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Despite the Yangtze River Basin (YRB)’s abundant land and forestry resources, there is still a dearth of research on forecasting habitat quality changes resulting from various geographic and environmental factors that drive landscape transformations. Hence, this study concentrates on the YRB as the focal area, with the aim of utilizing the Patch Landscape Upscaling Simulation model (PLUS) and the habitat quality model to scrutinize the spatial distribution of landscape patterns and the evolution of HQ under four scenarios: the natural development scenario (NDS), farmland protection scenario (CPS), urban development scenario (UDS), and ecological protection scenario (EPS), spanning from the past to 2030. Our results show that (1) from 2000 to 2020, the construction land in the YRB expanded at a high dynamic rate of 47.86% per year, leading to a decrease of 32,776 km2 in the cultivated land area; (2) the UDS had the most significant expansion of construction land, followed by the NDS, CPS, and EPS, which had higher proportions of ecologically used land such as forests and grasslands; (3) from 2000 to 2020, the HQ index ranged from 0.211 to 0.215 (low level), showing a slight upward trend, with the most drastic changes occurring in the low-level areas (−0.49%); (4) the EPS had the highest HQ (0.231), followed by the CPS (0.215), with the CPS increasing the HQ proportion of the lower-level areas by 2.64%; (5) and in addition to government policies, NDVI, DEM, GDP, and population were also significant factors affecting landscape pattern and changes in habitat quality.

The expansion of tea plantations has caused changes in land use structure, which, in turn, has affected the regional habitat quality. Exploring the characteristics of changes in land use structure and habitat quality under different development scenarios is important for the formulation of regional land planning policies and the guarantee of ecological security. This study quantified the habitat quality of the study area from 2010 to 2020 based on the InVEST habitat quality module and explored the land use distribution patterns and habitat quality change characteristics under different scenarios in combination with the PLUS model. The results show that, from 2010 to 2020, the area of tea plantations expanded by 153.0126 km2, and the mean value of habitat quality increased from 0.6502 to 0.6919; in different development scenarios, the area of tea plantations was from large to small in the order of scenario 1 (871.2468), scenario 3 (599.4531) and scenario 2 (518.5440), and the mean value of habitat quality was from high to low in the order of scenario 1 (0.7385), scenario 2 (0.7162) and scenario 3 (0.6919). This study mainly explored the structural changes of land use and habitat quality evolution characteristics under different development scenarios in the study area, and the results of the study can provide a reference basis for rational land development and utilization and habitat conservation in the large-scale tea plantation area.

Analyzing land use changes (LUC) in both past and future scenarios is critical to optimize local ecology and formulate policies for sustainable development. We analyzed LUC characteristics in Huaibei City, China from 1985 to 2020, and used the CLUE-S and PLUS models to simulate LU in 2020. Then, we compared the accuracy of the simulation phase and chose the PLUS model to project LU under four scenarios in 2025. The results showed the following: (1) Farmland and grassland areas decreased from 1985 to 2020, while forestland, water, and construction land increased. (2) The LU types in the region are explained well by the driving factors, with all receiver operation characteristic (ROC) values greater than 0.8. (3) The kappa indices for CLUE-S and PLUS analog modeling were 0.727 and 0.759, respectively, with figure of merit (FOM) values of 0.109 and 0.201. (4) Under the farmland and ecological protection scenario (FEP), farmland and forestland areas are protected, increasing by 1727.91 hm2 and 86.22 hm2, respectively, while construction land decreases by 2001.96 hm2. These results confirm that PLUS is significantly better than the CLUE-S model in modeling forestland and water, and slightly better than the CLUE-S model in modeling the rest of the LU type. Urban sustainability is strong in the scenario FEP.

Exploring the future trends of land use/land cover (LULC) changes is significant for the sustainable development of a region. The simulation and prediction of LULC in a large-scale basin in an arid zone can help the future land management planning and rational allocation of resources in this ecologically fragile region. Using the whole Ili-Balkhash Basin as the study area, the patch-generating land use simulation (PLUS) model and a combination of PLUS and Markov predictions (PLUS–Markov) were used to simulate and predict land use in 2020 based on the assessment of the accuracy of LULC classification in the global dataset. The accuracy of simulations and predictions using the model were measured for LULC data covering different time periods. Model settings with better simulation results were selected for simulating and predicting possible future land use conditions in the basin. The future predictions for 2025 and 2030, which are based on historical land change characteristics, indicate that the overall future spatial pattern of LULC in the basin remains relatively stable in general without the influence of other external factors. Over the time scale of the future five years, the expansion of croplands and barren areas in the basin primarily stems from the loss of grasslands. Approximately 48% of the converted grassland areas are transformed into croplands, while around 40% are converted into barren areas. In the longer time scale of the future decade, the conversion of grasslands to croplands in the basin is also evident. However, the expansion phenomenon of urban and built-up lands at the expense of croplands is more significant, with approximately 774.2 km2 of croplands developing into urban and built-up lands. This work provides an effective new approach for simulating and predicting LULC in data-deficient basins at a large scale in arid regions, thereby establishing a foundation for future research on the impact of human activities on basin hydrology and related studies.

Land use and land cover (LULC) changes resulting from rapid urbanization are the foremost causes of increases in land surface temperature (LST) in urban areas. Exploring the impact of LULC changes on the spatiotemporal patterns of LST under future climate change scenarios is critical for sustainable urban development. This study aimed to project the LST of Nanjing for 2025 and 2030 under different climate change scenarios using simulated LULC and land coverage indicators. Thermal infrared data from Landsat images were used to derive spatiotemporal patterns of LST in Nanjing from 1990 to 2020. The patch-generating land use simulation (PLUS) model was applied to simulate the LULC of Nanjing for 2025 and 2030 using historical LULC data and spatial driving factors. We simulated the corresponding land coverage indicators using simulated LULC data. We then generated LSTs for 2025 and 2030 under different climate change scenarios by applying regression relationships between LST and land coverage indicators. The results show that the LST of Nanjing has been increasing since 1990, with the mean LST increased from 23.44 °C in 1990 to 25.40 °C in 2020, and the mean LST estimated to reach 26.73 °C in 2030 (SSP585 scenario, integrated scenario of SSP5 and RCP5.8). There were significant differences in the LST under different climate scenarios, with increases in LST gradually decreasing under the SSP126 scenario (integrated scenario of SSP1 and RCP2.6). LST growth was similar to the historical trend under the SSP245 scenario (integrated scenario of SSP2 and RCP4.5), and an extreme increase in LST was observed under the SSP585 scenario. Our results suggest that the increase in impervious surface area is the main reason for the LST increase and urban heat island (UHI) effect. Overall, we proposed a method to project future LST considering land use change effects and provide reasonable LST scenarios for Nanjing, which may be useful for mitigating the UHI effect.

Terrestrial ecosystems play an important role in carbon reduction and sequestration, and it is important to explore the carbon sequestration potential of terrestrial ecosystems under different land use scenarios to enhance the regional carbon storage potential. We analysed land use changes in the Loess Plateau, an important ecological barrier in China, from 2000 to 2020, used the PLUS model to predict land use patterns under different scenarios in 2035, and applied the InVEST model to assess carbon storage from 2000 to 2035. The findings were as follows: (1) Cropland in the study area decreased significantly from 2000 to 2020, and forests, waters, and construction land showed an increasing trend. The area of cropland further decreased under the natural growth and ecological protection scenarios, the area of grassland decreased significantly under the cropland protection scenario, and forests and waters were effectively protected under the natural development, ecological protection, and cropland protection scenarios. (2) Carbon storage in the Loess Plateau has increased by 28 Tg (0.56%) over the past 20 years. Compared with those in 2020, by 2035, carbon storage under the natural development, ecological protection, and cropland protection scenarios will increase by 30, 44, and 21 Tg, respectively. (3) Carbon storage has obvious spatial heterogeneity, with high carbon density in the northern Qinling Mountains, Taihang Mountains, and Lvliang Mountains and low carbon density in Erdos City and its surrounding areas. Regional differences in carbon density are closely related to the spatial distribution of land use types. (4) Carbon storage showed an inverted V-shaped trend with the increase in elevation. Land use change is the main reason for the increase or decrease in carbon storage under different scenarios. Compared with the other two scenarios, the ecological protection scenario not only protects the ecological environment but also has a strong carbon storage potential, which may be significant for guiding the formulation of future land use planning on the Loess Plateau.

Ecosystem services (ESs) are crucial for sustainable development, as they impact human well-being. However, changes in land use/land cover (LULC) caused by climate change and social development can negatively affect ESs, particularly in arid river basins. This study focuses on current and future changes in LULC in the Kaxghar River Basin (KRB) in Xinjiang, China, to determine how these changes will affect the region’s ESs. The integrated PLUS-InVEST model was used to investigate the spatiotemporal distribution and changing patterns of habitat quality (HQ) and carbon storage (CS) under the natural increase scenario (NIS), economic development scenario (EDS), and water protection scenario (WPS). Additionally, the Ecosystem Service Contribution Index (ESCI) was also calculated to evaluate the contribution of LULC changes to ESs. The results show the following: (1) from 2000 to 2020, the average value of HQ in the KRB gradually decreased from 0.54 to 0.49 and CS trended slightly upward, with a total increase of 0.07 × 106 t. Furthermore, the changes in CS were highly consistent with changes in LULC. (2) From 2020 to 2030, the area of low-grade (0–0.2) HQ saw a continuous increase, with the fastest growth occurring in 2030 under the EDS. Meanwhile, under the WPS, HQ significantly improved, expanding by 1238 km2 in area. Total CS under the three test scenarios tended to decline, with the NIS showing the smallest decrease. (3) The expansion of cropland and unused land had a negative impact on ESs, particularly on CS, whereas the conversion to grassland and forestland had a significant positive impact. In conclusion, these insights will enrich our understanding of ESs in the study area and contribute to balancing the relationship between ecological conservation and socioeconomic development in the Kaxghar River Basin, as well as in other parts of China’s arid Northwest and similar regions around the world.

The arid region of northwest China is an extremely fragile area of natural ecology. With population growth and continuous expansion of urban scale, the ecosystem in the arid region is facing greater pressure. Scientific assessment and prediction of the value of ecosystem services in arid areas are necessary and of great significance for the sustainable development of regional ecological environments. In this paper, a parametric optimal geographic model is used to analyze the driving factors of ESV spatial dispersion in Jiuquan City as an example. The PLUS model is also used to simulate the spatial and temporal evolution of ESV in 2035 under the scenarios of natural development, urban development, water constraints and ecological conservation, based on the historical change pattern of land use and ecosystem service value (ESV). The results showed that from 1980 to 2020, the plowland, water and construction land area in Jiuquan City showed a significant increasing trend, while other land use types showed a decreasing trend. ESV has increased from CNY 139.394 billion to CNY 142.642 billion. The expansion of plowland and water area was the main reason for the increase in ESV. Elevation, temperature, and precipitation are the main driving factors of spatial differentiation of ESV in Jiuquan City. The interaction of natural and human factors enhances the explanatory power of each factor to the spatial differentiation of ESV. In 2035, the ESV in four development scenarios in Jiuquan City showed an upward trend, and the ESV of the ecological protection scenario was the highest, which was the best mode to realize a sustainable development in Jiuquan City in the future. This study can provide scientific basis and decision-making basis for Jiuquan City to formulate sustainable development strategy.

Land use change has significant impacts on the regional and global environment; thus, in-depth research on the associated ecological risks is necessary for promoting ecological restoration and sustainable development. Xinjiang, China, is characterized by a fragile ecological environment, and this study aimed to predict the land use change in the region in 2030 under different scenarios, including natural development, ecological conservation, and urban development, by using the PLUS model based on land use data from 2000, 2010, and 2020. Based on the landscape structure of regional ecosystems, we developed a comprehensive ecological risk assessment framework by utilizing a combination of landscape disturbance index, vulnerability index, and loss index. This framework allowed us to evaluate the spatiotemporal patterns and variations of landscape ecological risks under different scenarios in 2030. The study results indicate the following: (1) During the period from 2000 to 2020, the primary landscape type in Xinjiang was unused land. However, significant changes were observed in the area of cultivated land, mainly due to the conversion of grassland and construction land. The expansion of construction land during the urbanization process resulted in a decline in ecological landscapes, such as grassland, thereby weakening the ecosystem’s stability. (2) Under different simulation scenarios, the urban development scenario primarily led to the conversion of unused land into construction land, which is beneficial for economic development. On the other hand, the ecological conservation scenario resulted in a modest increase in construction land and a transformation of unused land into forest and grassland, which aligns with the principles of sustainable development. (3) Different scenarios in 2030 result in varying degrees of changes in each landscape type in Xinjiang, with the spatial distribution characteristics of landscape ecological risks remaining similar to those observed in 2020. Notably, under the urban development scenario, the area of lowest and medium risk areas decreases significantly while the area of higher and highest risk areas increases substantially. Conversely, under the ecological conservation scenario, the area of the lowest risk areas experiences a more significant increase. (4) Overall, the spatial differences in the ecological risk of Xinjiang’s landscape are significant, with HH and LL clustering types predominating and presenting a polarization pattern. The distribution pattern is low in the north and high in the central and southern parts of the study area.

High-frequency land-use changes caused by rapid economic development have become a key factor in the imbalance of carbon sequestration within regions. How to balance economic development and ecological protection is a difficult issue for regional planning. Studying the relationship between future land-use changes and ecosystem carbon storage (CS) is of important significance for the optimization of regional land-use patterns. The research used the gray prediction model and coupled the patch-generating land-use simulation (PLUS) model and the integrated valuation of ecosystem services and trade-offs (InVEST) model. On this basis, the evolution characteristics and spatial coordination between land-use changes and CS in the Dongting Lake Basin (DLB) in different scenarios in 2030 were simulated. The results show that: (1) The spatial distribution of CS remains stable in different scenarios, while land-use types with high carbon density in the periphery of cities are constantly invaded by construction land, which results in the greatest carbon loss in the urban areas. (2) Compared with the natural evolution scenario (NES), only 195.19 km2 of land-use types with high carbon density are transformed into construction land in the ecological protection scenario (EPS), generating a carbon sink gain of 182.47 × 104 Mg. Conversely, in the economic development scenario (EDS), a total of over 1400 km2 of farmland and ecological land are transformed into construction land, which weakens the carbon sequestration capacity of ecosystems, and more than 147 × 104 Mg of carbon loss occurs in the urban areas. (3) The planned development scenario (PDS) takes ecological protection and economic development both into consideration, which not only generates a carbon sink gain of 121.33 × 104 Mg but also reduces the carbon loss in urban areas by more than 50%. The PDS performs well in both land use and CS growth and can better motivate the effect of land-use changes in increasing the carbon sink, which is also proved by analysis of the coordination between land-use intensity (LUI) and CS. Therefore, the PDS better satisfies the future development demand of DLB and can provide a reference for sustainable land use in the basin.

Carbon storage is one of the key factors determining the global carbon balance in the terrestrial ecosystems. Predicting future changes in carbon storage is significant for regional sustainable development in the background of the “dual carbon” objective. This study which coupled the InVEST model and the PLUS model and is based on land use in different future scenarios evaluated the evolution characterization of terrestrial carbon storage in Jilin Province from 2000 to 2040 and explored the impact of related factors on it. The results show that: (1) from 2000 to 2020, the area of cultivated land and built-up areas increased continuously in Jilin Province, while the area of forest land, grassland, and wetland decreased with time; the ecological land has been restored to a certain degree. (2) Due to the continuous reduction in ecological land, the overall carbon storage in Jilin Province from 2000 to 2020 showed a downward trend, with a total reduction of 30.3 Tg, and the carbon storage in the western part of Jilin Province changed significantly. The SSP2-RCP4.5 scenario shows a minimum value of carbon storage in 2030 and a small increase in 2040; the SSP1-RCP2.6 scenario shows an increasing trend in carbon storage from 2020 to 2040; the area of built-up areas and cultivated land increases and the loss in carbon storage is more serious under the SSP5-RCP8.5 scenario. (3) On the whole, with the increase in elevation and slope, the carbon storage showed a trend of increasing first and then decreasing, and the carbon storage of shady and semi-shady slopes was higher than that of sunny and semi-sunny slopes; forest land and cultivated land were the keys to carbon storage changes in Jilin Province.

As a key area in the Yellow River basin for sand control and management, the land change process in the Hobq Desert plays a crucial role in keeping the river and desert ecosystems and promoting the construction of ecological civilization in human systems. Based on multi-temporal remote sensing from 1991 to 2019 in the Hobq Desert along the Yellow River section, this study selected spatial statistical methods (land-use monitoring and landscape metrics) to examine land-use change dynamics. Then, we evaluated habitat quality using the InVEST model and quantitatively analyzed the factors causing spatial changes in habitat quality using geographic detectors. Finally, this paper predicted the pattern of land use and habitat quality in 2030 using the PLUS model. The results reveal that (1) from 1991 to 2019, the total area of forest grassland increased by 3572.5 km2, providing the most vegetation cover, and the sandy land and water area decreased continuously, while the cultivated land and construction land increased. There were 38.01% conversions of land types, with the land-use dynamic decreasing the greatest in sandy land (−12.66%) and increasing the greatest in construction land (9.26%); the comprehensive land-use dynamics were the highest in 2010–2019 (1.68%), which was the most active stage during our study period. (2) Both of the landscape indices NP and PD showed “N” type fluctuations during 1991–2019, and CONTAG and LSI rose from 69.19% to 70.29% and 36.01% to 38.89%, respectively, indicating that the land-use degree of landscape fragmentation increased, landscape connectivity turned better, and landscape dominance was enhanced, balanced, and developed evenly in overall landscape type. (3) From the overall region analysis, the average habitat quality in 1991, 2000, 2010, and 2019 was 0.3565, 0.5108, 0.5879, and 0.6482, respectively, with the overall habitat value showing a gradually increasing trend. Spatially, the habitat quality along the Yellow River section of the Hobq Desert has a certain regularity, and the overall pattern there is high in the south and low in the north, high in the east and west, and low in the middle. (4) The change in land use between 2019 and 2030 is similar to the previous period, but the change rate is generally lower. The habitat quality improved significantly, with the growth of high and medium habitat quality.

Soil erosion is an important global environmental issue that severely affects regional ecological environment and socio-economic development. The Yellow River (YR) is China’s second largest river and the fifth largest one worldwide. Its watershed is key to China’s economic growth and environmental security. In this study, six impact factors, including rainfall erosivity (R), soil erosivity (K), slope length (L), slope steepness (S), cover management (C), and protective measures (P), were used. Based on the revised universal soil loss equation (RUSLE) model, and combined with a geographic information system (GIS), the temporal and spatial distribution of soil erosion (SE) in the YR from 2000 to 2020 was estimated. The patch-generating land use simulation (PLUS) model was used to simulate the land-use and land-cover change (LUCC) under two scenarios (natural development and ecological protection) in 2040; the RUSLE factor P was found to be associated with LUCC in 2040, and soil erosion in the Yellow River Basin (YRB) in 2040 under the two scenarios were predicted and evaluated. This method has great advantages in land-use simulation, but soil erosion is greatly affected by rainfall and slope, and it only focuses on the link between land-usage alteration and SE. Therefore, this method has certain limitations in assessing soil erosion by simulating and predicting land-use change. We found that there is generally slight soil erosivity in the YRB, with the most serious soil erosion occurring in 2000. Areas with serious SE are predominantly situated in the upper reaches (URs), followed by the middle reaches (MRs), and soil erosion is less severe in the lower reaches. Soil erosion in the YRB decreased 11.92% from 2000 to 2020; thus, soil erosion has gradually reduced in this area over time. Based on the GIS statistics, land-use change strongly influences SE, while an increase in woodland area has an important positive effect in reducing soil erosion. By predicting land-use changes in 2040, compared to the natural development scenario, woodland and grassland under the ecological protection scenario can be increased by 1978 km2 and 2407 km2, respectively. Soil erosion can be decreased by 6.24%, indicating the implementation of woodland and grassland protection will help reduce soil erosion. Policies such as forest protection and grassland restoration should be further developed and implemented on the MRs and URs of the YR. Our research results possess important trend-setting significance for soil erosion control protocols and ecological environmental protection in other large river basins worldwide.

Land-use change plays an important role in ecological change; knowing the trends in land-use change can quickly help identify problems in regional ecosystems. In 2000 to 2020, the development of a global economy caused increasing extreme weather events worldwide and lead to exacerbating changes in types of land-use. The Yellow River source area is an important water source and a central part of ecological protection efforts in China. The fragile ecosystems make the area sensitive to environmental changes. Therefore, in protecting the ecological security of the basin, simulating changes in the ecosystem service value under different scenarios is a meaningful procedure. A patch-generating land use simulation model was used to simulate different land use scenarios in 2030, including an ecological protection scenario, a production priority scenario, a carbon neutral scenario and a natural development scenario. The analysis shows that significant progress has been made in water conservation but grassland conservation faces enormous challenges. The rate of development, occupation of farmland and land dedicated to construction has increased. Unused land increased dramatically from 2010–2020 and has not been mitigated by existing policies. Based on the unit area value equivalent coefficients, the ecosystem service value rankings for the seven land use types were as follows: Grassland > Wetland > Water Area > Forest > Farmland > Unused Land > Construction Land; the four types of ecosystem service value are ranked as follows: regulating services > supporting services > supply services > cultural services; the four scenarios of ecosystem service value are ranked as follows: ecological protection scenario > production priority scenario > carbon neutral scenario > natural development scenario. The ecosystem service value of the Yellow River source area would increase by CNY 1.641 billion in 2030 with ecological protection goals and decrease by CNY 1.421 billion with the current of development. This study provides valuable insights and implications for land use, ecological protection and sustainable development by shedding light on watershed change issues and assessing and predicting the ecological status of the Yellow River source area.

It is essential to study the characteristics of land use change in the Fuxian Lake basin, a plateau lake in Yunnan Province, and to predict the basin’s future trend of land use change for sustaining the key carriers of current national major strategies such as ecological civilization, green development, and rural revitalization. This study used the Fuxian Lake basin as the subject and based on the seven periods of historical land use data, added six driving factors including human and natural factors, applied patches to generate the land-use simulation model (PLUS), and forecasted and analyzed the characteristics of land-use change in the basin in 2048 under the three scenarios of natural trend development, ecological protection, and production protection. The results showed that: (1) the overall simulation accuracy of the model was 79.14%, Kappa index was 0.73, FOM value was 0.29, and the model’s consistency was high. The model can be used to simulate future land-use changes in the Fuxian Lake basin. (2) In the natural development scenario, land-use development and the driving factors in the basin have the following relationship: rainfall and trunk road distance significantly impacted the types of land that emphasize ecological conservation and product development. Elevation and soil distribution characteristics had a significant impact on land types focused mainly on water zones and ecological protection. The land types mainly focused on urban construction were greatly affected by elevation, trunk road distance, GDP per capita, and other factors. (3) The main direction of land-use change in the watershed is the mutual conversion between farmland and forest land, with the continuous expansion of construction land. In the production protection scenario, the area of farmland increased by 44.79 hm2. In the ecological protection scenario, the area of arbor forest land increased by 37.85 hm2 and the area of shrub forest land decreased by 62.37 hm2. (4) From the perspective of spatial distribution patterns, the regional hotspot change blocks are mainly concentrated in the north of the basin, along the coast of the north of Fuxian Lake, and the southern land. In general, the PLUS model had good applicability in this study. The simulation results of the different scenarios were in line with the land development in the Fuxian Lake basin and can provide scientific reference for land-space planning, ecological and production land constraints, and coordination of development in the Fuxian Lake basin.

In efforts to improve regional ecosystem service functions, coordinate land development and ecological conservation, and establish a reference for optimizing land resource allocation and policy formulation to cope with climate change, it is critical to investigate the spatial distribution of land use/cover change (LUCC) and ecosystem services (ESs) under future climate change. This study proposes a framework based on the Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP), integrating the patch-generating land use simulation (PLUS) model and the integrated valuation of ecosystem services and tradeoffs (InVEST) model to analyze the spatial agglomeration of ESs, to analyze the importance of each driving factors. The results of the study show as follows: (1) the combination of CMIP6 and PLUS models can effectively simulate land use with an overall accuracy of 0.9379. (2) In spatial correlation, ESs show good clustering in all three future scenarios, with similar distribution of cold hotspots in the SSP126 and SSP245 scenarios. Hotspots are more dispersed and cold spots are shifted to the west in the SSP585 scenario. (3) GDP is an important factor in carbon storage and habitat quality, and precipitation has a greater impact on soil retention and water production. Overall, ESs can be increased by appropriately controlling population and economic development, balancing economic development and ecological protection, promoting energy transition, maintaining ecological hotspot areas, and improving cold spot areas.

Carbon storage (CS) is strongly associated with climate change and ecosystem services. Herein, taking Foshan City, Guangdong Province, China as the study object, analysis was performed upon the potential impacts of the urban–rural relationship of CS by combining the Integrated Assessment of Ecosystem Services and Trade-offs (InVEST) and the Patch Generation Land-use Simulation (PLUS) models. Based on three different development plans under regional policies, land-use/ land-cover (LULC) changes in Foshan City in 2035 were simulated. The results show that (i) Foshan City experienced rapid urban expansion from 2010 to 2020 spreading from the central area to the outer circle in a cascading manner. Urban land use mainly encroached on ecological land during these 10 years. (ii) The CS in Foshan City from 2010 to 2020 showed an increase followed by a decrease, and the simulations estimated a continuous loss of the CS in Foshan City by 2035. (iii) There was spatial heterogeneity in the CS changes in Foshan. From 2010 to 2020, the northern part of Sanshui District and the eastern part of Chancheng District experienced the greatest economic loss of CS. The carbon loss will further increase in future development scenarios. This research can provide vital references for government administrators to formulate valid development patterns and ecological conservation strategies.

Land-use/land-cover change (LUCC) is an important factor affecting carbon storage. It is of great practical significance to quantify the relationship between LUCC and carbon storage for regional ecological protection and sustainable socio-economic development. In this study, we proposed an integrated framework based on multiobjective programming (MOP), the patch-level land-use simulation (PLUS) model, and the integrated valuation of ecosystem service and trade-offs (InVEST) model. First, we used the InVEST model to explore the spatial and temporal evolution characteristics of carbon storage in Hangzhou from 2000 to 2020 using land-cover data. Second, we constructed four scenarios of natural development (ND), economic development (ED), ecological protection (EP), and balanced development (BD) using the Markov chain model and MOP, and then simulated the spatial distribution of land cover in 2030 with the PLUS model. Third, the InVEST model was used to predict carbon storage in 2030. Finally, we conducted a spatial correlation of Hangzhou’s carbon storage and delineated carbon storage zoning in Hangzhou. The results showed that: (1) The artificial surfaces grew significantly, while the cultivated land decreased significantly from 2000 to 2020. The overall trend was a decrease in carbon storage, and the changing areas of carbon storage were characterized by local aggregation and sporadic distribution. (2) The areas of artificial surfaces, water bodies, and shrubland will continue to increase up to 2030, while the areas of cultivated land and grassland will continue to decrease. The BD scenario can effectively achieve the multiple objectives of ecological protection and economic development. (3) The carbon storage will continue to decline up to 2030, and the EP scenario will have the highest carbon storage, which will effectively mitigate the carbon storage loss. (4) The spatial distribution of carbon storage in Hangzhou was inextricably linked to the land cover, which was characterized by a high–high concentration and a low–low concentration. The results of the study can provide decision support for the sustainable development of Hangzhou and other cities in the Yangtze River Delta region.

The evolution of regional land use is a complex process under the combined effect of multiple factors, and it is important to understand this evolution process, as well as its characteristics and future trends, through land use change models in order to achieve scientific use of land space and optimize the regional development pattern. In this study, the PLUS model is used to simulate the land use in 2035 for the natural development scenario, the urban expansion scenario and the ecological protection scenario using the middle reaches of Yangtze River urban agglomeration (MRYRUA) as the study area, and then to calculate the ecosystem service values (ESV) and analyze the contribution of each driver to each land type and the spatial autocorrelation of the ESV at the grid scale. The results show that (1) the land use changes in the study area from 2015 to 2020 are mainly: the rapid expansion of construction land with an increase of 200,221 hm2 and an increase in arable land, specifically 85,982 hm2, and a decrease in all other land types. (2) The ESV of the study area was CNY 3,837,282 million and CNY 3,774,162 million from 2015 to 2020, respectively, with an general decreasing trend. (3) Three scenarios are simulated for the study area in 2035, and the ESVs under the natural development scenario, urban expansion scenario and ecological conservation scenario are CNY 3,618,062 million, CNY 3,609,707 million and CNY 3,625,662 million, respectively, which are all lower than those in 2020. (4) The global autocorrelation indices for 2020 and the three scenarios are 0.7126, 0.7104, 0.7144 and 0.7104, respectively, which are significantly positive. The simulation of MRYRUA land use and the comparative analysis of ESV provide some help in the strategic optimization of the spatial distribution pattern of land use in large regional urban agglomerations.

Land use and cover change (LUCC) has a non-negligible impact on both carbon emissions and carbon sinks. Based on the analysis of land use dynamics in Shandong Province, this study simulates land use changes in Shandong Province in 2030 under the Natural Development Scenario (NDS) and Sustainable Development Scenario (SDS), classifies the risk level of carbon emissions in Shandong Province using the Land Use Carbon Emission (LUCE) risk indexes, and compares the differences between the risk level regions under NDS and SDS. This study shows that under the influence of LUCC, the carbon emissions in Shandong province increased significantly, from 90.5591 million tons in 2000 to 493.538 million tons in 2020, with urban land being the main source of carbon emissions, which increased from 90.0757 million tons in 2000 to 490.139 million tons in 2020. The main source of the increase in urban land was cropland. The LUCE was positively correlated with urban land area. The LUCE of SDS was 7.2423 million tons less than that of NDS. From 2000 to 2020, the risk areas of LUCE in Shandong province were mainly no-risk and mild-risk areas. The number of moderate-risk areas and high-risk areas of SDS was less than that of NDS. The rational organization of land use is important for Shandong Province to achieve low-carbon development.

The security of cultivated land is the foundation for stable social and economic development. In recent years, with rapid economic development, urbanization around the world has been accelerating. The demand for urban construction expansion is increasing day by day and lands used for cultivation are being infiltrated by construction, posing a serious threat to food security. This study used the land-use data from Haikou City in 1980, 2000, 2010 and 2020, to generate a transfer matrix, kernel density analysis and landscape pattern index to analyze the spatial-temporal evolution of cultivated land in Haikou. The PLUS model was used to explore potential factors driving land-use evolution. Results show that cultivated land in Haikou was continuously lost from 1980 to 2020 and the area of cultivated land decreased by 7020.58 ha. Loss was most significant during 2010–2020 when cultivated land ascended into construction land in the northern region of the city. Spatial distribution of cultivated land in Haikou is generally characterized by “dense in the southwest and sparse in the northwest”, and the spatial density of cultivated land in the northwest continuously decreased from 1980 to 2020. In the past 40 years, the degree of spatial aggregation for cultivated land in Haikou has decreased and the degree of fragmentation has increased. The primary factors driving changes in spatial-temporal patterns over the past 40 years has been the distance from roads and high-speed railways and the distance from water. During the 40-year timespan, Haikou continued to lose cultivated land areas due to the interaction of social and natural factors such as road traffic and water resources. The juxtaposition between the demand for urban construction lands and the protection of cultivated land has become increasingly evident. Due to the threat cultivated lands are facing in the northern area of Haikou, we suggest future expansion of construction development land should be strictly controlled.

The Chengdu Metropolitan Area, located on the eastern edge of the world’s highest plateau, has experienced a period of integrating urban and rural area development for decades. With rapid urbanization and population growth, the vulnerability and security of the ecological environment have become critical aspects to consider in sustainability. Moreover, the presence of different levels of vitality in the study area has a crucial impact on land-use change. Hence, we propose a growth boundary study based on the theory of urban vitality and ecological networks. We focus on identifying the inefficient urban land and urban development potential land, explore their expansion probabilities to conduct spatial simulations for the next 15 years, and combine the ecological network to form a reasonable spatial pattern. Results showed that the proposed model could simulate the urban growth state more accurately within a certain space scale and integrate different limits and influences to simulate different growth strategies under multiple planning periods. Thus, the proposed model can be an effective decision support tool for the government.

The configuration of ecological land directly affects the structure and function of an ecosystem and, ultimately, its ability to meet human needs. From the perspective of human needs, this paper classified human needs into material needs, security needs and spiritual needs. Using Hechi City, Guangxi as the study area, we combined the Multi-objective planning (MOP) and PLUS models to study the quantity and spatial optimization of ecological land under different human needs scenarios, and the optimal allocation of ecological land within the ecological red line was also discussed. We conclude that: (1) Hechi City currently has less arable land, which cannot fully guarantee the material needs of human beings; there is more forest land than the amount needed to meet human needs, which reduces the efficiency of ecological land use. (2) In terms of quantity optimization, and considering the goals of different human needs, the area of grass to forest should be extended to satisfy security needs; the area of arable land should be significantly increased in line with material needs; the area of grass and water, with the goal of accommodating spiritual needs, is the largest compared with the rest of the goals. Under the comprehensive needs goal, the forest land area is greatly reduced, and the rest of the land area is increased; the goals of human material, spiritual and security needs are basically met. (3) In terms of spatial layout optimization, in order to meet the security needs target, grass to forest conversion should be carried out in the northern area to enhance the aggregation of forest land; to meet the material needs target, the southwestern gentle slope area should be concentrated toward continuous farming to guarantee the aggregation of arable land while increasing the area of arable land; to meet the spiritual needs target, the area of water in the northwestern area should be increased, and the rest of the changes are similar to the security needs target; to meet the comprehensive needs target, the overall land use connectivity becomes stronger, the fragmented land types become less and the concentrated continuous area of forest land, arable land and grass increases. (4) The results of the ecological land adjustment within the ecological red line indicate that the current ecological red line delineation is good, and a small amount of adjustment can meet human needs. Based on human demand, combined with the MOP-PLUS model for ecological land optimization, it can accurately portray the spatial and temporal evolution pattern of land use and reveal the optimization path of ecological land, which has important theoretical and practical values.

Investigating the future land use patterns and carbon emissions are of great significance for carbon reduction. This study established the relationship between land use types and carbon emissions from energy consumption and adopted three future scenarios that combine shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs), the system dynamics (SD) model, and the patch-generating land use simulation (PLUS) model to simulate land use patterns in 2030 and 2035. Then the spatial distribution of future carbon density and its change in Shenzhen were obtained. Under scenario SSP245, a large amount of industrial and mining land is converted into living land from 2020 to 2035, and new living land is mainly located in Bao’an District and Guangming District. Under scenario SSP370, a large amount of living land replaces other land due to a plentiful population from 2020 to 2035, which is rare under other scenarios. The expansions of areas with high carbon density during 2020–2030 are mainly distributed in Nanshan District and Longhua District under all three scenarios. During 2030–2035, carbon emissions will decrease under scenarios SSP126 and SSP245. The results confirmed various trends in carbon emissions under different scenarios and emphasized the association between land use types and carbon emissions.

Based on China’s “carbon neutrality” strategy, this study explores the relationship between land-use/cover change and temporal and spatial changes of ecosystem carbon storage in urban agglomerations. Using the Plus-InVEST model, the projected spatial patterns of land use in the Chengdu-Chongqing urban agglomeration in 2030 under natural development and ecological protection scenarios were simulated and predicted, and the characteristics of carbon storage, together with its spatio-temporal dynamics, were evaluated under two scenarios. Results show that: (1) From 2000 to 2020, forests, water areas, construction areas, and unused land continued to increase, while the area of cropland and grassland decreased continuously. During the last 20 years, carbon storage in urban agglomeration showed an increasing trend, with an overall increase of 24.490 × 106 t. (2) Compared with the natural development scenario, forest land, grassland, and water area in 2030 under the ecological protection scenario exhibits a substantial change; the area of construction land is limited; and an ecological spatial effect is reflected. (3) Compared to 2020, carbon storage under natural development and ecological protection scenarios decreased by 50.001 × 106 t and 49.753 × 106 t in 2030, respectively. The stability of carbon storage under the ecological conservation scenario was significantly higher than that under the natural development scenario. Therefore, under the ecological protection scenario, as a result of the coordinated land use of Chengdu-Chongqing, the functions of various regions can be coordinated and carbon storage losses can be mitigated.

Delineating urban growth boundaries (UGBs) by combining the land-use/land-cover (LULC) change simulation method has become common in recent studies. However, few of the existing studies have integrated multi-source big data to analyze the driving factors of LULC dynamics in the simulation. Moreover, most of previous studies mainly focused on the UGBs delineation in macroscale areas rather than small-scale areas, such as the county area. In this study, taking Xinxing County of Guangdong Province as the study area, we coupled a system dynamics (SD) model and a patch-generating land-use simulation (PLUS) model to propose a framework for the LULC change simulation and UGBs delineation in the county area. Multi-source big data such as points of interest (POIs), night-time light (NTL) data and Tencent user density (TUD) were integrated to analyze the driving forces of LULC change. The validation results indicate that the coupled model received high accuracy both in the land-use demand projection and LULC distribution simulation. The combination of multi-source big data can effectively describe the influence of human socio-economic factors on the expansion of urban land and industrial land. The UGBs delineation results have similar spatial patterns with the LULC change simulation results, which indicates that the proposed UGBs delineation method can effectively transform the LULC simulation results into available UGBs for the county area. It has been proven that the proposed framework in this study is effective for the LULC change simulation and UGBs delineation in the county area, which can provide insight on territorial spatial planning in the county area.

The management of regional eco-environmental risks is the key to promoting regional economic sustainability from the macro level, and accurate evaluation of the evolutionary trends of regional ecological risk in the future is of high importance. In order to clearly identify the possible impact of future development scenario selection for the Chengdu-Chongqing Economic Zone (C-C E Zone) on the evolution of landscape ecological risk (LER), we introduced the Patch-generating Land Use Simulation (PLUS) model to simulate land use data for the C-C E Zone from 2030 to 2050 for two scenarios: natural development (ND) and ecological protection (EP). Based on the ecological grid and landscape ecological risk index (LERI) model, the landscape ecological risk (LER) evolutionary trends seen in the C-C E Zone from 2000 to 2050 were analyzed and identified. The results showed that: (1) The PLUS model can obtain high-precision simulation results in the C-C E Zone. In the future, the currently increasing rate of land being used for construction will be reduced, the declining rates of forest and cultivated land area will also be reduced, and the amount of land being used for various purposes will remain stable going into the future. (2) This study found that the optimal size of the ecological grid in the LERI calculation of the mountainous area was 4 × 4 km. Additionally, the mean values of the LERI in 2030, 2040, and 2050 were 0.1612, 0.1628, and 0.1636 for ND and 0.1612, 0.1618, and 0.1620 for EP. (3) The hot spot analysis results showed that an area of about 49,700 km2 in the C-C E Zone from 2000 to 2050 belongs to high agglomeration of LER. (4) Since 2010, the proportions of high and extremely high risk levels have continued to increase, but under the EP scenario, the high and extremely high risk levels in 2040 and 2050 decreased from 14.36% and 6.66% to 14.33% and 6.43%. Regional analysis showed that the high and extremely high risk levels in most regions increased over 2010–2050. (5) Under the ND scenario, the proportions of grids with decreased, unchanged, and increased risk levels were 15.13%, 81.48%, and 3.39% for 2000–2010 and 0.54%, 94.75%, and 4.71% for 2040–2050. These trends indicated that the proportion of grids with changed risk levels gradually decreased going into the future. This study analyzed the evolutionary trends of LER at the C-C E Zone for the ND and EP scenario. On the whole, the LER for the C-C E Zone showed an upward trend, and the EP scenario was conducive to reducing the risk. These research results can serve as a valuable data reference set for regional landscape optimization and risk prevention and control.

The rapid urbanization in recent years as a vehicle for social growth and ecological construction has resulted in a significant transformation of the spatial structure of the land in the lower reaches of the Yellow River. Based on this, the current study used the PLUS model to simulate the future territorial spatial pattern of the lower reaches of the Yellow River in various development scenarios to reveal differences in the ecosystem’s spatial distribution and provide a reference for optimizing territorial spatial usage and ecological protection. The results show that the overall accuracy of the Patch-generating Land Use Simulation (PLUS) model’s simulation results was 0.748, the Kappa coefficient was 0.812, and the simulation effect was good. The simulation results for each land space in various situations reveal a preferential spatial development trend model. In the territorial and spatial priority scenario, development was reasonably balanced, which is consistent with the status of the quantitative structure of the territorial space of the study area during 2015. From 2015 to 2035, the value of ecosystem services will change in different ways depending on the scenario and the set priorities. The ecosystem service value decreased in the production space and living space priority development scenarios, while it increased in the ecological space and national space priority development scenarios. The PLUS model has a high degree of applicability to the spatial pattern development simulation of the lower Yellow River region, and the results of this multi-scenario simulation and ecological environmental effect study may be used as a reference for future territorial spatial planning and policy formulation in the region.

The sustainable development goals (SDGs) of the United Nations are focused on regional development and ecological security. Based on these SDGs, quantitative regional landscape ecological risk assessment is significant to realize regional sustainable development. This study took the central mountainous area (CMA) of Hainan Island as the research area, and combined SDGs and a patch-generating land-use simulation (PLUS) model to analyze multi-scenario land-use change and landscape ecological risk simulation. The study results show that the low ecological risk areas are located in the central hinterland of the CMA, and the high ecological risk areas are located on the northern and southern edges, with strong disturbances from human activities. The construction land in the CMA expanded drastically from 2010 to 2018, mainly invading forestland and grassland, leading to landscape fragmentation, which was the main cause of the increased ecological risk in the CMA landscape. The future multi-scenario simulations for SDGs show that under the scenario of natural development and economic development, the construction land and water area will significantly expand and the forest land will be dramatically reduced. Under the ecological protection scenario, the expansion of construction land will be restrained, and the area of forest land will increase. The results showed that the landscape ecological risks in the three simulated scenarios would be higher than in 2018, but the increase in the landscape ecological risks under the ecological protection scenario would be relatively slight. Forest land plays an essential role in maintaining the ecological security of the CMA. The expanding construction land in the CMA has led to landscape fragmentation and increased ecological risk. Therefore, it is necessary to protect the forest land in the CMA. In addition, construction and development should be limited in high-risk areas. Although the adoption of the ecological conservation scenario favors regional sustainability, it is still necessary to improve ecological protection policies such as ecological compensation to ensure the realization of other SDGs.