Search Results (2,467)

Land use and land cover (LULC) dynamics are critical indicators of environmental transformation and anthropogenic pressure on regional landscapes. Mirzapur, located in the transitional zone between the Indo-Gangetic Plain and the Vindhyan uplands in Northern India, represents a region characterized by ecological sensitivity, mineral-based industries, agricultural dependency, and rapid infrastructural growth. In recent decades, Northern India has experienced accelerated urbanization, population pressure, land fragmentation, and environmental stress, thus making systematic LULC monitoring crucial for sustainable resource management and policy planning. The present study examines the spatio-temporal changes in land use and land cover in Mirzapur for the years 2004, 2014, and 2024. The study employed a cloud-based platform and the Random Forest algorithm for supervised classification of multi-temporal satellite imagery. LULC maps were generated and post classification comparison was used to assess changes across the selected years. Accuracy assessment was conducted using standard validation metrics, including the Kappa coefficient, to evaluate classification. From 2004 to 2024, urban areas expanded by a relative increase of 169.36%, largely through the conversion of cropland, although the overall cropland area showed a slight increase due to agricultural expansion in other parts of the study area. A slight increase in forest cover was also observed during this period. Water bodies and barren lands declined, indicating ecological stress in the region. These changes reflect rapid urbanization, demographic pressure, and evolving socio-economic activities within the district. The LULC classification achieved overall accuracies of 96.50% (2004), 97.52% (2014), and 96.08% (2024), showing the reliability of the generated maps. The study demonstrates the effectiveness of cloud-based geospatial analysis combined with a machine learning algorithms for long-term LULC monitoring and provides valuable insights for sustainable land management and regional planning. Full article

Understanding spatiotemporal changes in landscape ecological risk is essential for regional ecological security and sustainable land management, particularly in environmentally sensitive areas. Using land-use data from five time points (2000, 2005, 2010, 2015, and 2020) together with topographic, climatic, vegetation, and socioeconomic data, we assessed landscape ecological risk dynamics in Xinzhou City, a typical ecologically sensitive region in the middle Yellow River Basin. We integrated a landscape ecological risk assessment model, spatial autocorrelation analysis, and an optimal-parameter geographical detector (OPGD) to identify the spatiotemporal patterns and key drivers of ecological risk. Built-up land expanded by 131.47% over the study period, while cropland and grassland both contracted. Land-use change was dominated by bidirectional conversion between cropland and grassland, alongside a net shift of both to built-up land. Overall, ecological risk declined: high- and relatively high-risk areas decreased by 1354.15 km². Spatially, the pattern remained stable, with higher risk in basins and lower risk in mountainous regions, although the trend varied across phases. Risk exhibited significant spatial clustering: low–low clusters remained stable in mountainous ecological source areas, whereas high–high clusters persisted in basin agricultural areas. Elevation was the dominant factor in spatial risk differentiation. Combined natural and anthropogenic factors shaped the overall risk pattern. Despite the regional decline, urbanization-induced disturbance remains the principal driver of local risk increases. Our findings demonstrate the value of coupling long-term land-use data with OPGD to evaluate the relative and interactive contributions of terrain constraints and anthropogenic drivers in complex mountain–basin systems, with implications for spatially targeted ecological restoration and sustainable land management in ecologically sensitive transition zones. Full article

The design of urban pedestrian–cycling routes is of great importance for the sustainable development of cities. Properly designed routes encourage the use of sustainable modes of transport. They also bring numerous environmental and social benefits. The study examines how greenery and spatial characteristics influence citizens’ aesthetic perception of pedestrian and cycling corridors. The Scenic Beauty Estimation (SBE) method was used to assess visual landscape quality based on users’ subjective evaluations. A total of 301 participants evaluated 20 photographs taken in Lublin, Poland, depicting different types of urban routes, including sidewalks, cycling paths, and park pathways, using a five-point rating scale. Statistical analyses (ANOVA, post hoc tests, and composite and differential variable analyses) were conducted to identify patterns in preferences. The results indicate that greenery is the dominant factor shaping landscape preferences across all age and gender groups. Age plays a stronger role than gender in differentiating evaluations: younger participants prefer more natural and greener environments, whereas older participants favor more ordered and less green spaces. Gender effects are limited and primarily relate to preferences for natural landscapes. An additional finding concerns the role of benches, which were most preferred by younger and middle-aged women, suggesting a broader social and functional interpretation of this element. Overall, the results highlight the importance of greenery in shaping the perceived attractiveness of urban routes. They also indicate the key spatial features that encourage people to use these routes, which affects the use of sustainable modes of transport as well as residents’ health. They also demonstrate the usefulness of the SBE method in planning, design and managing user-friendly and sustainable urban routes. Full article

The concentrations of 18 chemical elements were determined in the upper soil horizons within the landscapes of river basins in the Eastern Caucasus, using the Ulluchay, Sulak, Sunzha, Samur, Shuraozen (Russia), Karachay, and Atachay (Azerbaijan) rivers as case studies. This research aims to provide an ecological and geochemical assessment of soil conditions in the mountain river basins of the Eastern Caucasus. The ecological status of the soils is largely governed by elevated concentrations of such elements as Zn, Ni, Cu, Mo, As, and Cr, which exhibit both accumulation tendencies and potential toxicity. Environmentally unfavorable areas were identified through an integrated scoring assessment that incorporates the values of four ecological and geochemical indices: the modified contamination factor (mCf), the Pollution Load Index (PLI), the Potential Ecological Risk Index (PERI), and the total contamination index (Zc). According to each index, more than half of the study area is classified as uncontaminated. Low PLI values were recorded for 54% of the sampling sites, and low mCf values for 63%. Based on PERI and Zc, 82% of the sampling sites are categorized as uncontaminated. The integral scoring assessment enabled the delineation of more than a dozen environmentally unfavorable areas, with the highest concentrations observed in the Atachay and Karachay basins, spatially extensive in the Sunzha basin. The formation of environmentally unfavorable zones in terms of soil contamination is primarily driven by natural factors, including lithological conditions, climatic features, complex topography, and the directions of waterborne and mechanical migration. Anthropogenic factors contribute to a lesser extent to the development of high-contamination zones and exert only localized influences near major settlements. The results can be applied to mitigate public health risks and to promote sustainable development of mountain river basins. Targeted measures are proposed for the sustainable management of contaminated areas, including restrictions on agricultural activities and the use of drinking water sources. Full article

Soil organic carbon (SOC) stock is a key component of terrestrial ecosystems, playing a critical role in climate regulation and ecosystem productivity. Despite its economic importance, the impacts of the expansion of khat (Catha edulis) cultivation at the expense of other land uses and its intensive management practices on the depletion of soil carbon content are overlooked in Eastern Ethiopia. This study aimed to estimate and map SOC stocks using multispectral Sentinel-2 and RapidEye imagery, combined with environmental, soil, and topographic variables, across khat-dominated landscapes in the Haramaya District of Eastern Ethiopia. A total of 88 soil samples were collected and analyzed to quantify SOC stocks. Random Forest (RF) and extreme gradient boosting (XGBoost) algorithms were employed to predict SOC stocks. The dataset was stratified into training (70%) and an independent validation (30%) subset. Model development was performed using five-fold cross-validation on the training dataset, while final performance was assessed on the independent validation set using the coefficient of determination (R²), root mean square error (RMSE) and mean absolute error (MAE). Laboratory-measured SOC stocks ranged from 24.99 to 65.94 Mg C ha⁻¹, with a mean value of 36.88 Mg C ha⁻¹. The predicted spatial SOC stocks ranged from 30.4 to 50.4 Mg C ha⁻¹ using RapidEye data and from 32.8 to 51.5 Mg C ha⁻¹ using Sentinel-2, with Sentinel-2 producing slightly higher mean estimates. The lowest SOC stocks were consistently observed in bare, grass, and shrub land-use types across both datasets. RF demonstrated superior performance compared with XGBoost, achieving moderate predictive performance for both the RapidEye (R² = 0.56, RMSE = 5.91 Mg C ha⁻¹) and Sentinel-2 (R² = 0.42, RMSE = 6.90 Mg C ha⁻¹) datasets. This result indicates that RF provided greater robustness for SOC stock prediction under the heterogeneous environmental conditions of khat-dominated agricultural landscapes. Topographic and soil-related variables, particularly the Topographic Wetness Index (TWI), land surface temperature (LST), and clay content, were identified as the most influential predictors in both models. Although less consistent, remote sensing indices such as GNDVI, BSI, and NDWI also contributed to SOC prediction. While both sensors proved effective for SOC mapping, a measurable sensor-related effect was observed. The findings demonstrate the effectiveness of integrating multisource remote sensing, environmental, soil, and topographic variables with machine learning for SOC stock mapping in khat-dominated landscapes. This approach provides valuable spatial information to understand SOC variability and support sustainable land management and climate change mitigation strategies in Eastern Ethiopia. Full article

Impervious surfaces create heterogeneous planting sites for urban trees, but whether crown-scale sealing is associated jointly with leaf economics and reproductive dispersal morphology remains unclear. We aimed to test these associations in mature female Populus tomentosa while treating impervious surface area (ISA) as a composite indicator of site context rather than a direct measure of thermal or hydrological stress. In a single-season, cross-sectional survey of 180 trees in Beijing (60 per low-, mid-, and high-ISA descriptive stratum), we measured crown-scale ISA, short-term midday ground-surface temperature, a pervious-soil access-moisture index (PSAMI), eight leaf traits, and five reproductive traits, and analyzed continuous associations, group contrasts, effect sizes, and multivariate patterns. Greater ISA was associated with lower PSAMI (R² = 0.581) and higher land surface temperature (R² = 0.845). Compared with low-ISA trees, high-ISA trees had lower specific leaf area (117.5 ± 29.1 vs. 90.9 ± 19.0 cm² g⁻¹; Hedges’ g = −1.07, 95% CI [−1.50, −0.71]) and longer seed hairs (0.564 ± 0.067 vs. 0.727 ± 0.078 cm; g = 2.24, 95% CI [1.82, 2.78]), together with greater fuzz biomass and lower seed mass. Multivariate analyses showed coordinated shifts in mean leaf and reproductive phenotype without stronger within-stratum cross-module integration. We conclude that the study’s principal contribution is the joint description of vegetative economics and reproductive dispersal morphology on the same mature urban trees. Because ISA co-varied with land use and management and PSAMI includes structural zeros, the findings are preliminary and do not establish causal stress mechanisms, plant-available water status, airborne exposure, or management effects; multi-year matched-site validation is required. Full article

The Taklimakan Desert Highway shelterbelt is the world’s largest ecological protection system established along a highway in a shifting desert environment and plays a critical role in mitigating wind-blown sand hazards and ensuring transportation safety. However, its long-term stability and protective capacity after more than two decades of operation remain insufficiently understood. In this study, Landsat imagery from 2005 to 2025 was used to monitor the long-term evolution of the shelterbelt along the Middle Section (~180 km) of the Taklimakan Desert Highway. A Random Forest classifier was employed to extract shelterbelt distribution, and classification results were validated using high-resolution Google Earth imagery and unmanned aerial vehicle observations. To quantify shelterbelt condition, a Shelterbelt Stability Index (SSI) was developed by integrating fractional vegetation cover (FVC), connectivity index (CI), percentage of landscape (PLAND), and perimeter-area fractal dimension (FRAC). The shelterbelt experienced initial seedling decline from 2005 to 2011, followed by progressive restoration during 2011–2020 and finally entered a stable saturated stage after 2020. Affected by saline water drip irrigation, wind-sand erosion and pipeline clogging, the overall vegetation condition deteriorated continuously before 2011. After targeted irrigation regulation, optimization of planting patterns and replanting measures were implemented; the degradation trend was reversed, contributing to the sustained improvement of vegetation thereafter. Significant spatial heterogeneity was observed along the highway, with certain sections maintaining high continuity and vegetation coverage, while others exhibited fragmentation, local discontinuities, area shrinkage, and increasing structural complexity. The proposed SSI effectively captured long-term structural dynamics and identified vulnerable sections subject to degradation. This study provides new insights into the life-cycle evolution of desert highway shelterbelts and offers scientific support for the sustainable management of ecological protection systems in arid environments. Full article

Urban form profoundly influences the effectiveness of coordinated management of carbon emissions and air pollution, which is of great significance for sustainable urban development. This study took 336 Chinese cities as research samples and used carbon emissions, PM_2.5, and nighttime light datasets from 2000 to 2020 to investigate the contribution of urban form to the degree of coordination between urban carbon emissions and PM_2.5. We constructed a multi-dimensional indicator system for urban form and adopted the coupling coordination degree (CCD) model to quantify the coordinated development of these two variables. A novel analytical framework was established using the stacking ensemble learning model. Combined with the SHAP method, this framework provided nonlinear associations of various urban morphological factors with the CCD. The results are as follows: (1) The stacking ensemble model performs best in capturing high-dimensional nonlinear relationships, with test set R², RMSE, and RPD values of 0.75, 0.082, and 1.98, respectively. (2) Urban form exhibits nonlinear threshold effects on the carbon-pollution coordination degree. The top predictors contributing to the model output are the class area (CA), the landscape shape index (LSI), the percentage of like adjacencies (PLADJ), and the number of patches (NP). Among them, CA exhibits a monotonically increasing asymptotic saturation response, while the LSI presents an inverted U-shaped response. (3) The contribution of urban form to the CCD exhibits significant spatial heterogeneity. The developed regions of eastern China constitute the high-sensitivity zone of the CCD, and are mainly constrained by scale expansion, land fragmentation, and excessive agglomeration, while the central and western regions show the low-sensitivity zone of the CCD. These results offer a scientific reference for designing pollution control and carbon mitigation strategies. Full article

The Inner Mongolia Autonomous Region, located in northern China, spans a vast territory. It serves as a crucial transitional zone connecting three major ecosystems—forest, grassland, and desert—and constitutes an essential component of the nation’s ecological security barrier. Over the past three decades, significant changes have occurred in the region’s land use structure and landscape patterns. Based on long-term time-series land use data, this study systematically analyzed land cover changes and landscape diversity characteristics by dividing the region into climatic zones, ecological zones, and administrative areas. Additionally, a driver analysis framework based on the eXtreme Gradient Boosting (XGBoost) model was constructed, and the SHapley Additive exPlanations (SHAP) method was employed to quantitatively identify the contribution rates of driving factors influencing the Shannon Diversity Index (SHDI). Results indicate pronounced spatial heterogeneity in land-use structure dynamics across regions. Among all land use types, grasslands, croplands, and bare land exhibited the most pronounced changes under the combined influence of natural environmental variations and human disturbances. Against this backdrop of landscape pattern evolution, the regional Shannon Diversity Index (SHDI) also showed differentiated variation trends. Based on SHAP contribution analysis, population density (POP) was identified as the primary driver affecting SHDI changes, with a contribution rate of 29.9%, followed by precipitation (PRE, 19.5%), elevation (DEM, 17.2%), and GDP (11.9%). Further SHAP response analysis revealed the nonlinear effects and characteristics of different driving factors on SHDI, indicating that the proposed framework can effectively elucidate the driving mechanisms of landscape changes. The findings provide scientific support for developing sustainable and differentiated land-use management strategies and optimizing ecological conservation and restoration measures across regions with diverse ecological backgrounds. Full article

Extensive livestock farming is characteristic of the landscape of the Mediterranean regions of Southern Iberian Peninsula. These production systems based on dryland pastures provide a wide range of services and contribute to maintaining environmental balance when compared with intensive agricultural or other livestock production systems. The Portuguese Montado is a habitat of Community importance and is protected under the European Natura 2000 network. This makes any research aimed at preserving, maintaining, or restoring this ecosystem particularly important to ensure its sustainable management. The main objectives of this study were to evaluate: (i) the impact of dolomitic limestone application on soil pH; (ii) the relation between multiple soil parameters; (iii) the impact of grazing preferences and livestock stocking rates on topsoil compaction; (iv) temporal and spatial sheep grazing patterns and sward productivity, quality and floristic composition throughout the growing vegetative season. This study was carried out during the vegetative cycle of 2023/2024 on a 4-ha pasture field located at Mitra farm (Southern Portugal). The experimental design included four treatments resulting from the combination of limestone application (with and without) and stocking rate (traditional: 7 sheep ha⁻¹; high: 18 sheep ha⁻¹). Sheep grazing preferences, soil compaction and fertility, sward productivity, quality and floristic composition were monitored at 48 sampling areas. The results confirm that improving soil pH through the application of dolomitic limestone is an effective, although slow and gradual process. When combined with grazing management through increased stocking rates, several important outcomes were observed: (i) preferential grazing areas did not exhibit significant differences in soil trampling; (ii) higher stocking rates resulted in less selective grazing; (iii) soil amendment and higher livestock stocking rates contributed to greater pasture crude protein content; and (iv) the influence of pasture quality on grazing preferences depended on the phase of the pasture-grazing cycle. Overall, these findings are promising indicators of sustainability for extensive animal production in Mediterranean dryland silvopastoral systems. However, with regard to the sward, as this study only monitored a single growing season, will need to be validated in future studies. Full article

This article examines the conceptual and practical relationships between UNESCO’s 2011 Historic Urban Landscape (HUL) Recommendation and the European Commission’s 2020 Circular Economy (CE) Action Plan, bringing together cultural heritage conservation and sustainable resource management. A comparative analysis was conducted using directed qualitative content analysis across four analytical themes: value systems, resource management, governance models, and sustainability perspectives. Building upon these results, this article proposes the circular cultural landscape (CCL) model, which positions cultural heritage as an active component of circular systems through four interconnected layers. To illustrate its potential applicability, the model is translated into a preliminary assessment framework through the proposed CCL index and conceptually demonstrated using a hypothetical scenario in the Balat neighborhood of Istanbul. Rather than providing empirical validation, the scenario illustrates how the framework may support the integrated assessment of cultural, environmental, social, and economic sustainability in historic urban landscapes. The proposed CCL model offers a conceptual and methodological foundation for future research and decision support in sustainable heritage management. Full article

Isotopic and nuclear techniques, including fallout radionuclides (FRNs), fingerprinting (FP), and isotope hydrology (IH), are essential tools for assessing soil and water degradation. However, as in state-of-the-art reviews, isolated application of FRNs, FP and IH limits their potential to address complex, interconnected environmental processes across landscapes. This study proposes a novel methodology based on the concept of Synergistic Convergence to integrate FRNs, FP, and IH into a unified framework for assessing soil and water degradation. Validated through a case study in Cuba’s Hanabanilla sub-basin, the five-stage methodology improves the identification of erosion hotspots, sediment sources, and water resource vulnerabilities. Results demonstrate that combining FRNs (quantifying soil redistribution), FP (tracing sediment sources), and IH (evaluating water dynamics) provides a robust approach for sustainable landscape management, according to the United Nations Sustainable Development Goals (SDGs) and the One Health framework. The integrated methodology proves superior to the non-integrated approach, connecting causes (erosion), drivers (water), and consequences (sedimentation, pollution). The Synergistic Convergence methodology effectively integrates isotopic and nuclear techniques (INTs) (FRNs, FP, and IH), enabling a holistic assessment of soil and water degradation and their interactions within terrestrial and aquatic ecosystems. Full article

Nature-Based Solutions (NBS) have emerged as a key strategy to address complex and intensifying urban sustainability challenges, yet empirical assessments of regulatory frameworks that operationalize these strategies remain limited. This study addresses that gap through an empirical evaluation of the Green Area Ratio (GAR), a hybrid performance-based zoning regulation for sustainable landscapes in Washington, DC, using more than a decade of regulatory implementation data. Regulatory plan approval records from 1329 private properties subject to GAR between 2015 and 2025 were analyzed to examine trends in landscaping Best Management Practice (BMP) selection, relationships with parcel characteristics, and interactions with stormwater management requirements. Over this period, approximately 184 ha of multifunctional NBS were approved through GAR plans primarily consisting of landscaping areas, plantings, and tree planting and preservation, often combined through BMP stacking and amplified by a native plant bonus. BMP selection varied significantly according to zoning district, lot area, and GAR Score Requirement. Importantly, GAR requirements influenced BMP selection differently than stormwater requirements. The findings suggest that simplicity, flexibility, and adaptability of the GAR make the regulation a versatile policy instrument for DC and a useful model for cities seeking to expand NBS through performance-based zoning regulation. Full article

Rapid peri-urban sprawl is intensifying flood risk by replacing natural landscapes with dense, impervious residential developments. Thailand’s land use regulations require a 5% minimum green space allocation for new housing developments as a measure to promote livability and well-being. Green space also has the potential to sustainably manage stormwater runoff, but for Thailand’s peri-urban development, the question remains whether 5% green space is sufficient to reduce flood risk. As such, this study critically evaluates whether this 5% green space guideline is sufficient for peri-urban runoff and flood management in peri-urban Pathum Thani, particularly given the acceleration of Bangkok’s urban sprawl over the past 30 years. Using a multi-scalar framework, we integrated GIS spatial analysis of 164 gated communities (1995–2025) with site-specific PCSWMM hydrologic modeling to test baseline conditions and Nature-based Solution (NbS) interventions against 5-, 10-, 50-, and 100-year design storms. Findings reveal developers generally adhere to the 5% guideline, thereby addressing policy while maximizing salable land space. PCSWMM simulations show the 5% baseline alone does not adequately manage runoff, with localized residential flooding expected for a 5-year design storm under current baseline conditions. Scenario testing indicates a hybrid grey–green infrastructure approach would optimally manage flooding. Given economic barriers to expanding open space, converting roads to permeable pavements offers a possible optimization strategy. Ultimately, static area-based regulations remain insufficient; policies must transition to performance-based volumetric retention targets to mitigate downstream flooding and foster resilient communities. Full article

Assessing the impacts of large-scale photovoltaic plants on soil properties is critical for sustainable land management in arid regions. This study examined a 50 MWp utility-scale PV facility in Siziwangqi, Inner Mongolia, northern China, a cold semi-arid desert steppe where renewable-energy development overlaps with fragile wind-eroded ecosystems. A spatially resolved sampling design contrasted soils at key micro-positions relative to the panels, namely Front, Under, and Behind, with adjacent natural Controls. By integrating laser diffraction analysis, multifractal modeling, and the EPIC erodibility equation, we evaluated soil particle-size probability redistribution and EPIC-estimated intrinsic erodibility. Compared with the silt-dominated surface soil of the natural steppe, soils within the photovoltaic plant exhibited fine-particle retention and lower information and correlation dimensions (D1 and D2), indicating stronger local clustering and a less even particle-size probability distribution. The EPIC-estimated erodibility factor decreased from 0.452 in the Control to approximately 0.361 in the PV micro-locations. These associations should be interpreted as texture- and SOC-based model estimates rather than direct measurements of wind erosion. Overall, multifractal parameters provide complementary proxy descriptors for detecting PV-induced particle sorting and potential changes in intrinsic soil erodibility, underscoring the need for field validation and adaptive management in dryland PV landscapes. These findings provide physical soil evidence for evaluating the environmental sustainability of dryland PV development and for supporting adaptive land management in solar farms. Full article