Search Results (13,371)

Urbanization and economic growth have substantially modified the land utilization structure, affecting ecosystem services and their spatial distribution. As a crucial component of Beijing’s urban framework, the city’s green belts, located at the periphery of its core metropolitan area, play a vital role in supplying urban ecosystem services. They also represent a focal point for land use transformation conflicts, making them an important study area. This research utilizes land utilization data from 2000, 2005, 2010, 2015, and 2020 as the primary dataset. It adopts a modified standard equivalent factor and integrates it with the Patch-Generaling Land Use Simulation (PLUS) model to model land utilization in Beijing’s green belts for 2035 under three scenarios: the natural development scenario (NDS), ecological protection scenario (EPS) and cultivated protection scenario (CPS). The study aims to analyze and project the spatial and temporal evolution of ecosystem service values (ESVs) in 2035 under different scenarios in the green belts of Beijing. The results indicate that (1) land use in Beijing’s green belts is dominated by cropland and construction land. Construction land has expanded significantly since 2000, increasing by 500.78 km², while cropland has decreased by 488.47 km². Woodland, grassland, and water have also seen a reduction. Overall, there is a trend of woodland and water being converted into cropland, with cropland subsequently transitioning into construction land. (2) In the NDS, construction land increases by 91.76 km², while cropland, grassland, and water decrease. In EDS, the growth of construction land decelerates to 22.09 km², the reduction in cropland decelerates, and the conversion of cropland to construction land is limited. Grassland and water remain largely unchanged, and woodland experiences a slight increase. In CPS, the conversion of cropland to construction land is notably reduced, with construction land increasing by 11.97 km², woodland increasing slightly, and grassland and water decreasing slightly. (3) The ESV ranking across scenarios is as follows: EPS 1830.72 mln yuan > CPS 1816.23 mln yuan > NDS 1723.28 mln yuan. Hydrological regulation and climate regulation are the dominant services in all scenarios. ESV in EPS attains the greatest economic gains. This study contributes to understanding the effects of land utilization changes on ESV, offering valuable empirical evidence for sustainable development decision-making in swiftly urbanizing areas. Full article

Desertification presents major environmental challenges in Central Asia, driven by climatic and anthropogenic factors. The present study quantifies desertification risk through an integrated approach using Bayesian networks and the ESAS model, offering a holistic perspective on desertification dynamics. Four key variables—vegetation cover, precipitation, land-use intensity, and soil quality—were incorporated into a Bayesian model to evaluate their influence on desertification. A probabilistic model was developed to gauge desertification intensity, with simulations conducted at 200 geospatial points. Hazard maps for 2030–2050 were produced under climate scenarios SSP245 and SSP585, incorporating projected land-use changes. All procedures for desertification risk assessment, land-use mapping, and climate downscaling were performed using the Google Earth Engine platform. The findings suggest a 4% increase in desertification risk under SSP245 and an 11% increase under SSP585 by 2050, with the greatest threats observed in western regions such as Kazakhstan, Uzbekistan, and Turkmenistan. Sensitivity analysis indicated that vegetation quality exerts the strongest influence on desertification, reflected by a Vegetation Quality Index (VQI) ranging from 1.582 (low in Turkmenistan) to 1.692 (very low in Kazakhstan). A comparison of the Bayesian and ESAS models revealed robust alignment, evidenced by an R² value of 0.82, a Pearson correlation coefficient of 0.76, and an RMSE of 0.18. These results highlight the utility of Bayesian networks as an effective tool for desertification assessment and scenario analysis, underscoring the urgency of targeted land management and proactive climate adaptation. Although reclaimed land presents opportunities for afforestation and sustainable agriculture, carefully considering potential trade-offs with biodiversity and ecosystem services remains essential. Full article

Erosion is a significant environmental challenge in Serbia, shaped by natural and human factors. Pronounced relief, fragile geological substrate, a developed hydrographic network, and a climate characterized by an uneven distribution of precipitation throughout the year make this area prone to activating erosion processes and flash floods whenever there is a significant disruption in ecological balance, whether due to the removal of vegetation cover or inadequate land use. Researchers have recorded approximately 11,500 torrents in Serbia, most of which were activated during the 19th century, a period of significant social and political change, as well as intensive deforestation and the irrational exploitation of natural resources. By the mid-19th century, the effects of land degradation were impossible to ignore. As the adequate assessment of soil erosion intensity is the initial step in developing a prevention and protection strategy and the type and scope of anti-erosion works and measures, this article presents the path that the anti-erosion field in Serbia has taken from the initial observations of erosion processes through the first attempts to create the Barren Land Cadastre and Torrent Cadastre to the creation of the Erosion Potential Method (EPM) and its modification by Dr. Lazarević that resulted in the creation of the first Erosion Map of SR Serbia in 1971 (published in 1983). In 2020, a new Erosion Map of Serbia was created with the application of Geographic Information System (GIS) technologies and based on the original method by Professor Slobodan Gavrilović—the EPM—without the modifications introduced by Lazarević. We compared the 1983 and 2020 erosion maps in a GIS environment, where the change in soil erosion categories was analyzed using a confusion matrix. The updated erosion maps mirror the shift in methodology from a traditional approach (Lazarević’s modification) to the modern GIS-based method (Gavrilović’s original EPM) and reflect technological improvements and changes in land use, conservation practices, and environmental awareness. Full article

Water stress has induced many environmental and developmental conflicts in the arid basins in the Middle East region under the context of climate change and increasing anthropogenic influence. Quantifying the anthropogenic influence on water stress at the basin scale is very challenging because of insufficient anthropogenic-related spatial data. Given that climate change is a global impact that is hard to mitigate at the basin scale, quantifying anthropogenic influence is practical to inform strategies for alleviating regional water stress. Thus, this study attempts to quantify the contribution of potential anthropogenic factors driving the water stress in the Tigris–Euphrates river basin (TERB) using pure spatial data. The water stress level in the studied basin was evaluated via the water stress index (WSI), which can be obtained as the ratio of water demand to water availability, from the Aqueduct 4.0 dataset. The driving contributions of social development (population, POP; fine particulate matter, PM2.5), economic development (gross domestic product, GDP; electricity consumption, EC), and landscape modification (urban expansion index, UEI; cultivated land expansion index, CEI) factors were quantitatively evaluated based on a spatial statistical geographical detector model (GDM). Assessment showed that nearly 66.13% of the TERB area was under severe water stress, particularly in Syria, Iraq, Saudi Arabia, and Iran. The q statistic of the GDM, adopted to quantify the contribution of driving factors, revealed that CEI (0.174), EC (0.145), and GDP (0.123) were the dominant factors driving water stress. These individual influences were further enhanced particularly in the interaction between economic development and landscape modification factors such as UEI and CEI (0.566), PM2.5 and UEI (0.350), EC and CEI (0.346), GDP and CEI (0.323), and PM2.5 and GDP (0.312). The findings of this research can provide some beneficial references to alleviate the TERB’s water stress for its future sustainable development. Full article

Numerous research studies have long established the causes and consequences of the depopulation of certain regions in Europe, but it seems that there are no systematic approaches to implementing the policy of managing abandoned areas. Following years of demographic decline in settlements, the 2022 census revealed depopulated clusters in Serbia—regions with 20 or fewer residents or even no inhabitants at all. The areas of depopulated settlements are growing territorially from the south towards the north. This paper adopts a broader interpretation of brownfield land, defining it as any previously used land that is no longer employed for commercial purposes, serving as the theoretical foundation. Although they seem economically hopeless, some depopulated clusters have become the subject of research for the exploitation of mineral resources such as gold, copper, zinc, uranium, lithium and coal. The main problem is that depopulated clusters have acquired an ecological stability that would be disrupted by the opening of mines and massive construction. The changes in land use were analyzed using time series data and a formal database of natural resources from these communities. The primary methodological framework was based on the correlation between population size, utilized areas, and the ecological stability coefficient. This study aimed to explore the relationship between the proportion of arable land within a spatial unit and its depopulation rate while also examining how arable land and mineral resources could influence the potential revitalization of rural wastelands in Serbia’s depopulated areas. The primary findings indicate a significant correlation between population decline and changes in the natural environment of abandoned clusters, as well as the significant potential of clusters as rural brownfields. While it is natural to continue with ecological and green space projects, the current liberal and centralized mining management policy can create major problems for the remaining population. Full article

In the context of rapid urbanization and extreme climate change globally, balancing ecological resources and economic development for land spatial planning has become one of the pressing issues that need to be addressed. This study proposes a composite model to construct a spatial ecological security pattern. It identifies restoration areas with different risk levels based on the spatial distribution of land use, offering suggestions for optimizing spatial configuration. Focusing on the central Shaanxi region of the Yellow River Basin in China, ecological sources are identified by integrating ecological factors, and ecological corridors and restoration zones are extracted using the minimum cumulative resistance difference and circuit theory. The results indicate significant improvements in ecological quality and desertification in the study area from 2000 to 2020. Currently, the core area covers 51,649.71 km², accounting for 62.18% of all landscape types; the total ecological source area covers 31,304.88 km², representing 18.84% of the entire area. These ecological source areas are mainly distributed in the northern Loess Plateau and the southern mountainous regions. The area has 26 important ecological corridors, identifying 16 ecological pinch points and 12 ecological barriers, presenting an ecological security pattern characterized by a grid-like structure in the northern region and a dispersed pattern in the southern region. Additionally, 273.72 km² of ecological restoration priority areas and 197.98 square kilometers of ecological restoration encouragement areas are proposed as key planning regions for ecological environmental protection. This study provides references for optimizing spatial configuration to promote the sustainable development of urban and rural living environments in the Yellow River Basin. Full article

The relocation of residents from high-risk areas is a critical measure to address safety and development issues in the floodplain regions of Henan Province in China. Whether the old villages can be reclaimed as farmland after demolition concerns Henan Province’s ability to maintain its farmland red line. This paper integrated multiple remote sensing indices and proposed a remote sensing identification method for monitoring the progress status of village relocation and reclamation that adapted to data characteristics and application scenarios. Firstly, it addressed the issue of missing target bands in GF-2 (GaoFen-2) by employing a band downscaling method; secondly, it combined building and vegetation indices to identify changes in land cover in the old villages within the floodplain, analyzing the implementation effects of the relocation and reclamation policies. Results showed that using a Random Forest regression model to generate a 4 m resolution shortwave infrared band not only retains the original target band information of Landsat-8 but also enhances the spatial detail of the images. Based on the optimal thresholds of multiple remote sensing indices, combined with human footprint data and POI (Points of Interest) identified village boundaries, the overall accuracy of identifying the progress status of resident relocation and reclamation reached 93.5%. In the floodplain region of Henan, the implementation effect of resident relocation was relatively good, with an old village demolition rate of 77%, yet the farmland reclamation rate was only 23%, indicating significant challenges in land conversion, lagging well behind the pilot program schedule requirements. Overall, this study made two primary contributions. First, to distinguish between rural construction and bare soil, thereby improving the accuracy of construction land extraction, an Enhanced Artifical Surface Index (EASI) was proposed. Second, the monitoring results of land use changes were transformed from pixel-level to village-level, and this framework can be extended to other specific land use change monitoring scenarios, demonstrating broad application potential. Full article

Economic pressure on agricultural land is generating major changes in affected territorial systems. The development of methodologies to analyze the pressure on agricultural land is one of the main concerns regarding food security and how to provide fresh produce to large cities. The methodology used uses the Corine Land Cover database, provided by Copernicus Land Monitoring Services (CLMS), from 1990–2018. Data processing and analysis was performed using the open-source software package QGIS, a process that started by reprojecting the data into the national coordinate reference system Pulkovo 1942(58)/Stereo 70, EPSG: 3844. The methodology used was able to highlight the transformations that have taken place in land use, highlighting when and how the land was transformed. Our results show that quantitative and land-use changes due to the socio-economic pressures generated by the transition to a different type of economy can be highlighted. Urban sprawl has led to dramatic changes in land use, with agricultural land being the category that has seen the largest reductions in area. Full article

The carbon stock in terrestrial ecosystems is closely linked to changes in land use. Understanding how land use alterations affect regional carbon stocks is essential for maintaining the carbon balance of ecosystems. This research leverages land use and driving factor data spanning from 2000 to 2020, utilizing the Patch-generating Land Use Simulation (PLUS) model alongside the InVEST ecosystem services model to examine the temporal and spatial changes in carbon storage across Beijing. Additionally, four future scenes for 2030—urban development, natural development, cropland protection, as well as eco-protection—are explored, with the PLUS and InVEST models employed to emulate dynamic land use changes and the corresponding carbon stock variations. The results show that the following: (1) Between 2000 and 2020, changes in land use resulted in a significant decline in carbon storage, with a total reduction of 1.04 × 10⁷ tons. (2) From 2000 to 2020, agricultural, forest, and grassland areas in Beijing all declined to varying extents, while built-up land expanded by 1292.04 km² (7.88%), with minimal changes observed in water bodies or barren lands. (3) Compared to the carbon storage distribution in 2020, carbon storage in the 2030 urban development scenario decreased by 6.99 × 10⁶ tons, highlighting the impact of rapid urbanization and the expansion of built-up areas on the decline in carbon storage. (4) In the ecological protection scenario, the optimization of land use structure resulted in an increase of 6.01 × 10⁵ tons in carbon storage, indicating that the land use allocation in this scenario contributes to the restoration of carbon storage and enhances the carbon sink capacity of the urban ecosystem. This study provides valuable insights for policymakers in optimizing ecosystem carbon storage from a land use perspective and offers essential guidance for the achievement of the “dual carbon” strategic objectives. Full article

Soil is an important link in the cycling of carbon, nitrogen, and other elements. The soil environment, especially the soil water, nutrients, and salts, undergoes profound changes in the process of oasis evolution. As a key component of the soil ecosystem in an oasis, soil microbial communities are strongly influenced by environmental factors and have feedback effects on them. However, the response of the soil microbial community structure and function to the process of oasis evolution and its mechanism is still unclear. In this study, the effects of different land-use types, including cotton field (CF), orchard (OR), forest land (FL), waste land (WL) and sand land (SL), on the soil microbial community structure and function were analyzed by metagenomic sequencing. The results showed that the cotton field had the highest soil water content, showing a significant difference compared with the other land-use types. Forest land had the highest soil pH, also showing a significant difference compared with the other land-use types. Among the land-use types with different degrees of oasis evolution, Pseudarthrobacter and Actinomycetota were the dominant phyla, with higher relative abundance. The main metabolic pathways in the cotton field, sand land, and waste land were L-glutamine biosynthesis, ornithine cycle, and nitrate reduction V. The soil total salt, moisture content, pH, and available potassium were the important soil physicochemical factors influencing soil microorganisms. This study will deepen our understanding of the role of soil microbial communities in the process of oasis evolution and provide a scientific basis for ecological restoration and desertification control in arid areas. Full article

This study introduces an innovative machine learning method to model the spatial variation of land surface temperature (LST) with a focus on the urban center of Da Nang, Vietnam. Light Gradient Boosting Machine (LightGBM), support vector machine, random forest, and Deep Neural Network are employed to establish functional relationships between urban LST and its influencing factors. The machine learning approaches are trained and validated using remote sensing data from 2014, 2019, and 2024. Various explanatory variables representing topographical and spatial characteristics, as well as urban landscapes, are used. Experimental results show that LightGBM outperforms other benchmark methods. In addition, Shapley Additive Explanations are utilized to clarify the impact of the factors affecting LST. The analysis outcomes indicate that while the importance of these variables changes over time, urban density and greenspace density consistently emerge as the most influential factors. LightGBM attained R² values of 0.85, 0.92, and 0.91 for the years 2014, 2019, and 2024, respectively. The findings of this work can be helpful for deeper understanding of urban heat stress dynamics and facilitate urban planning. Full article

This research examines the transformation of the Lake Pontchartrain coastal landscape, including the New Orleans shoreline. The paper addresses the critical need to understand long-term environmental change through a comprehensive geospatial analysis of historical cartographic representations. The study employs a methodology involving three key steps: (1) georeferencing maps using QGis v. 3.4.8., (2) vectorization using AutoCAD v. 2013, and (3) comparative spatial analysis to quantify coastal morphological changes. The quantitative results reveal significant coastal dynamics, with Lake Pontchartrain experiencing a total erosion balance of −36.42 km², although the New Orleans coastal zone has experienced land reclamation. This loss can be attributed to the synergistic interaction of natural (e.g., subsidence, sea level rise, hurricanes) and anthropogenic (e.g., urban development, infrastructure, ecological fragmentation) processes that have accelerated coastal erosion in the study area. The research provides a critical historical analysis of the evolution of coastal landscapes in response to anthropogenic influences. However, the methodology is constrained when it comes to addressing the socioeconomic impacts. Nevertheless, the study considered the profound environmental and societal consequences of historical governmental and social decisions, thereby underscoring the intricate interplay between natural processes and human intervention in coastal ecosystems. These findings contribute to a more profound comprehension of the processes of coastal landscape transformation, underscoring the dynamic and fragile nature of coastal environments. Full article

Camera localization approaches often degrade in challenging environments characterized by illumination variations and significant viewpoint changes, presenting critical limitations for fixed-wing aircraft landing applications. To address these challenges, we propose LandNet—a novel absolute camera pose estimation network specifically designed for airborne scenarios. Our framework processes images from forward-looking aircraft cameras to directly predict 6-DoF camera poses, subsequently enabling aircraft pose determination through rigid transformation. As a first step, we design two encoders from Transformer and CNNs to capture complementary spatial–temporal features. Furthermore, a novel Feature Interactive Block (FIB) is employed to fully utilize spatial clues from the CNN encoder and temporal clues from the Transformer encoder. We also introduce a novel Attentional Convtrans Fusion Block (ACFB) to fuse the feature maps from encoder and transformer encoder, which can enhance the image representations to promote the accuracy of the camera pose. Finally, two Multi-Layer Perceptron (MLP) heads are applied to estimate 6-DOF of camera position and orientation, respectively. Thus the estimated position and orientation of our LandNet can be further used to acquire the pose and orientation of the aircraft through the rigid connection between the airborne camera and the aircraft. The experimental results from simulation and real flight data demonstrate the effectiveness of our proposed method. Full article

Human activities and climate change have accelerated land use and land cover change (LUCC) globally, diminishing the ecosystem service value (ESV) in ecologically fragile areas such as highly mountainous canyons and disrupting the human–nature balance. However, existing research lacks analysis on the impact of land use changes on ecosystem service value in typical counties with highly mountainous canyon regions. Therefore, we aim to address this gap by analyzing land use changes and their driving factors in Chayu County using multi-year land use data, calculating the ecosystem service value (ESV) for different periods, and estimating its spatial correlation and stability. The results showed the following: (1) Forestland and grassland were the predominant land-use types, with notable conversions between grassland and water bodies, grassland and unused land, and water bodies and unused land. (2) The total ESV increased steadily from 2003 to 2023, with higher values in the north and west and lower values in the central east. Forestland and water areas were the primary contributors to ESV changes, and ESV sensitivity to LUCC steadily increased from 0.46% to 2.49%. (3) Moran’s I ESV shows an overall increase, with a heightened correlation and enhanced stability. Spatially, the ESV exhibited a general high–high and low–low clustering pattern, with localized high–low and low–high clusters. These changes, driven by natural resource endowments and climate change, provide essential support for ecological protection and sustainable development in highly mountainous canyons and similar regions. Full article

Land desertification management in the Mu Us Desert has received widespread attention. Assessing land desertification sensitivity is crucial for desertification monitoring and management. This study constructed a comprehensive evaluation index system using four factors: dryness index, the number of windy and sandy days in the winter and spring, soil texture, and vegetation cover. Land sand sensitivity was divided into five grades, and multi-source data from the Ecological Functional Reserve of the Mu Us Desert from 2002 to 2022 were used to study spatial distribution and dynamic changes. The results show the following: (1) the overall land desertification sensitivity in the Mu Us Desert Ecological Functional Reserve decreased from 2002 to 2022, with the proportion of highly sensitive land decreasing from 92.39% to 82.75%, and the proportion of medium-, medium–low-, and low-sensitivity areas increasing from 0.63% to 1.70%. (2) Low-sensitivity areas were concentrated in Jingbian County, Hengshan District, and southern Uxin Banner. Southeast Otog Banner and northern Jingbian County saw the most significant decreases in land desertification sensitivity since 2002. (3) The four selected factors interacted, with increased vegetation cover being the most crucial factor. This study provides a reference for future ecological restoration in the Mu Us Desert area. Full article