Land Use Development Research Articles

Spatio-temporal evolution and prediction of carbon storage at the source of the Fen River and Sanggan River based on a PLUS-InVEST model

Investigating the evolution of land use and its impact on carbon storage is of significant importance for mitigating regional climate change and promoting green low-carbon development. Ningwu County is located in the source region of the Fenhe and Sanggan River, and its ecological status significantly influences the carbon storage (CS) of the watershed ecosystem. In this study, the PLUS-InVEST model was employed to analyze the land use evolution from 1990 to 2020 in Ningwu County, Shanxi Province, as well as their impacts on CS. Additionally, the study simulated and predicted land use changes in Ningwu County by 2040 under four scenarios: natural development (NDS), ecological protection (EPS), cultivated land protection (CLPS), and urban development (UDS), while estimating the corresponding changes in ecosystem CS. Furthermore, the study utilized optimal parameters-based geographical detector to explore the mechanisms underlying the spatial differentiation of CS. The results indicated that the areas of forest land and construction land in the study area consistently increased from 1990 to 2020, whereas the area of cultivated land continuously declined, with grassland, water bodies, and unused land exhibiting a fluctuating increasing trend. The spatial distribution of CS was highest in the northwest, second highest in the southeast, and lowest in the middle region. Over these 3 decades, CS had shown a continuous increase. It is projected that by 2040, the areas of forest and grassland will experience the most significant increase under the EPS; cultivated land only increase under the CLPS; while construction land display the greatest increase under the UDS. Compared to 2020, these four scenarios for 2040 indicate an increase in regional CS, with the EPS showing the largest increment. The primary factors influencing the spatial differentiation of CS in Ningwu County are human activities, followed by topography and climate change; the interactions among these factors exhibit a reinforcing relationship, with the interaction between the distance from construction land and slope having the most substantial impact on the spatial differentiation of CS.

PARADIGM DEVELOPMENT OF LAND RELATIONS AND HIGH-TECHNOLOGICAL LAND USE

The study substantiates that land resources are a strategic resource, the socio-economic development of society depends on the rationality and efficiency of their use. The economic content of the concept of «land relations» is generalized and it is revealed that they are a component of social relations, arise in the process of interaction of society with natural resources and regulate the norms of behavior of business entities of the agricultural sector of the economy within the framework of land legislation. The basis of land relations is the category of land ownership, therefore changes and development of organizational and legal forms of land ownership are perhaps the most important condition. It is worth noting that land relations in agriculture are part of production relations and can be both stimulating and restraining factors for the rational use of agricultural land and high-tech land use. It was found that land legislation in Ukraine remains fragmentary and often inconsistent between all regulatory acts, and changes to individual regulations and legal mechanisms cause risks for investors and landowners, which creates legal uncertainty and complicates the implementation of the efficiency of land resources use. High-tech land use is a direction of modern agrarian development aimed at increasing the efficiency of agriculture, preserving natural resources and ensuring food security. Systematizing the problems and directions of development of land relations and high-tech land use, it was highlighted that the main priority remains the implementation of the social function of land ownership and land use, which ensures the most efficient land use of land plots for their intended purpose. Thus, the main guidelines of land policy are the stability and effectiveness of the functioning of the system of land relations and agricultural land use, aimed at ensuring the country's food security and increasing the well-being of the population. The development of land relations and high-tech land use should be based on maximum consideration of natural, economic and social conditions and environmental requirements for preserving the environment, protecting land resources and restoring their fertility, increasing the productivity of the land fund, as well as limiting the negative impact of economic activity on flora and fauna, etc.

Analysis of natural and man-made factors of landslide development in the Carpathian region using GIS

Purpose. Determination of the dependencies of spatial relationships between landslides in the Carpathian region of Ukraine and the factors causing them, taking into account the differences in geomorphological, geological, climatic conditions and natural and geographical zoning according to the landscape principle. Methodology. The morphometric analysis of the territory was carried out using QGIS tools to determine the slope angles and exposure; linear characteristics were calculated: distances to the river, road, and houses. Based on the image interpretation data, we calculated the total annual rainfall and average annual air temperature. The impact of the factors considered on landslide formation was assessed using multivariate statistical analysis: factor analysis and linear multiple regression. Findings. Studies on the impact of natural and topographical conditions and anthropogenic activity on the development of landslide processes have been conducted. Orographic and climatic factors play the most important role. Construction of business facilities results in a decrease in the slope stability in 14–19 % of cases. The analysed independed factors showed good consistency between the distribution of existing landslides and the parameters under consideration: the share of the total variance of the factors under consideration is 71–76 %, the coefficient of determination of the regression model is 0.7. Based on the results of geoinformation and statistical analyses, it is proved that differences in geomorphological conditions and human activity (construction of roads, economic facilities) are dominant in the formation of landslides in different landscape zones. Originality. It is established that there is a dynamic coherence between the spatial change in natural conditions and human settlement and activity, which interact with each other to create prerequisites for the development of landslides. Practical value. This study is important from the point of view of understanding and mitigating the cause-and-effect relationship of landslide development for certain territories, and the results obtained can be useful in developing land use planning strategies, infrastructure development, and planning new construction works.

Dynamics System Modeling of Declining Agricultural Land Area Potentially Causing Jakarta Flood Disaster

The change or evolution of land use in the DKI Jakarta area has caused various environmental problems in the city that have an impact on disasters that occur from time to time. The conversion of agricultural land that has a relatively high ability to absorb water into built-up land has reduced the water absorption capacity because the built-up area is increasingly impermeable which is at risk of causing flood disasters. This research focuses on a simple dynamic system modeling approach to understand the cause-and-effect relationship of the decline in agricultural land area in the DKI Jakarta area. The method used in this research is a qualitative-based dynamic system, dynamic system is a method that can be used to form structures and predict behavior and feedback. Dynamic system modeling using Powersim Studi 10 Express software uses time specifications ranging from 2020 to 2070. The results of the dynamic system model of agricultural land decline can be said to be valid, where the dominant structure formed is Negative Feedback (Balancing Loop) with Exponential Decay behavior and Average Means Error (AME) test results obtained a value of 29.6%

Economic Assessment of Hydrologic Ecosystem Services in Morocco’s Protected Areas: A Case Study of Ifrane National Park

This study delves into the complex interplay between land use dynamics, hydrological services, and intangible benefits within the context of Ifrane National Park (INP) in Morocco. Due to its extensive mountain forests and numerous wetlands, INP is a crucial contributor to the nation’s water supply and a vital source of hydrological ecosystem services (HES). However, climate change and evolving land use patterns have led to diminishing water resources and the desiccation of certain wetlands. This research used the Integrated Valuation of Ecosystem Services and Tradeoffs software (InVEST 3.10.2) for HES quantification and environmental economics approach for monetization to comprehend how HES values respond to challenges posed by urbanization, intensive agriculture, and other land use alterations. This work underscores INP’s role as a significant “water tower”, emphasizing the evolution of its services amidst challenges. Our findings reveal an annual decrease in HES economic value by USD 4000. This economic assessment serves as a compelling tool to enlighten decision-makers and park users about the imperative need to preserve natural ecosystems and use water resources judiciously. It advocates for investments in conservation and restoration within protected areas to sustain these vital services.

Assessing Land Use Ecological-Social-Production Functions and Interrelationships from the Perspective of Multifunctional Landscape in a Transitional Zone between Qinghai-Tibet Plateau and Loess Plateau

Investigating the evolution and drivers of multifunctional land use is essential for sustainable land management and regional biological conservation. This research focuses on the Hehuang Valley, where we developed an “ecological-social-production” evaluation system for assessing land use multifunctionality from the perspective of multifunctional landscape. Leveraging Geographic Information System technologies, we conducted a quantitative analysis of spatiotemporal variations in multifunctional land use across the valley in recently twenty years. Correlation coefficients were employed to identify trade-offs and synergies among various land use functions. Additionally, geographical detector and grey relational analysis models were utilized to pinpoint the factors influencing spatiotemporal changes in land use functions during the specified period. The results showed that: (1) During the period, the overall multifunctionality of land use in the Hehuang Valley exhibited an increasing trend. The economic production function of the land showed the highest growth, while the ecological and social functions showed lower growth. (2) In most areas of the Hehuang Valley, there was a positive correlation between social and economic production functions and a negative correlation between social and ecological functions, as well as between economic production and ecological functions. (3) Natural conditions were the main factors of spatial variation of land use comprehensive functions, but human factors, including land use intensity and the rate of farmland conversion to non-agricultural uses, were the primary drivers of temporal changes in multifunctional land use. The findings provide valuable references and scientific support for policymakers in optimizing land use and multifunctional landscape conservation.

The impact of heterogeneous accessibility to metro stations on land use changes in a bike-sharing context

The integration of urban rail transit and land use has been adopted as a crucial approach to fostering compact development in cities. Proximity to rail transit stations can increase the probability of land use changes, while few studies have analyzed the spatial heterogeneity of the impact of rail transit on land use changes. This study proposes a distance-decay function to delineate the spatial heterogeneity of metro station accessibility using bike-sharing data and examines the impact of metro stations accessibility on land use changes. Jiading New Town in Shanghai, China, is selected as our study case. By utilizing a non-linear distance-decay function to delineate metro station accessibility as a driving factor for training neural networks in a vector-based cellular automata model, an improvement in simulation accuracy is achieved compared to the model using a linear distance-decay function. This study could help establish more efficient strategies for promoting integrated development of rail transit and land use. The significance of this study lies in the generality of the optimized land use vector-based cellular automata model considering the spatial heterogeneity of metro station accessibility, which could also be applied to other situations, such as considering the accessibility to bus stops and road networks.

Geospatial Intelligence for Landslide Susceptibility and Risk Analysis: Insights from NH31A and East Sikkim Himalaya Settlements

Slope instability is a serious concern in the Sikkim Himalayas. The town and numerous road segments along National Highway 31A were ravaged by multiple landslides that occurred in the nearby region. A bivariate statistical method known as frequency ratio (FR), information value (IV), and certainty factor (CF) analysis was employed in this work to examine landslide risk assessment (LRA) and landslide susceptibility zonation (LSZ) maps in the Rorachu watershed. This study represents the first comprehensive analysis of landslide risk in the populated areas of East Sikkim and along NH31A, offering a deeper understanding of the risks involved and contributing to the enhancement of local resilience against landslide hazards. A total of 153 different landslide locations were mapped using Google Earth and GIS software; 30% (46) of these locations were used to validate the models, and 70% of these (107) served as training data for the FR, IV, and CF models. The thirteen landslide causative factors (geology, soil, elevations, slope, curvature, drainage density (DD), road density (RD), rainfall, normalized difference vegetation index (NDVI), land use land cover (LULC), topographic position index (TPI), stream power index (SPI), and topographic wetness index (TWI)) were extracted from a spatial database for LSZ mapping. Landslides were most prevalent on slopes (35° to 50°), heights (2,500–4,100 m), and rainfall (2000–2,500 mm and 3,000–3,300 mm). The area under the curves (AUC) for the FR, IV, and CF models are 0.925 (92.50%), 0.846 (84.60%), and 0.868 (86.20%), respectively. The prediction rates are shown by the AUCs for the FR, IV, and CF models, which are 0.828 (82.8%), 0.750 (%), and 0.836 (83.60%), respectively. According to the landslide risk assessment (LRA), the FR (20.75%), IV (40.91%) and CF (18.78%) models showed high risk on Highway 31A, while the FR (9.05%), IV (38.59%) and CF (20.90%) models showed high risk in densely populated areas. These landslide risk and vulnerability maps can be used to develop land use planning strategies that can save lives and are useful for planners and mitigation measures. Special attention should be paid to urbanization, highway construction, and deforestation.

Tissue distribution and temporal and spatial assessment of per- and polyfluoroalkyl substances (PFAS) in smallmouth bass (Micropterus dolomieu) in the mid-Atlantic United States

Per- and polyfluoroalkyl substances (PFAS) have become an environmental issue worldwide. A first step to assessing potential adverse effects on fish populations is to determine if concentrations of concern are present in a region and if so, in which watersheds. Hence, plasma from adult smallmouth bass Micropterus dolomieu collected at 10 sites within 4 river systems in the mid-Atlantic region of the United States, from 2014 to 2019, was analyzed for 13 PFAS. These analyses were directed at better understanding the presence and associations with land use attributes in an important sportfish. Four substances, PFOS, PFDA, PFUnA, and PFDoA, were detected in every plasma sample, with PFOS having the highest concentrations. Sites with mean plasma concentrations of PFOS below 100 ng/ml had the lowest percentage of developed landcover in the upstream catchments. Sites with moderate plasma concentrations (mean PFOS concentrations between 220 and 240 ng/ml) had low (< 7.0) percentages of developed land use but high (> 30) percentages of agricultural land use. Sites with mean plasma concentrations of PFOS > 350 ng/ml had the highest percentage of developed land use and the highest number PFAS facilities that included military installations and airports. Four of the sites were part of a long-term monitoring project, and PFAS concentrations of samples collected in spring 2017, 2018, and 2019 were compared. Significant annual differences in plasma concentrations were noted that may relate to sources and climatic factors. Samples were also collected at two sites for tissue (plasma, whole blood, liver, gonad, muscle) distribution analyses with an expanded analyte list of 28 PFAS. Relative tissue distributions were not consistent even within one species of similar ages. Although the long-chained legacy PFAS were generally detected more frequently and at higher concentrations, emerging compounds such as 6:2 FTS and GEN X were detected in a variety of tissues.

Driving the Evolution of Land Use Patterns: The Impact of Urban Agglomeration Construction Land in the Yangtze River Delta, China

The rapid increase in population and economic activities has greatly influenced land use and spatial development. In urban agglomerations where socioeconomic activities are densely concentrated, the clash between ecological protection and economic growth is becoming more evident. Therefore, a thorough quantitative assessment of spatial changes driven by land use dynamics, alongside an examination of temporal and spatial driving factors, is crucial in offering scientific backing for the long-term and sustainable growth of urban agglomerations. This paper focuses on the major urban agglomerations in China’s Yangtze River Delta region, examining the spatiotemporal evolution of land use and landscape patterns from 2000 to 2020. By employing the standard deviation ellipse technique, coupled with multiple linear regression and the geographical detector model, we conduct a quantitative assessment of the directional trends in urban construction land expansion as well as the diverse impacts of temporal and spatial factors on this expansion across various periods and regions. The findings indicate that over the past 20 years, construction land in the Yangtze River Delta Urban Agglomeration expanded in concentrated patches, showing significant scale effects with relatively intact farmland and forest land being increasingly encroached upon. Landscape-type transitions predominantly occurred in cities around Taihu Lake and Hangzhou Bay, with the most significant transition being farmland converted to construction land, resulting in a greater number of patches and more pronounced land fragmentation. Throughout the 20 years, the standard deviation ellipse of construction land in the Yangtze River Delta Urban Agglomeration expanded and shifted, with the predominant expansion trending from the northwest toward the southeast, and the EN orientation being the most intense expansion area, covering 1641.24 km2. The influence of temporal and spatial driving factors on the expansion of urban construction land differed across various periods and regions. This study thoroughly examines the driving factors that affect the evolution of urban construction land in the region, offering valuable scientific evidence and references for future planning and development of the Yangtze River Delta Urban Agglomeration, aiding in the formulation of more precise and efficient urban management and land use strategies.

Coupling Coordination Degree of Land, Ecology, and Food and Its Influencing Factors in Henan Province

Studying the spatiotemporal evolution characteristics of the coupling coordination of the land–ecology–food system (LEF) aids in promoting green agricultural development and regional resource management. This study enriches food indicators under the dietary structure and uses the coupling coordination degree model to analyze the coupling coordination relationship among the LEF of 18 cities in Henan Province from 2011 to 2020. The gray relational degree model is used to investigate the main influencing factors determining the synergistic development of the system. The results show that the comprehensive development index of the LEF in Henan Province ranges between 0.4 and 0.6. The overall comprehensive evaluation index of various cities is ranked as Southern Henan &gt; Eastern Henan &gt; Central Henan &gt; Northern Henan &gt; Western Henan, with the greatest fluctuation observed in the food subsystem. During the study period, the coupling degree of Henan’s LEF ranged from 0.277 to 0.996, indicating stages from low- to high-level coupling. The coupling coordination degree ranged from 0.338 to 0.775, generally bordering on imbalance and barely coordinated. The impact of each subsystem evaluation index on the system’s coupling coordination degree can be ranked as food subsystem &gt; ecology subsystem &gt; land subsystem, with the correlation degree of internal indicators of the food and ecology subsystems with the system’s coupling coordination degree being over 85%, emphasizing the importance of strict management. In summary, the coupling coordination of the LEF system in Henan Province urgently needs to be improved; especially, the coordination of the agricultural system is particularly important. Clarifying the spatiotemporal pattern of the LEF coupling and its coordination can provide a scientific basis for the coordinated development of land use, agricultural ecology, and grain production in Henan Province.

Global sustainability scenarios lead to regionally different outcomes for terrestrial biodiversity

Abstract Mitigating climate change (CC) and reversing biodiversity decline are urgent and interconnected global priorities. Strategies to address both crises must consider the relationships, synergies and trade-offs between key response measures, including sustainable production and consumption patterns, protected areas (PAs) and climate mitigation policy (CP). In this paper, we review a large set of scenarios (n = 96) from the Integrated Model to Assess the Global Environment (IMAGE) describing future development of land use, greenhouse gas emissions and their impact on CC and biodiversity. We calculate the global mean temperature increase (GMTI) and the Mean Species Abundance (MSA) of plants, a metric indicative of local terrestrial biodiversity intactness. The set includes scenarios with and without specific CP to address CC, PA for biodiversity and demand and supply sustainability measures such as increased energy efficiency and reduced meat consumption. Our findings indicate that scenarios with integrated measures can prevent biodiversity loss at the global scale, yet with clear regional differences. By 2050, 15 out of 30 (50%) scenarios with at least 30% of global land as PAs show positive MSA changes in grasslands and tropical non-forests (Grass &amp; TnF), but only 1 (3%) does so in tropical forests (TF). We demonstrate that pasture and food/feed crops are the main drivers of MSA loss in Grass &amp; TnF and that scenarios with high levels of PAs prevent land conversion and increase biodiversity. By 2100, 28 out of 46 (60%) scenarios with mitigation measures to restrict CC to 2 °C or less in 2100 result in positive MSA changes in TF, but only 13 (28%) do so in Grass &amp; TnF, reflecting the larger impacts of land use change in the latter region. These results underscore the importance of time and regionally-tailored approaches to address the biodiversity and CC crises.

Spatio-Temporal Evolution and Multi-Scenario Modeling Based on Terrestrial Carbon Stocks in Xinjiang

The increase in atmospheric CO2 leads to global warming and ecological environment deterioration. Carbon storage modeling and assessment can promote the sustainable development of the ecological environment. This paper took Xinjiang as the study area, analyzed the spatial and temporal evolution of land use in four periods from 1990 to 2020, explored the spatial relationship of carbon stocks using the InVEST model, and coupled the GMOP model with the PLUS model to carry out multiple scenarios for the future simulation of land use in the study area. We found (1) Over time, the types with an increasing area were mainly impervious and cropland, and the types with a decreasing area were grassland, snow/ice, and barren; spatially, the types were predominantly barren and grassland, with the conversion of grassland to cropland being more evident in the south of Northern Xinjiang and north of Southern Xinjiang. (2) The evolutionary pattern of terrestrial carbon stocks is increasing and then decreasing in time, and the carbon sink areas are concentrated in the Tarim River Basin and the vicinity of the Ili River; spatially, there are differences in the aggregation between the northern, southern, and eastern borders. By analyzing the transfer in and out of various categories in Xinjiang over the past 30 years, it was obtained that the transfer out of grassland reduced the carbon stock by 5757.84 × 104 t, and the transfer out of Barren increased the carbon stock by 8586.12 × 104 t. (3) The land use layout of the sustainable development scenario is optimal under the conditions of satisfying economic and ecological development. The reduction in terrestrial carbon stocks under the 2020–2030 sustainable development scenario is 209.79 × 104 t, which is smaller than the reduction of 830.79 × 104 t in 2010–2020. Land optimization resulted in a lower loss of carbon stocks and a more rational land-use layout. Future planning in Xinjiang should be based on sustainable development scenarios, integrating land resources, and achieving sustainable economic and ecological development.

Assessment of Landscape Change and its Relationships with Surface Temperature and Geo-spatial Indices during 1992 - 2022 at Haldia Industrial Region, West Bengal, India

Unplanned local development and alterations in Land Use and Land Cover (LULC) are an early alert for towns and cities around the world. The population pressure has resulted in the conversion of natural land into impermeable areas, which has altered the surface energy budget and created microclimatic differences locally. The main objective of the present study is to estimate LULC changes and its relation to increases Land Surface Temperature (LST) in the Haldia Industrial Region (HIR) of West Bengal using multi-temporal Landsat 5 Thematic Mapper (TM) of 1992 and Landsat 8 Operational Land Imager (OLI) of 2022 with 30-m spatial resolution images were obtained from the USGS website. The supervised classification method was applied by using Maximum Likelihood classification (MLC) to classify the satellite images into various LULC classes such as settlement, waterbody, vegetation, agriculture land, and fallow land, respectively. The result suggested an overall increase of settlement area from 13.49 km2 in 1992 to 44.54 km2 in 2022. On the other hand, the agriculture land decreased from 214.26 km2 to 152.34 km2 due to fast urbanization, decline green lands, and expansion of barren lands. The outcome result from LST was exhibited that the LST value has increased 3.77°C during 1992 to 2022 in this study area. The Normalized Difference Vegetation Index (NDVI) was showed a strong negative relationship with LST with a determination coefficient (R2) values found as 0.491 (1992) and 0.356 (2022). The positive determination coefficient between LST with Normalized Difference Water Index (NDWI) was found as 0.0002 (1992), and 0.0417 (2022). R2 values were estimated as 0.174 (1992), and 0.0347 (2022) between LST with Normalized Difference Built-up Index (NDBI) that indicated a positive determination coefficient. The findings enhanced understanding of the relationship between urban LST and LULC in developing an inclusive climate resilience policy and making the HIR more sustainable to the effects of climate change.

Evolution of Land Use and Land Cover Change in Panjim, Goa: A Comparative Analysis from 1990 to 2024

This research paper investigates the dynamics of land use and land cover (LU/LC) change in Panjim, Goa, India, from 1990 to 2024. Using satellite Data and GIS techniques, the study analyzes the spatial and temporal transformations of land cover categories, including forest, agriculture, urban areas, and water bodies. The primary objective is to understand the drivers of LU/LC change and assess their implications for sustainable urban development and environmental conservation. The findings reveal significant urban expansion, encroachment on agricultural lands, and reduction in forest cover. The study highlights the need for effective land use planning and management strategies to mitigate negative environmental impacts and ensure the city's long-term sustainability. Keywords: Land Use, Land Cover, Supervised Classification, Change Detection, Accuracy Assessment

Decadal hydrological impact assessment of evolving land use and land cover in an Indian river basin: a multi-model approach

ABSTRACT All river basins have ever-evolving land use and land cover (LULC) attributes. The impact of these changes may not be significant on short time scales (i.e., monthly, seasonal, yearly), but over a decadal scale, they can substantially alter the hydrological processes of the basin. This study comprehensively quantifies the impacts of LULC changes over Cauvery basin in India using LULC maps from four decades spanning from 1980 to 2020. Simulations were performed using the Soil and Water Assessment Tool (SWAT) with various datasets. To isolate the effects of LULC changes, two sets of SWAT models were developed: A-set models for calibration and validation to establish basin parameters and B-set models to examine LULC change impacts while isolating other factors such as terrain and climate changes. Key findings include a significant increase in urban areas (0.87% in 1985 to 5.54% in 2015), a decline in vegetation cover (25.34% in 1985 to 21.32% in 2015), and an increase in the Curve Number and average annual surface runoff, highlighting the impact of LULC changes on hydrological processes. The A-set models achieved R-squared values of 0.831, 0.728, 0.715, and 0.757, while the B-set models showcased significant changes in hydrological parameters due to LULC changes.

Driving forces and prediction of urban open spaces morphology: The case of Shanghai, China using geodetector and CA-Markov model

Urban open spaces offer both environmental and social benefits. However, comprehensive studies that integrate both quantitative and qualitative evaluations of the factors driving change in these spaces and their long-term predictions are lacking. Most existing studies concentrate on land-use development rather than conducting empirical research specific to urban open spaces in Shanghai. This study addresses this gap by employing a geographic detector (geodetector) to analyze the influence of various driving factors on open-space changes. These factors were then used as weight values in a multicriteria CA-Markov model to simulate and predict change in Shanghai's urban open spaces by 2050. The advantage of analyzing driving forces lies in their ability to capture the multifactor synergy influencing change in urban open spaces, aligning with the aim of this study to quantitatively evaluate the interaction between natural, climatic, and socioeconomic factors. Additionally, semi-structured interviews were conducted with 10 policymakers and planners to assess the reliability of the quantitative predictions. The results indicate that socioeconomic factors are the primary drivers of change in urban open spaces. Specifically, the interaction between the normalized difference vegetation index (NDVI) and population density (PD) emerged as the most influential variables. For prediction outcomes, the unconstrained scenario predicts a decrease in open-space area from 5610.94 km2 in 2020 to 5124.36 km2 in 2050. The planning intervention scenario anticipates minimal changes in Shanghai's total urban open-space area with almost no floating changes. However, the economic development scenario predicts a rapid decline in open spaces. Experts and planners evaluated these three scenarios and confirmed the reliability and accuracy of the prediction models. The methods and findings of this study can support zoning planning for urban open-space systems in other cities and regions.

Prediction of Land Use and Habitat Quality in Harbin City Based on the PLUS- InVEST Model

Analyzing the spatiotemporal evolution of urban land use and habitat quality can reveal the correlation between land use and habitat quality, aiding in rational urban land policies and high-quality ecological environment development. This study was based on land use transition matrices and an Intensity-Migration （IM） model to analyze the changes in land use in Harbin from 2000 to 2020. It combined the PLUS model to explore the driving factors of land use expansion for various land types and predicted land use scenarios for 2030 under natural development, ecological protection, farmland protection, and urban development scenarios. Finally, the InVEST model was used to complete the habitat quality analysis. The results indicated： ① The dominant land use types in Harbin were cropland, forest land, and grassland. From 2000 to 2020, there was a significant tendency of conversion into grassland, cropland, forest land, and artificial surfaces, with noticeable changes in land use intensity. Water bodies, bare land, and wetland types showed less conversion and tended to be restrictive. ② Elevation was the primary factor influencing the expansion of grassland, cropland, forest land, bare land, wetland, and water bodies. Socioeconomic factors were the main factor affecting the expansion of artificial surfaces. ③ Simulation of land use types in Harbin for 2030 under the four scenarios showed an increase in forest land area and a decrease in grassland area, with insignificant changes in wetland, water bodies, and bare land areas. Except for in the ecological protection scenario, the area of artificial surfaces increased, whereas cropland decreased. ④ Overall, habitat quality in Harbin improved from 2000 to 2020. ⑤ In 2030, the spatial pattern of habitat quality in Harbin remained consistent across all scenarios, showing an overall improvement in habitat quality. Under the ecological protection scenario, areas with low and medium habitat quality decreased, whereas areas with higher habitat quality increased, indicating a relatively significant improvement in habitat quality. The research results provide a scientific basis and insights for the development of ecological civilization and urban planning and construction in Harbin.

Combining ecosystem service value and landscape ecological risk to subdivide the riparian buffer zone of the Weihe River in Shaanxi

Riparian buffer zones are transitional and ecological intersections between land and water. These areas play a major role in advancing ecosystem protection and restoration. Here, we investigated the spatial and temporal evolution of land use, ecosystem service value (ESV), and landscape ecological risk (LER) in riparian buffer zones between 1990 and 2020 using the Shaanxi section of the Weihe River as a case study using a GIS grid, the unit-area-equivalent-factor method, the landscape ecological risk index, and the natural breakpoint method. We also established four ecological zones using standardized Z-scores. The predominant land categories in the study area comprised cultivated, construction, and grassland, which together accounted for more than 80 % of the total area. The construction land demonstrated the most significant increase of 4,062.33 hm2 area, and cultivated land showed most significant decrease of 13,048.56 hm2 area, between 1990 and 2020. Next, study-site ESV increased from 28.30 × 108 CNY in 1990 to 28.94 × 108 CNY in 2020, reflecting 2.26 % growth. High-value areas were principally bodies of water and primarily situated along the Weihe River, extending from west to east along the main channel. The LER of the study area was dominated by the lowest ecological risk, low ecological risk, and medium ecological risk classes, which collectively accounted for more than 70 % of the total area. The main land types in the areas with high ecological risk were forest land and cultivated land. The study area’s LER demonstrated a decreasing trend from 1990 to 2020, and the area with the lowest ecological risk and low ecological risk zones increased by 9.97 %. The riparian buffer zone was divided into ecological restoration, reconstruction, conservation, and protection zones based on two factors, namely, ESV and LER. The most dominant of these was the ecological reconstruction zone, which showed a 13.75 % decrease in area share between 1990 and 2020. The ecological restoration zone occupied the smallest area with the largest increase of 56.63 % during this period. In conclusion, this study contributes to ecological zoning and management of the riparian buffer zone along the main channel of the Weihe River. Appropriate zoning is integral to protecting this valuable ecosystem and achieving sustainable development of surrounding human communities.

Spatio-temporal evolution, driving mechanisms, and simulation of land use and cover in China from 2000 to 2060

Spatio-temporal evolution, driving mechanisms, and simulation of land use and cover in China from 2000 to 2060