Search Results (887)

The rapid urbanization process has accelerated the degradation of ecosystem services (ESs) in peri-urban rural areas of the Yangtze River Delta (YRD), leading to increasing landscape ecological risks (LERs). Establishing a scientifically grounded landscape ecological risk assessment (LERA) system and corresponding control strategies is therefore imperative. Using rural areas of Jiangning District, Nanjing as a case study, this research proposes an optimized dual-dimensional coupling assessment framework that integrates ecosystem service value (ESV) and ecological risk probability. The spatiotemporal evolution of LER in 2000, 2010, and 2020 and its key driving factors were further studied by using spatial autocorrelation analysis and geodetector methods. The results show the following: (1) From 2000 to 2020, cultivated land remained dominant, but its proportion decreased by 10.87%, while construction land increased by 26.52%, with minimal changes in other land use types. (2) The total ESV increased by CNY 1.67 × 10⁹, with regulating services accounting for over 82%, among which water bodies contributed the most. (3) LER showed an overall increasing trend, with medium- to highest-risk areas expanding by 55.37%, lowest-risk areas increasing by 10.10%, and lower-risk areas decreasing by 65.48%. (4) Key driving factors include landscape vulnerability, vegetation coverage, and ecological land connectivity, with the influence of distance to road becoming increasingly significant. This study reveals the spatiotemporal evolution characteristics of LER in typical peri-urban villages. Based on the LERA results, combined with terrain features and ecological pressure intensity, the study area was divided into three ecological management zones: ecological conservation, ecological restoration, and ecological enhancement. Corresponding zoning strategies were proposed to guide rural ecological governance and support regional sustainable development. Full article

Gully erosion refers to the landform formed by soil and water loss through gully development, which is a critical manifestation of soil degradation. However, research on the spatio-temporal variations in erosion gullies at the county scale remains insufficient, particularly regarding changes in gully aggregation and their driving factors. This study utilized high-resolution remote sensing imagery, gully interpretation information, topographic data, meteorological records, vegetation coverage, soil texture, and land use datasets to analyze the spatio-temporal patterns and influencing factors of erosion gully evolution in Bin County, Heilongjiang Province of China, from 2012 to 2022. Kernel density evaluation (KDE) analysis was also employed to explore these dynamics. The results indicate that the gully number in Bin County has significantly increased over the past decade. Gully development involves not only headward erosion of gully heads but also lateral expansion of gully channels. Gully evolution is most pronounced in slope intervals. While gentle slopes and slope intervals host the highest density of gullies, the aspect does not significantly influence gully development. Vegetation coverage exhibits a clear threshold effect of 0.6 in inhibiting erosion gully formation. Additionally, cultivated areas contain the largest number of gullies and experience the most intense changes; gully aggregation in forested and grassland regions shows an upward trend; the central part of the black soil region has witnessed a marked decrease in gully aggregation; and meadow soil areas exhibit relatively stable spatio-temporal variations in gully distribution. These findings provide valuable data and decision-making support for soil erosion control and transformation efforts. Full article

The ecological environment is crucial for human survival and development. As ecological issues become more pressing, studying the spatiotemporal evolution of ecological quality (EQ) and its driving mechanisms is vital for sustainable development. This study, based on MODIS data from 2000 to 2022 and the Google Earth Engine platform, constructs a remote sensing ecological index for the Beibu Gulf Urban Agglomeration and analyzes its spatiotemporal evolution using Theil–Sen trend analysis, Hurst index (HI), and geographic detector. The results show the following: (1) From 2000 to 2010, EQ improved, particularly from 2005 to 2010, with a significant increase in areas of excellent and good quality due to national policies and climate improvements. From 2010 to 2015, EQ degraded, with a sharp reduction in areas of excellent quality, likely due to urban expansion and industrial pressures. After 2015, EQ rebounded with successful governance measures. (2) The HI analysis indicates that future changes will continue the past trend, especially in areas like southeastern Chongzuo and northwestern Fangchenggang, where governance efforts were effective. (3) EQ shows a positive spatial correlation, with high-quality areas in central Nanning and Fangchenggang, and low-quality areas in Nanning and Beihai. After 2015, both high–high and low–low clusters showed changes, likely due to ecological governance measures. (4) NDBSI (dryness) is the main driver of EQ changes (q = 0.806), with significant impacts from NDVI (vegetation coverage), LST (heat), and WET (humidity). Urban expansion’s increase in impervious surfaces (NDBSI rise) and vegetation loss (NDVI decline) have a synergistic effect (q = 0.856), significantly affecting EQ. Based on these findings, it is recommended to control construction land expansion, optimize land use structure, protect ecologically sensitive areas, and enhance climate adaptation strategies to ensure continuous improvement in EQ. Full article

This study presents an integrative investigation of four rare and threatened plant species—Taraxacum kok-saghyz L.E. Rodin, Astragalus rubtzovii Boriss., Schmalhausenia nidulans (Regel) Petr., and Rheum wittrockii Lundstr.—native to the Ile Alatau and Ketmen ridges of the Northern Tian Shan in Kazakhstan. Combining chloroplast genome sequencing, geobotanical surveys, and anatomical and population structure analyses, we aimed to assess the ecological adaptation, genetic distinctiveness, and conservation status of these species. Field surveys revealed that population structures varied across species, with T. kok-saghyz and S. nidulans dominated by mature vegetative and generative individuals, while A. rubtzovii and R. wittrockii exhibited stable age spectra marked by reproductive maturity and ongoing recruitment. Chloroplast genome assemblies revealed characteristic patterns of plastid evolution, including structural conservation in S. nidulans and R. wittrockii, and a reduced inverted repeat region in A. rubtzovii, consistent with its placement in the IR-lacking clade of Fabaceae. Morphological and anatomical traits reflected habitat-specific adaptations such as tomentose surfaces, thickened epidermis, and efficient vascular systems. Despite these adaptations, anthropogenic pressures including overgrazing and habitat degradation pose significant risks to population viability. Our findings underscore the need for targeted conservation measures, continuous monitoring, and habitat management to ensure the long-term survival of these ecologically and genetically valuable endemic species. Full article

Unmanned Aerial Vehicle Remote Sensing (UAV-RS) has emerged as a transformative technology in high-resolution Earth observation, with widespread applications in precision agriculture, ecological monitoring, and disaster response. However, a systematic understanding of its scientific evolution and structural bottlenecks remains lacking. This study collected 4985 peer-reviewed articles from the Web of Science Core Collection and conducted a comprehensive scientometric analysis using CiteSpace v.6.2.R4, Origin 2022, and Excel. We examined publication trends, country/institutional collaboration networks, keyword co-occurrence clusters, and emerging research fronts. Results reveal an exponential growth in UAV-RS research since 2015, dominated by application-driven studies. Hotspots include vegetation indices, structure from motion modeling, and deep learning integration. However, foundational challenges—such as platform endurance, sensor coordination, and data standardization—remain underexplored. The global collaboration network exhibits a “strong hubs, weak bridges” pattern, limiting transnational knowledge integration. This review highlights the imbalance between surface-level innovation and deep technological maturity and calls for a paradigm shift from fragmented application responses to integrated systems development. Our findings provide strategic insights for researchers, policymakers, and funding agencies to guide the next stage of UAV-RS evolution. Full article

Vegetation plays a multifaceted role in the enhancement and conservation of archaeological sites, functioning not only as an aesthetic element but also as a core component of landscape architecture practice. This review traces the historical evolution of vegetation management, though the lens of landscape architecture, highlighting its potential as a design and planning tool for historical interpretation and sustainable integration of heritage sites into broader contexts. From Romantic landscaping ideals to modern interdisciplinary conservation frameworks, the review draws on key milestones such as the Athens and Venice Charters, and examines case studies like Rome’s Passeggiata Archeologica, the Acropolis slopes, Ruffenhofen Park, and Campo Lameiro. These examples illustrate how landscape architectural approaches can use vegetation to reconstruct lost architectural forms, enhance visitor engagement, and provide ecosystem functions. The article also addresses challenges related to historical authenticity, species selection, and ecological performance, arguing for future strategies that integrate archaeological sites into dynamic, living heritage systems, through collaborative, ecologically informed design. Full article

Vegetation and soil indices are able to indicate patterns of gradual plant growth. Therefore, productivity data may be used to predict performance in the development of pastures prior to grazing, since the morphology of the pasture follows repetitive cycles through the grazing of animals. Accordingly, in recent decades, much attention has been paid to the monitoring and development of vegetation by means of remote sensing using remote sensors. The current study seeks to determine the differences between three remote sensing products in the monitoring and development of white clover and perennial ryegrass ratios. Various grass and legume associations (perennial ryegrass, Lolium perenne, and white clover, Trifolium repens) were evaluated in different proportions to determine their yield and relationship through vegetation and soil indices. Four proportions (%) of perennial ryegrass and white clover were used, being 100:0; 90:10; 80:20 and 70:30. Likewise, to obtain spectral indices, a Spectral Evolution PSR-1100 spectroradiometer was used, and two UAVs with a MAPIR 3W RGNIR camera and a Parrot Sequoia multispectral camera, respectively, were employed. The data collection was performed before and after each cut or grazing period in each experimental unit, and post-processing and the generation of spectral indices were conducted. The results indicate that there were no significant differences between treatments for yield or for vegetation indices. However, there were significant differences in the index variables between sensors, with the spectroradiometer and Parrot obtaining similar values for the indices both pre- and post-grazing. The NDVI values were closely correlated with the yield of the forage proportions (R² = 0.8948), constituting an optimal index for the prediction of pasture yield. Full article

Our study focused on identifying the evolution of soil erosion and its key drivers under multiple future scenarios in the Yiluo River Basin. Integrating the Universal Soil Loss Equation (USLE), future land use and vegetation cover simulation methods, and the Geodetector model, we analyzed historical soil erosion trends (2000–2020), projected future soil erosion risks under multiple Shared Socioeconomic Pathways (SSPs), and quantified the interactive effects of key driving factors. The results showed that soil erosion within the basin exhibited moderate intensity. Over the past 20 years, soil erosion decreased by 28.78%, with 76.29% of the area experiencing reduced erosion intensity. Future projections indicated an overall declining trend in soil erosion, showing reductions of 4.93–35.95% compared to baseline levels. However, heterogeneous patterns emerged across various scenarios, with the highest risk observed under SSP585. Land use type was identified as the core driving factor behind soil erosion (explanatory capacity q-value > 5%). Under diverse future climate scenarios, interactions between land use type and precipitation and temperature exhibited high sensitivity, highlighting the critical regulatory role of climate change in regulating erosion processes. This research provides a scientific foundation for the precise prevention and adaptive management of soil erosion in the Loess Plateau region. Full article

Urban vegetation shows significant spatial differences due to the combined effects of natural and human factors, yet fine-scale evolutionary patterns and their cross-scale feedback mechanisms remain limited. This study focuses on the Yangtze River Delta (YRD), the top economic area in China. By integrating data from multiple Landsat sensors, we built a high—resolution framework to track vegetation dynamics from 1990 to 2020. It generates annual 30-m Enhanced Vegetation Index (EVI) data and uses a new Vegetation Green—Brown Balance Index (VBI) to measure changes between greening and browning. We combined Mann-Kendall trend analysis with machine—learning based attribution analysis to look into vegetation changes across different city types and urban—rural gradients. Over 30 years, the YRD’s annual EVI increased by 0.015/10 a, with greening areas 3.07 times larger than browning. Spatially, urban centers show strong greening, while peri—urban areas experience remarkable browning. Vegetation changes showed a city-size effect: larger cities had higher browning proportions but stronger urban cores’ greening trends. Cluster analysis finds four main evolution types, showing imbalances in grey—green infrastructure allocation. Vegetation baseline in 1990 is the main factor driving the long-term trend of vegetation greenness, while socioeconomic and climate drivers have different impacts depending on city size and position on the urban—rural continuum. In areas with low urbanization levels, climate factors matter more than human factors. These multi-scale patterns challenge traditional urban greening ideas, highlighting the need for vegetation governance that adapts to specific spatial conditions and city—unique evolution paths. Full article

Vegetation is a fundamental component of terrestrial ecosystems. Understanding how vegetation changes and what drives these evolutions is crucial for developing a high-quality ecological environment and addressing global climate change. Extensive evidence has shown that China has undergone substantial vegetation changes, characterized primarily by greening. To quantify vegetation dynamics in China and assess the contributions of various drivers, we explored the spatiotemporal variations in the kernel Normalized Difference Vegetation Index (kNDVI) from 2001 to 2020, and quantitatively separated the influences of climate and human factors. The kNDVI time series were generated from the MCD19A1 v061 dataset based on the Google Earth Engine (GEE) platform. We employed the Theil-Sen trend analysis, the Mann-Kendall test, and the Hurst index to analyze the historical patterns and future trajectories of kNDVI. Residual analysis was then applied to determine the relative contributions of climate change and human activities to vegetation dynamics across China. The results show that from 2001 to 2020, vegetation in China showed a fluctuating but predominantly increasing trend, with a significant annual kNDVI growth rate of 0.002. The significant greening pattern was observed in over 48% of vegetated areas, exhibiting a clear spatial gradient with lower increases in the northwest and higher amplitudes in the southeast. Moreover, more than 60% of vegetation areas are projected to experience a sustained increase in the future. Residual analysis reveals that climate change contributed 21.89% to vegetation changes, while human activities accounted for 78.11%, being the dominant drivers of vegetation variation. This finding is further supported by partial correlation analysis between kNDVI and temperature, precipitation, and the human footprint. Vegetation dynamics were found to respond more strongly to human influences than to climate drivers, underscoring the leading role of human activities. Further analysis of tree cover fraction and cropping intensity data indicates that the greening in forests and croplands is primarily attributable to large-scale afforestation efforts and improved agricultural management. Full article

The Saiss plain in northern Morocco covers an area of 2300 km² and is one of the main agricultural contributors to the national economy. However, climate change and water scarcity reduce the region’s agricultural yields. Conventional methods of estimating evapotranspiration (ET) provide localized results but cannot capture regional-scale variations. This study aims to estimate the spatiotemporal evolution of daily crop ET (olives, fruit trees, cereals, and vegetables) across the Saiss plain. The METRIC model was adapted for the region using Landsat 8 data and was calibrated and validated using in situ flux tower measurements. The methodology employed an energy balance approach to calculate ET as a residual of net radiation, soil heat flux, and sensible heat flux by using hot and cold pixels for calibration. METRIC-ET ranged from 0.1 to 11 mm/day, demonstrating strong agreement with reference ET (R² = 0.76, RMSE = 1, MAE = 0.78) and outperforming MODIS-ET in accuracy and spatial resolution. Olives and fruit trees showed higher ET values compared to vegetables and cereals. The results indicated a significant impact of ET on water availability, with spatiotemporal patterns being influenced by vegetation cover, climate, and water resources. This study could support the development of adaptive agricultural strategies. Full article

The possibility of collecting new archaeological elements useful in reconstructing the dynamics of population, production and commercial activities in the Bronze Age at the edge of the central-southern Venice Lagoon was provided between 2023 and 2024 thanks to an intervention of rescue archaeology planned during some water restoration works in the Giare–Mira area. Three small excavations revealed, approximately one meter below the current surface and covered by alluvial sediments, a rather complex palimpsest dated to the late Recent and the early Final Bronze Age. Three large circular pits containing exclusively purified grey/blue clay and very rare inclusions of vegetable fibres, and many large, fired clay vessels’ bases, walls and rims clustered in concentrated assemblages and random deposits point to potential on-site production. Two pyro-technological structures, one characterised by a sub-circular combustion chamber and a long inlet channel/praefurnium, and the second one with a sub-rectangular shape with arched niches along its southern side, complete the exceptional context here discovered. To analyse the relationship between the site and the natural sedimentary succession and to evaluate the possible extension of this site, three electrical resistivity tomography (ERT) and low-frequency electromagnetic (FDEM) measurements were collected. Several manual core drillings associated with remote sensing integrated the geophysical data in the analysis of the geomorphological evolution of this area, clearly related to different phases of fluvial activity, in a framework of continuous relative sea level rise. The typology and chronology of the archaeological structures and materials, currently undergoing further analyses, support the interpretation of the site as a late Recent/early Final Bronze Age productive site. Geophysical and geomorphological data provide information on the palaeoenvironmental setting, suggesting that the site was located on a fine-grained, stable alluvial plain at a distance of a few kilometres from the lagoon shore to the south-east and the course of the Brenta River to the north. The archaeological site was buried by fine-grained floodplain deposits attributed to the Brenta River. The good preservation of the archaeological structures buried by fluvial sediments suggests that the site was abandoned soon before sedimentation started. Full article

This study developed a coupled hydrodynamic-sediment-vegetation model to investigate the effects of Spartina alterniflora management and Suaeda salsa restoration on coastal wetland geomorphological evolution and vegetation distribution. Special attention is paid to the regulatory roles of tidal dynamics, sea-level rise, sediment supply, and sediment characteristics. The study shows that the management of Spartina alterniflora significantly alters the sediment deposition patterns in salt marsh wetlands, leading to intensified local erosion and a decline in the overall stability of the wetland system; meanwhile, the geomorphology of wetlands restored with Suaeda salsa is influenced by tidal range, sediment settling velocity, and suspended sediment concentration, exhibiting different deposition and erosion patterns. Under the scenario of sea-level rise, when sedimentation rates fail to offset the rate of sea-level increase, the wetland ecosystem faces the risk of collapse. This study provides scientific evidence for the ecological restoration and management of coastal wetlands and offers theoretical support for future wetland conservation and restoration policies. Full article

As a crucial ecological barrier in China, the Greater Khingan Mountains play a vital role in global ecological security. Investigating the spatiotemporal variations in fractional vegetation cover (FVC) and the driving mechanisms behind its spatial differentiation is essential. This study introduced a KNDVI-XGeoML framework integrating the Kernel NDVI and explainable geospatial machine learning to analyze the FVC dynamics and the mechanisms driving their spatial differentiation in China’s Greater Khingan Mountains, based on which targeted ecological management strategies were proposed. The key findings reveal that (1) from 2001 to 2022, FVC showed an increasing trend, confirming the effectiveness of ecological restoration. (2) The XGeoML model successfully revealed nonlinear relationships and threshold effects between driving factors and FVC. In addition, both single-factor importance and inter-factor interaction analyses consistently showed that landform factors dominated the spatial distribution of FVC. (3) Regional heterogeneity emerged—human activities drove the northern alpine zones, while landform factors governed other areas. (4) The natural-environment-dominated zones and human-activity-dominated zones were established, and management strategies were proposed: restricting tourism in low-altitude zones, optimizing the cold-resistant vegetation at high elevations, and improving the southern soil conditions to support ecological barrier construction. The innovation lies in merging nonlinear vegetation indices with interpretable machine learning, overcoming the traditional limitations in terms of saturation effects and analyses of spatial heterogeneity. This approach enhances our understanding of high-latitude vegetation dynamics, offering a methodological advancement for precision ecological management. The spatial zoning strategy based on dominant drivers provides actionable insights for maintaining this critical ecological barrier, particularly under climate change pressures. The framework demonstrates strong potential for extrapolation to other ecologically sensitive regions requiring data-driven conservation planning. Full article

Research on the supply–demand relationships of ecosystem services (ESs) in alpine pastoral regions remains relatively scarce, yet it is crucial for regional ecological management and sustainable development. This study focuses on the Sanjiangyuan Region, a typical alpine pastoral area and significant ecological barrier, to quantitatively assess the supply–demand dynamics of key ESs and their spatial heterogeneity from 2000 to 2020. It further aims to elucidate the underlying driving mechanisms, thereby providing a scientific basis for optimizing regional ecological management. Four key ES indicators were selected: water yield (WY), grass yield (GY), soil conservation (SC), and habitat quality (HQ). ES supply and demand were quantified using an integrated approach incorporating the InVEST model, the Revised Universal Soil Loss Equation (RUSLE), and spatial analysis techniques. Building on this, the spatial patterns and temporal evolution characteristics of ES supply–demand relationships were analyzed. Subsequently, the Geographic Detector Model (GDM) and Geographically and Temporally Weighted Regression (GTWR) model were employed to identify key drivers influencing changes in the comprehensive ES supply–demand ratio. The results revealed the following: (1) Spatial Patterns: Overall ES supply capacity exhibited a spatial differentiation characterized by “higher values in the southeast and lower values in the northwest.” Areas of high ES demand were primarily concentrated in the densely populated eastern region. WY, SC, and HQ generally exhibited a surplus state, whereas GY showed supply falling short of demand in the densely populated eastern areas. (2) Temporal Dynamics: Between 2000 and 2020, the supply–demand ratios of WY and SC displayed a fluctuating downward trend. The HQ ratio remained relatively stable, while the GY ratio showed a significant and continuous upward trend, indicating positive outcomes from regional grass–livestock balance policies. (3) Driving Mechanisms: Climate and natural factors were the dominant drivers of changes in the ES supply–demand ratio. Analysis using the Geographical Detector’s q-statistic identified fractional vegetation cover (FVC, q = 0.72), annual precipitation (PR, q = 0.63), and human disturbance intensity (HD, q = 0.38) as the top three most influential factors. This study systematically reveals the spatial heterogeneity characteristics, dynamic evolution patterns, and core driving mechanisms of ES supply and demand in an alpine pastoral region, addressing a significant research gap. The findings not only provide a reference for ES supply–demand assessment in similar regions regarding indicator selection and methodology but also offer direct scientific support for precisely identifying priority areas for ecological conservation and restoration, optimizing grass–livestock balance management, and enhancing ecosystem sustainability within the Sanjiangyuan Region. Full article