs. The private adaptation measure, together with government-led buyout policies, could foster a shift toward more resilient urban development and yield a more affordable relocation strategy. Our findings emphasize the need for a multidisciplinary approach in building resilient coastal communities, particularly in the face of escalating climate risks in local communities.

Land-use simulation for synergistic pollution and carbon reduction: Scenario analysis and policy implications

Simulations of sustainable land use and management are required to achieve targets to reduce pollution and carbon emissions. Limited research has been conducted on synergistic pollution and carbon reduction (SPCR) in land-use simulations. This study proposed a framework for land-use simulation focused on SPCR. The non-dominated sorting genetic algorithm (NSGA-Ⅱ) and the entropy weight-based technique for order of preference by similarity to an ideal solution (TOPSIS) were used to optimize the land-use structure according to minimum net carbon, nitrogen, and phosphorus emissions. The cellular automata (CA) Markov model was then utilized to simulate the land-use spatial pattern according to the optimal conditions. The proposed framework was applied to the Dongjiang River Basin, South China, and three other scenarios (natural development (ND), carbon minimization (CM), and pollution minimization (PM)) were designed to validate the effectiveness of pollution and carbon emissions reduction under the SPCR scenario. The land-use structure and the pollution and carbon emissions in the scenarios were compared. The results showed the following. (1) The proportions of cultivated land, woodland, grassland, water, and construction land In the SPCR scenario accounted for 14%, 72%, 4%, 3%, and 7% of the total area, respectively. The carbon, nitrogen, and phosphorus emissions were 42.4%, 6.6%, and 7.8% lower, respectively, in the SPCR scenario than in the ND scenario, demonstrating the advantages of simultaneous pollution and carbon reduction. (2) The kappa coefficient of the CA-Markov model was 0.8729, indicating high simulation accuracy. (3) The simulated land-use spatial patterns exhibited low spatial heterogeneity under the CM, PM, and SPCR scenarios. However, there were significant disparities between the ND and SPCR scenarios. The cultivated and construction land areas were significantly smaller in the SPCR scenario than in the ND scenario. In contrast, the woodland and grassland areas were larger, with most differences in the central and southwestern regions of the Dongjiang River Basin. The results of the current study can be used to formulate effective land use policies and strategies in the Dongjiang Basin and similar areas to achieve the Coupling coordination between pollution reduction and carbon reduction. Policy recommendations include increasing the proportion of woodland and grassland, implementing reasonable constraints on expanding cultivated and construction lands, and establishing farmland red lines to promote synergistic pollution and carbon reduction.

An Optimization Strategy for Provincial “Production–Living–Ecological” Spaces under the Guidance of Major Function-Oriented Zoning in China

The comprehensive evaluation of China’s major function-oriented zoning, grounded in scientific principles, has evolved into a nationwide initiative aimed at promoting regional coordinated sustainable development. A pivotal focus during this transitional phase is the optimization of a “production–living–ecological” spatial pattern within the main national functional areas. This involves a meticulous examination of the main functions, encompassing the distinct categories of production, living, and ecology, as well as prioritizing scenarios aligned with the functional orientation of towns, agriculture, and ecology in land-use simulation. Utilizing the PLUS model’s land-use simulation technology, a detailed investigation into Anhui Province’s main function orientation was conducted to achieve an optimal simulation of the “production–living–ecological” spatial pattern. The findings underscore the inadequacy of a singular scenario in attaining a global optimal solution for simulating the three spaces of production, living, and ecology. However, a gradual stabilization was observed in the overall quantitative structure and spatial transition frequency of these three spaces in Anhui Province. The continuous optimization of local spatial patterns and functional layouts was achieved through a multi-scenario optimization simulation based on main function orientation. Noteworthy improvements were identified in the optimization of the three spaces in specific regions: the northern part of Anhui, urban living spaces around Hefei and Wuhu, and ecological spaces in southern and western Anhui. Crucially, the simulation results align with the strategic goal orientation of the provincial main functional areas, the optimization trajectory of the “production–living–ecological” spatial pattern, and the strategic imperative for the coordinated and sustainable development of territorial space in Anhui Province. These findings furnish a robust scientific foundation for decomposing and transmitting the core indicators of provincial territorial spatial planning, as well as delineating the “three zones and three lines” in municipal territorial spatial planning.

Dynamic Simulation of Land Use and Habitat Quality Assessment in Baiyangdian Basin Using the SD-PLUS Coupled Model

The physical foundation and environmental assurance provided by the regional habitat are crucial for the survival and sustainable development of organisms. Land use change, as a significant manifestation of human activity, is a crucial factor in habitat quality. An SD-PLUS coupled model was developed to simulate land use change in the Baiyangdian(BYD) Basin using data on land use, socio-economic factors, and the climatic environment from 2000 to 2020. The InVEST model was employed to assess the habitat quality of the basin from 2000 to 2050. The findings indicated the following: Between 2020 and 2050, the predominant land use changes across the three scenarios involve the conversion of farmland to construction land and grassland to woodland. The magnitude of these changes steadily declines over time. The magnitude of change in land use for all kinds was greater under SSP5 compared to SSP1 and SSP2. The movement of habitat quality grades primarily occurred from higher grades to lower grades. In 2050, the habitat quality is projected to improve compared to 2020 under three different scenarios. The highest improvement is expected in SSP5 with a 0.60% increase, followed by SSP2 with a 0.42% increase and SSP1 with the smallest increase of 0.23%.

Carbon storage and sequestration in a eucalyptus productive zone in the Brazilian Cerrado, using the Ca-Markov/Random Forest and InVEST models

Tropical ecosystems in Brazil, particularly Mato Grosso do Sul, possess substantial greenhouse gas (GHG) mitigation potential through carbon sequestration in tree forests. However, the expansion of agricultural activities poses a threat to this potential. Notably, eucalyptus forests could enhance carbon sequestration and reduce GHG emissions. This study focused on Três Lagoas, known as Brazil's cellulose capital, and aimed to evaluate carbon stock and sequestration for 2030 under business as usual (BAU) and protected forest (PF) scenarios. Combining Cellular Automata (CA) and Random Forest models implemented in Patch-Generating Land Use Simulation (PLUS) and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, we simulated land use scenarios and assessed ecosystem services generated by carbon sequestration. The results showed that the PF scenario indicated a higher total carbon stock than the BAU scenario, with a difference of 2.48 Tg. Carbon sequestration varied by period and scenario. Between 2010 and 2020, 3.88 Tg of carbon were sequestered. However, in the next period (2020–2030), the BAU scenario estimated 2.45 Tg in total carbon sequestration. In contrast, the PF scenario predicted 4.93 Tg of carbon sequestration for 2020–2030, surpassing the previous decade. Monetarily, carbon sequestration in 2010–2020 amounted to $92.48 million, decreasing to $58.49 million for 2020–2030 in the BAU scenario. In the PF scenario, sequestration for 2020–2030 increased to $ 117.43 million, nearly double that of the BAU scenario. In conclusion, combining the Ca-Markov/Random Forest and InVEST models revealed the spatiotemporal dynamics of carbon stock and sequestration in the municipality with the largest eucalyptus-planted area in Brazil. The results underscore the significant variability in carbon stocks and sequestration based on classes, periods, and scenarios analyzed. This study contributes valuable insights into the potential for carbon mitigation in this critical region.

Quo vadis, smallholder forest landscape? An introduction to the LPB-RAP model.

The impacts of the Anthropocene on climate and biodiversity pose societal and ecological problems that may only be solved by ecosystem restoration. Local to regional actions are required, which need to consider the prevailing present and future conditions of a certain landscape extent. Modeling approaches can be of help to support management efforts and to provide advice to policy making. We present stage one of the LaForeT-PLUC-BE model (Landscape Forestry in the Tropics-PCRaster Land Use Change-Biogeographic & Economic model; in short: LPB) and its thematic expansion module RAP (Restoration Areas Potentials). LPB-RAP is a high-resolution pixel-based scenario tool that relies on a range of explicit land use types (LUTs) to describe various forest types and the environment. It simulates and analyzes future landscape configurations under consideration of climate, population and land use change long-term. Simulated Land Use Land Cover Change (LULCC) builds on dynamic, probabilistic modeling incorporating climatic and anthropogenic determinants as well as restriction parameters to depict a sub-national regional smallholder-dominated forest landscape. The model delivers results for contrasting scenario settings by simulating without and with potential Forest and Landscape Restoration (FLR) measures. FLR potentials are depicted by up to five RAP-LUTs. The model builds on user-defined scenario inputs, such as the Shared Socioeconomic Pathways (SSP) and Representative Concentration Pathways (RCP). Model application is here exemplified for the SSP2-RCP4.5 scenario in the time frame 2018-2100 on the hectare scale in annual resolution using Esmeraldas province, Ecuador, as a case study area. The LPB-RAP model is a novel, heuristic Spatial Decision Support System (SDSS) tool for smallholder-dominated forest landscapes, supporting near-time top-down planning measures with long-term bottom-up modeling. Its application should be followed up by FLR on-site investigations and stakeholder participation across all involved scales.

Dynamics of Land Use/Land Cover Considering Ecosystem Services for a Dense-Population Watershed Based on a Hybrid Dual-Subject Agent and Cellular Automaton Modeling Approach

Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions, leading to potential conflicts among natural and human-related issues as well as among stakeholders. This study introduced economic standards for farmers. A hybrid approach (CA-ABM) of cellular automaton (CA) and an agent-based model (ABM) was developed to effectively deal with social and land-use synergic issues to examine human–environment interactions and projections of land-use conversions for a humid basin in south China. Natural attributes and socioeconomic data were used to analyze land use/land cover and its drivers of change. The major modules of the CA-ABM are initialization, migration, assets, land suitability, and land-use change decisions. Empirical estimates of the factors influencing the urban land-use conversion probability were captured using parameters based on a spatial logistic regression (SLR) model. Simultaneously, multicriteria evaluation (MCE) and Markov models were introduced to obtain empirical estimates of the factors affecting the probability of ecological land conversion. An agent-based CA-SLR-MCE-Markov (ABCSMM) land-use conversion model was proposed to explore the impacts of policies on land-use conversion. This model can reproduce observed land-use patterns and provide links for forest transition and urban expansion to land-use decisions and ecosystem services. The results demonstrated land-use simulations under multi-policy scenarios, revealing the usefulness of the model for normative research on land-use management.

Simulation and attribution analysis of terrestrial ecosystem carbon storage of Hainan Island from 2015 to 2050

Terrestrial ecosystem carbon storage (TECS) could significantly affect the concentration of atmospheric CO2, which is critical for climate change prediction. Along these lines, the Integrated Valuation of Ecosystem Services and Trade-offs model was employed to determine the TECS of Hainan Island (HN) from 2015 to 2050 accurately. Besides, the Future Land-use Simulation model combined with natural and anthropogenic factors was used to forecast the land-use types from 2025 to 2050 in HN by considering different Shared-socioeconomic pathway-Rrepresentative concentration pathway (SSP-RCP) scenarios. Finally, the geographical detector explored the influence mechanism concerning the TECS. Under the SSP1-RCP1.9 scenario, the TECS of HN will be gradually increased to 388.10 million tons in 2050, mainly due to the increase in forest areas and the fact that the majority of grassland in the western part of HN is being converted into forest. Under different SSP-RCP scenarios except for SSP1-RCP1.9, HN's TECS is expected to gradually decrease from 2015 to 2050, mainly due to the loss of grassland and forest in coastal low-altitude areas. From the single/pair factor perspective influenced mechanism concerning the TECS, the elevation (DEM) and DEM∩Slope were found to be the dominant single/pair factor under the SSP1-RCP1.9, SSP1-RCP2.6 and SSP2-RCP4.5 scenarios. The least distance to residential area (LDP) and LDP∩LDR (i.e. LDP and least distance to roads or railways) were found to be the dominant factors under the SSP3-RCP7.0, SSP4-RCP3.4, SSP4-RCP6.0, SSP5-RCP3.4 and SSP5-RCP8.5 scenarios. Besides, the pair factors provided a higher determinant power for TECS than a single factor. Given the results of the TECS and the influence mechanism concerning the TECS under different SSP-RCP scenarios, we suggest reasonably planning the transportation network and limiting the disorderly expansion of construction land.

Optimizing Land Use for Carbon Neutrality: Integrating Photovoltaic Development in Lingbao, Henan Province

This study aims to examine the impact of land use variations on carbon emissions by incorporating the development of photovoltaics as a scenario. To meet this end, we investigate the carbon emissions fluctuations resulting from different development scenarios: natural development, low-carbon strategies, and widespread adoption of photovoltaic technology. We identify important influencing factors related to these changes and utilize multi-objective optimization and the PLUS model to simulate land use patterns in Lingbao City projected for 2035, with a focus on achieving carbon neutrality. Through multiple scenarios, we analyze differences in carbon emissions, economic benefits, ecological impacts, and land use allocations. Our findings demonstrate that the photovoltaic scenario leads to a substantial 3500-ton reduction in carbon emissions and boosts overall benefits by RMB 85 million compared to the low-carbon scenario. This highlights the significant role of photovoltaic systems inefficient land utilization, meeting carbon emission targets, and generating economic gains. This research explores the relationship between land use alterations and carbon emissions, aiming to achieve ambitious carbon reduction objectives by integrating photovoltaic applications across diverse land types. It provides fresh perspectives for examining urban land utilization and strategies to reduce carbon emissions.

Spatiotemporal Dynamics of Ecosystem Service Balance in the Beijing-Tianjin-Hebei Region and Its Ecological Security Barrier with Inner Mongolia

In the context of the global decline in the capacity of ecosystem services (ESs) to meet increasing human demands, assessing and quantifying ESs is crucial for ecological policy formulation. To address this, our study employs an adjusted land-use matrix method and the patch-generating land-use simulation (PLUS) model for a quantitative analysis of the ES balance in the Beijing–Tianjin–Hebei–Inner Mongolia (JJJM) region from 2000 to 2020, projecting to 2040. Focusing on the JJJM region, a focal area for ecological policy exhibits significant socioeconomic disparities, revealing a synergistic interplay in the ESs balance. Areas with high vegetation cover, like forests and grasslands, demonstrate an elevated ESs balance, with Inner Mongolia having the highest total ESs balance at 71.40. Conversely, highly urbanized areas, such as Beijing and Tianjin, face deficits in the ESs balance, with Tianjin recording the lowest at 17.83. Our results show an upward trend in total ESs balance in the JJJM region (slope: 0.08 year−1). In particular, regulating services are declining (slope: −0.04 year−1), cultural services are increasing (slope: 0.08 year−1), and provisioning services remain relatively stable. Projecting to 2040, our analysis indicates a slight decline in ESs balance, attributed to Inner Mongolia’s urban expansion. This emphasizes the need for industrial transfers and proactive urbanization promotion to enhance ESs balance and support sustainable management and ecological civilization development in the JJJM region.

A cellular automata model coupled with partitioning CNN-LSTM and PLUS models for urban land change simulation

Urbanisation is a key aspect of land use change (LUC), and accurately modelling of urban LUC is crucial for sustainable development. Cellular automata (CA) are widely used in LUC research. However, previous studies have overlooked the significant temporal dependence and spatial heterogeneity associated with LUC. To address these gaps, this study proposes a novel model called KCLP-CA, which integrates k-means, a convolutional neural network (CNN), a long and short-term memory neural network (LSTM), and the popular patch-generation land use model (PLUS). Initially, k-means and CNN are utilised to address spatial heterogeneity, while LSTM tackles temporal dependence. The LSTM and land expansion analysis strategy (LEAS) models of PLUS are employed to obtain land use conversion probability maps. Finally, a simulation of land use dynamic change was conducted using a linear weighted fusion conversion probability map that accounts for random factors. To validate the KCLP-CA model, land use data collected from Hangzhou between 1995 and 2000 were employed. The results showed that the KCLP-CA model outperformed traditional methods, including artificial neural networks and random forest model, with the figure of merit (FoM) index increasing from 2.12% to 4.19%. Random forest analysis of drivers impacting LUC revealed that distance to water and road network density exerted the greatest influence on urban land development in Hangzhou. Incorporation of various policy planning factors affecting urban development yielded simulation results aligning more closely with reality, resulting in a FoM index increase of 1.64–1.76%. In summary, the model developed in this study combines the strengths of two sub models to deliver an accurate and effective simulation of future land use.

Predicting land use change around railway stations: An enhanced CA-Markov model

Predicting land use change around railway stations is crucial for facilitating the coordinated development of transport and land use. Previous studies have seldom focused on simulating and predicting small-scale land use changes at a railway station. Therefore, this study employs an enhanced Cellular Automata-Markov (CA-Markov) model, aiming to achieve simulations and predictions with heightened precision. Firstly, two additional driving factors, namely accessibility to railway stations and the kernel density of points of interest (POIs), are incorporated into the CA-Markov model. Secondly, the validation of the enhanced model is achieved through simulating land use changes around Dujiangyan Station. Finally, this model is applied to predict land use around Mianzhu South Station in 2026, and optimization strategies for railway station areas are proposed. The results indicate an 83.43-hectare reduction in farmland area, accompanied by a moderate increase in 35.8 hectares of forest land and 41.52 hectares of residential land. This enhanced model provides valuable technical support for strategic planning in railway station areas.

Future Land Use and Flood Risk Assessment in the Guanzhong Plain, China: Scenario Analysis and the Impact of Climate Change

Continuously global warming and landscape change have aggravated the damage of flood disasters to ecological safety and sustainable development. If the risk of flood disasters under climate and land-use changes can be predicted and evaluated, it will be conducive to flood control, disaster reduction, and global sustainable development. This study uses bias correction and spatial downscaling (BCSD), patch-generating land-use simulation (PLUS) coupled with multi-objective optimization (MOP), and entropy weighting to construct a 1 km resolution flood risk assessment framework for the Guanzhong Plain under multiple future scenarios. The results of this study show that BCSD can process the 6th Climate Model Intercomparison Project (CMIP6) data well, with a correlation coefficient of up to 0.98, and that the Kappa coefficient is 0.85. Under the SSP126 scenario, the change in land use from cultivated land to forest land, urban land, and water bodies remained unchanged. In 2030, the proportion of high-risk and medium-risk flood disasters in Guanzhong Plain will be 41.5% and 43.5% respectively. From 2030 to 2040, the largest changes in risk areas were in medium- and high-risk areas. The medium-risk area decreased by 1256.448 km2 (6.4%), and the high-risk area increased by 1197.552 km2 (6.1%). The increase mainly came from the transition from the medium-risk area to the high-risk area. The most significant change in the risk area from 2040 to 2050 is the higher-risk area, which increased by 337 km2 (5.7%), while the medium- and high-risk areas decreased by 726.384 km2 (3.7%) and 667.488 km2 (3.4%), respectively. Under the SSP245 scenario, land use changes from other land use to urban land use; the spatial distribution of the overall flood risk and the overall flood risk of the SSP126 and SSP245 scenarios are similar. The central and western regions of the Guanzhong Plain are prone to future floods, and the high-wind areas are mainly distributed along the Weihe River. In general, the flood risk in the Guanzhong Plain increases, and the research results have guiding significance for flood control in Guanzhong and global plain areas.

Land-Use Optimization Based on Ecological Security Pattern—A Case Study of Baicheng, Northeast China

In the current context of global urbanization and climate change, balancing ecological protection and economic development is a particular challenge in the optimal allocation of regional land use. Here, we propose a research framework for the optimal allocation of land use that considers the regional ecological security pattern (ESP) and allocates space for land-use activities to areas with low ecological risk. Taking Baicheng, China as our study area, ecological sources were first identified by integrating their ecological importance and landscape connectivity, and ecological corridors and functional zones were extracted using the minimum cumulative resistance difference and circuit theory. The ecological source areas were then taken as limiting factors, and four future scenarios were established for 2030 using the parcel-level land-use simulator (PLUS) model. The ecological corridors and functional zones served as areas having restricted ecological conditions, and the four future scenarios were coupled into the corresponding functional zones to optimize the land-use structure in 2030. The results indicate that under the coupled ESP–PLUS scenario, the spatial distribution and structure of land use in Baicheng balance the needs of ecological source area protection and economic development, resulting in greater sustainability. By 2030, the cultivated land area will steadily increase, but attention will also be given to the protection of ecological land (e.g., woodland and marshland), aligning with current policy planning demands. An analysis of the landscape indices for each future scenario found all scenarios to be effective in reducing negative changes in landscape patterns. These findings provide a novel perspective for the rational allocation of future land resources and the optimization of land-use structures.

Simulation and prediction of land use in urban agglomerations based on the PLUS model: a case study of the Pearl River Delta, China

The Pearl River Delta (PRD) is a highly urbanized region in China that faces significant challenges in land use management. These challenges include the decrease in agricultural and ecological land resulting from rapid urbanization, the effectiveness of government governance, and the trajectory of development, all of which warrant careful research examination. Moreover, existing studies on land use in the PRD predominantly rely on static historical analysis, lacking a multi-scenario simulation approach. This study examines land use in PRD using a Patch-Generating Simulation (PLUS), from 1985 to 2020 to address this gap. Three scenarios were established to simulate potential land use outcomes in the PRD by 2030: spontaneous change, cropland protection, and ecological protection. The findings reveal that cropland, forest, and impervious surfaces are the dominant land use types in the PRD. From 1985 to 2020, the proportion of cropland decreased from 37.63% to 27.40%, with most conversions occurring to impervious surfaces and forest land. The proportion of impervious surfaces increased from 1.81% to 12.57%, primarily from conversions of cropland, forest, and water bodies. Economic development, population growth, accessibility, climatic factors, and topographic conditions were shown to be the primary determinants of land use in the PRD. Modelling results suggest that under the spontaneous change scenario, cropland and ecological land decrease, while impervious surfaces expand significantly, threatening cropland preservation and ecological construction. However, under the cropland protection scenario, the conversion rate of cropland to other land types can be effectively controlled, contributing to efficient preservation. Under the ecological protection scenario, impervious infrastructure encroachment on ecological land can be mitigated, but cropland protection is limited. The study proposes cropland protection and ecological priority policies to optimize the structure of land use, enhance efficiency, and offer policy guidance for the efficient utilization of land resources and the preservation of the ecological environment in the PRD.

Allocating payments for ecosystem services under future multiple scenarios in the Yellow River Basin, China

Reasonable payments of Ecosystem Services (PES) standards are crucial to provide eco-environment management countermeasures. However, existing research on the unified coordination of future PES from the overall perspective is insufficient. This paper proposes a framework derived from the patch-generating land-use simulation (PLUS) model and the ecosystem services value (ESV) assessment method for allocation PES funds. The Yellow River Basin (YRB) was taken as a case study, which is a highly integrated and interconnected entity. The PLUS model was used to analyze various land-use situations from 2010 to 2020, and predict future land-use status under different development scenarios including natural development (ND), cropland conservation (CC) and ecological conservation (EC). The ESV approach was applied to calculate the ESV in nine provinces of the YRB, and propose optimized fund distribution schemes. The results showed that (1) The most significant land-use changes during 2010–2020 were impervious, forests, grasslands, and croplands, where the impervious increased by 22.47 % (4642 km2) and the forest increased by 9 % (7623 km2). (2) The total ESV in the YRB will be highest under EC scenario in 2030, at 729.16 billion CNY, and Qinghai, Sichuan, Gansu and Shandong will have the highest ESV under EC scenario. (3) The funds will reach lowest under EC scenario, at 13.35 billion CNY, while reach highest under CC scenario, at 13.58 billion CNY. (4) In any scenario, Qinghai and Gansu province will get the highest PES funds among nine provinces, and financial investment in the Qinghai Province needs to be increased. Based on our results, it is recommended to foster the exploration of horizontal compensation between the downstream provinces of Henan and Shandong, and the upstream provinces of Qinghai, Sichuan, and Gansu, in order to enhance the protection of the eco-environment. The findings can provide scientific guidance for improvement of the PES funds allocation in the YRB, and methodological references for other river basins.

Anthropisation and Sustainable Management of the Sorobouly and Pâ Classified Forests in the Balé Province

The aim of this research is to study the dynamics of land use in the Sorobouly and Pâ classified forests and the factors responsible for these dynamics. These factors are both natural and anthropogenic. In the province of Balé, demographic and pastoral pressures have increased the level of degradation of the classified forests to over 20%. The methodology used is based on a diachronic analysis of Landsat images from 1998 to 2017 and on field surveys. A projection of land-use dynamics using the Markov and CA Markov cellular automaton was carried out with a view to providing decision-makers with the necessary data for decision-making. The results of image processing in 1998, 2007 and 2017 show a faster rate of degradation in the Sorobouly classified forest than in the Pâ classified forest. Dwellings and fields occupied 53.6% of the Sorobouly classified forest in 2017. Numerous human and natural factors are responsible for this regressive change in vegetation cover. The land-use simulation predicts a vegetation cover of 32.16% of the Sorobouly CF and 97% of the Pâ CF by 2027, according to the trend scenario. The green environmental and economic scenarios developed offer sustainable management alternatives for the Sorobouly classified forest

Coupling RESI with Multi-Scenario LULC Simulation and Spatiotemporal Variability Analysis: An Ecological Spatial Constraint Approach

Southwest China’s arid river valleys represent ecologically vulnerable areas with intense human activity. Understanding the historical changes in LULC and land cover and projecting the impacts of various development scenarios on future LULC have become crucial for regional spatial information management and territorial spatial planning. This research analyzes the land-use changes in the Yuanmou dry-hot valley over a 30-year span from 1990 to 2020. Building upon the PLUS model, we established a coupled habitat quality spatial and multi-scenario land-use simulation model. Four development scenarios were proposed: natural progression, economic development, ecological conservation, and balanced development. We conducted simulations and evaluations of land-use in the Yuanmou dry-hot valley for 2030 using the PLUS mode, assessing the sustainability of future development scenarios under varying ecological constraints. During the simulation, three distinct RESI regions were employed as restricted development zones, integrating the three ecological constraints with the four simulation scenarios. We introduced a novel approach based on ecological environmental quality as the ecological constraint, providing a scientific reference for sustainable development in ecologically vulnerable areas. The results indicate that under ecological conservation scenarios with high-to-low RESI constraints, the ecological environment is superior to the other three scenarios. The results show the following: (1) From 1990 to 2020, aside from a continuous decrease in grassland area, there was an increasing trend in the areas of water bodies, forests, croplands, construction lands, and unused lands in the Yuanmou dry-hot valley. (2) By 2030, under all four development scenarios, the cropland area is expected to expand rapidly, while forested areas will decrease; grassland areas will decline under natural and economic development scenarios but show opposite trends under the other scenarios; and construction land and unused land areas will decrease under the ecological conservation and balanced development scenarios. (3) Land-use intensity analysis for the four scenarios indicated that, by 2030, unused lands in the Yuanmou dry-hot valley are more likely to be converted into water bodies, forests are more likely to be converted into croplands and grasslands, grasslands are more likely to be converted into croplands, croplands are more likely to be converted into grasslands, and construction lands are more likely to become unused lands. (4) Sustainable LULC management evaluations based on landscape indices reveal that ecological conservation and balanced development scenarios exhibit superior landscape connectivity and clustering. Thus, the balanced development scenario is the most appropriate LULC strategy for the Yuanmou dry-hot valley in the future. These findings provide scientific references for balancing ecological conservation and economic development in the arid river valleys of Southwest China.

Optimization and Simulation of Mountain City Land Use Based on MOP-PLUS Model: A Case Study of Caijia Cluster, Chongqing

Mountainous cities face various land use challenges, including complex topography, low land use efficiency, and the insufficient control of land use in small-scale areas at the urban fringe. Considering population changes, environmental conservation, and urban planning, this study first established three scenarios: economic priority (Econ. Prior.), ecological priority (Ecol. Prior.), and balanced development (BD), and then used the Multi-Objective Planning (MOP) model to calculate the optimal land use structure. Finally, it carried out land use spatial layout optimization based on the Patch-generating Land Use Simulation (PLUS) model in 2035, Caijia Cluster, Chongqing, China. This approach, known as MOP-PLUS modeling, aimed to optimize land use. Meanwhile, the applicability of the PLUS model in simulating land use changes was discussed in small-scale mountainous areas. The results show the following: (1) The “quantity + space” approach in the MOP-PLUS model demonstrated the feasibility of the PLUS model in simulating land use change in small-scale mountainous areas. The overall accuracy (OA) of land use change simulation reached 81.60%, with a Kappa value of 0.73 and a Figure of Merit (FoM) coefficient of 0.263. (2) Land use optimization: Under the Econ. Prior. scenario, economic benefits peaked at 4.06 × 1010 CNY. Urban expansion was the largest, leading to increased patch fragmentation. The Ecol. Prior. scenario yielded the highest ecological benefits, reaching 7.46 × 107 CNY. The urban development pattern exhibited inward contraction, accompanied by urban retrogression. In the BD scenario, economic benefits totaled 3.89 × 1010 CNY, and ecological benefits amounted to 7.16 × 107 CNY. Construction land tended to concentrate spatially, leading to relatively optimal land use efficiency. Therefore, based on a comprehensive consideration of the regional land use constraint policies and spatial layout, we believe that a balance point for land use demands can be found in the BD scenario. It can ensure economic growth without compromising the ecological environment.

Scenario Simulation of Land Use and Cover under Safeguarding Ecological Security: A Case Study of Chang-Zhu-Tan Metropolitan Area, China

Scenario-based simulation in land use and cover change (LUCC) is a practical approach to maintaining ecological security. Many studies generally set constraints of LUCC utilizing ecological patches but without consideration of corridors connecting these patches. Here, we constructed a framework to balance urban growth and ecological security by integrating ecological security patterns (ESPs) into the PLUS model. This study selected Chang-Zhu-Tan Metropolitan Area (CZTMA) in central China as a typical case. Specifically, coupling quantitative demand with spatial constraints of multiple levels of ESPs, this study designed four scenarios, including historical tendency (HT), urban growth (UG), ecological conservation (EC), and coordinating city development and ecological protection (CCE). Then, the transformations and landscape patterns of LUCC were analyzed to evaluate the future land change from 2020 to 2050. The results show sixty-one key ecological sources in the CZTMA, mainly in higher-elevation forested areas. Forty-six ecological corridors were estimated using circuit theory. The building expansion was driven by accessibility to transportation and government locations and will contribute to the loss of forest and cropland in the future. The feature of different scenarios in alleviating the increasing fragmentation of patches and reducing the loss amount of ecological land showed EC > CCE > HT > UG. This study developed the ESP-PLUS framework and its modeling idea, which has the potential to be applied in other regions. This extension would assist decision-makers and urban planners in formulating sustainable land strategies that effectively reconcile eco-environmental conservation with robust economic growth, achieving a mutually beneficial outcome.