Search Results (987)

Regional differences in land use transitions and urban expansion patterns have become increasingly pronounced under rapid urbanization. However, conventional land use and land cover change (LUCC) analyses often rely on independent graphical presentations, limiting systematic cross-regional comparison and the identification of spatial heterogeneity. To address this limitation, this study constructs a comparative land use transition analytical framework integrating LUCC contrastive transition patterns, the landscape expansion index (LEI), and the PLUS model. The framework enables structured identification of transition directions, intensity differentials, and stage-specific characteristics, thereby enhancing the reproducibility and comparability of cross-regional land use analysis. Using Xi’an (inland) and Quanzhou (coastal) as representative cases, this study analyzed their land use changes from 1990 to 2020 based on Intensity Analysis and LUCC contrastive transition patterns and quantified the differences in urban expansion using the urban expansion intensity index and expansion pattern metrics. The results show that the urban expansion of Xi’an and Quanzhou was active during 1990–2020, with crops as the main stable source of urban expansion. This urban expansion mainly took the form of edge-expansion and infilling, with urban development transitioning from disorderly expansion to intensive utilization. Notable regional disparities were observed: Forest conversion to urban land was substantially higher in Quanzhou, reflecting stronger ecological land pressure in coastal areas, whereas grass conversion to crops was more prominent in Xi’an, suggesting agricultural spatial adjustment under food security constraints in inland regions. The PLUS model further demonstrates that urban expansion is jointly influenced by topographic conditions (DEM) and economic growth (GDP), highlighting the coupled effects of natural constraints and development dynamics. This study clarifies the differentiation characteristics and driving forces of coastal and inland urban expansion, providing a scientific basis for differentiated territorial spatial planning, ecological protection, and farmland management in eastern and western regions. It also helps formulate more targeted urban development policies based on regional resource endowments, promoting regional coordination and sustainable urbanization. Full article

Global high-mountain ecosystems are increasingly subjected to intensified anthropogenic disturbances, which facilitate the spread of invasive alien plants and threaten agricultural sustainability and ecological security. Using Laojun Mountain in Yunnan as the study area, this research investigates the relationship between the distribution patterns of invasive plants and land-use changes, based on data from 38 transect surveys conducted in 2023 and 30-m-resolution land-use data spanning 2003–2023. The analysis incorporates a random forest model and a land-use transition matrix. The key findings are as follows: (1) Variable importance analysis revealed elevation as the most critical factor influencing invasion occurrence (mean decrease in Gini index: 8.0), followed by slope, aspect, and land-use type. (2) Cultivated land exhibited the highest probability of invasion, with high-risk areas (>0.8) concentrated in agricultural zones in the central-southern and northeastern regions. (3) From 2003 to 2023, cultivated land increased by a net area of 20.85 km², primarily due to conversion from forests (19.57 km²) and grasslands, while grassland area decreased by 24.70 km². This study concludes that agricultural expansion has intensified habitat fragmentation and anthropogenic disturbances, creating favorable conditions for invasive plant establishment. It is recommended that invasive species monitoring and ecological restoration efforts be strengthened in agroforestry transition zones to enhance landscape resilience against biological invasions. Full article

China’s Cultural Ecological Protection Zones (CEPZs) are a distinctive policy instrument intended to safeguard intangible cultural heritage through the “integrated” protection of cultural practices and their supporting socioecological environments. However, there remains limited robust causal evidence on whether CEPZs generate measurable ecological co-benefits and whether such benefits come with landscape-structure trade-offs. Using a county-level panel covering 454 counties from 2006 to 2023, we evaluate CEPZs’ impacts on ecosystem quality and landscape patterns through a multi-period DID design with a rich set of socio-environmental controls. Ecosystem quality is proxied by a satellite-derived NDVI, NDWI, and NPP, while landscape pattern outcomes are captured by a composite landscape pattern connectivity index (LPCI) derived from multi-metric landscape configuration indicators. We further test mechanisms using mediators constructed from Morphological Spatial Pattern Analysis (MSPA) (core habitat proportion) and built-up land proportion, and examine heterogeneity by local governance capacity and region. The results show that CEPZ designation significantly increases the NDVI (β = 0.002, p < 0.01) but significantly reduces the LPCI (β = −0.004, p < 0.01). The average effects on the NDWI and NPP are statistically insignificant. Mechanism tests reveal two countervailing pathways: CEPZs increase the share of core habitat (β = 0.009, p < 0.01), which is positively associated with the NDVI, while simultaneously expanding built-up land (β = 0.012, p < 0.01), which offsets greening and drives fragmentation. Heterogeneity analyses suggest that ecological gains are amplified where independent CEPZ management agencies exist and are stronger in western/central China. These findings provide causal evidence that biocultural governance can yield “greening” co-benefits but may undermine landscape integrity unless development pressures are spatially regulated and local institutional capacity is strengthened. Full article

Current sustainability discourse promotes sustainable yard practices as a means for residents to contribute to urban environmental health and soil conservation. Social–ecological research suggests that yard practices are shaped by multiscale social drivers, including social contagion, whereby visible expressions of individuality in front yard design are copied by nearby neighbors. This study evaluated residential areas within the Río Piedras Watershed (RPWS) in the San Juan metropolitan area to assess evidence of social contagion in front yard configuration and vegetation structure, and to examine whether these variables were associated with socio-demographic and economic characteristics when spatial effects were considered. A total of 6858 front yards across six highly urbanized sites were analyzed using Google Earth Street View imagery. Housing lot sizes were quantified, and yards were classified into eight landscape configurations based on green and gray cover elements. Woody vegetation structures, including trees, shrubs, and palms, were also quantified to generate estimates of functional diversity and a front yard quality index. Significant differences in yard characteristics were observed among sites. Spatial analyses revealed significant clustering at distances of 65–80 m, particularly for front yard configuration, while clustering of woody vegetation density was weaker. Local clustering patterns and the distribution of outliers varied across sites. Spatial lag models indicated that lot area positively influenced yard configuration and quality, and the density and diversity of woody vegetation. While socio-economic variables were not significant predictors of yard quality, their effects cannot be discarded. Overall, results are consistent with social contagion processes but also highlight neighborhood design as a key driver of clustering, alongside widespread conversion of green to paved front yards, with implications for soil and green infrastructure loss as well as environmental and human health in the RPWS. Full article

Against the backdrop of global warming and the urgent demand for sustainable development, blue–green spaces (BGSs) play a vital role in carbon reduction and sequestration, yet the multi-scale spatial mechanisms by which blue–green space patterns (BGSPs) regulate carbon storage (CS) remain unclear. Taking the Zhengzhou Metropolitan Area as the study area, this research clarifies the BGSP-CS correlations at both class and landscape levels and quantifies their spatial interaction mechanisms, providing scientific support for integrated BGS planning that aligns with sustainable development objectives. Using the InVEST model coupled with regional carbon density correction, the total CS of the area is estimated at 1112.27 × 10⁶ t. Spearman’s correlation analysis shows that at the class level, area–edge and shape complexity indicators (e.g., Landscape Shape Index, LSI: r = −0.427) are negatively correlated with CS, while connectivity indicators exert no significant effect. At the landscape level, Shannon’s Diversity Index (SHDI: r = −0.635) and area–edge indicators inhibit CS, whereas Shannon’s Evenness Index (SHEI: r = 0.602), Largest Patch Index (LPI: r = 0.618) and shape complexity indicators exert positive effects. A comparative analysis of three regression models reveals that the multi-scale geographically weighted regression (MGWR) model outperforms the ordinary least squares (OLS) and geographically weighted regression (GWR) models, with R² values of 0.505 (class level) and 0.484 (landscape level). It effectively captures the “west–strong and east–weak” spatial heterogeneity of BGSP impacts on CS. This study identifies key BGSP indicators regulating CS and their spatial mechanisms, providing scientific support for integrated BGS planning, regional carbon sink enhancement, the achievement of “dual carbon” goals, and the promotion of sustainable development in metropolitan areas. Future research may optimize model parameters through field surveys and explore the coupling mechanism between BGSPs, land surface temperature and CS to better align BGS management with sustainable development agendas. Full article

Sweet potato (Ipomoea batatas L.) has become a relevant crop in global research due to its remarkable resilience to abiotic stress, richness in bioactive compounds, nutritional relevance, and growing importance within sustainability and circular economy frameworks. This study conducted a comprehensive bibliometric analysis of scientific production indexed in Web of Science, Scopus, and PubMed, mapping how research links the crop’s biochemical properties with sustainability-oriented innovation. Literature on bioactive compounds, food waste management, circular economy strategies, and by-product valorization was examined through keyword co-occurrence, authorship networks, citation patterns, and thematic clustering. Results reveal a rapidly expanding research landscape over the past decade, with strong connections between phytochemical composition, health benefits, sustainable cultivation, and industrial applications. Biology, Chemistry, and Food Science emerged as the most interconnected areas. Collaboration networks remain fragmented, and high-income countries achieve disproportionate citation impact, underscoring structural inequalities. Theoretically, this study contributes to understanding how sweet potato research consolidates as a multidisciplinary field aligned with global sustainability goals. Practically, it highlights opportunities to strengthen equitable international collaboration, advance circular economy approaches, and integrate biotechnology with environmental sustainability to support more resilient food systems. Full article

This study aimed to analyze changes in vegetation, built-up areas, and population growth in Lahore city from 1990 to 2023. The data was acquired from Google Earth Engine, and the spectral bands were retrieved from Landsat 5 and Landsat 8. The decadal analysis of the landscape was conducted from 1993 to 2001, 2001 to 2012, and from 2013 to 2023. Further analysis was conducted in ArcGIS version 10.3 to evaluate the Normalized Difference Vegetation Index and the Normalized Difference Built-up Index to assess vegetation and built-up areas, respectively. To analyze the urban population of Lahore, data were obtained from the Global Human Settlement Layer for 1990, 2000, 2010, and 2020. Results revealed that the total vegetated area of Lahore city decreased from 1453.0 km² in 1993–2001 to 788.2 km² in 2013–2023. Moreover, the urban built-up area expanded from 319.6 km² in 1993–2001 to 966.8 km² in 2013–2023. Sub-district-level analysis indicated that Model Town and Raiwind areas of Lahore depicted better vegetation recovery in this decade. The population of Lahore has been increasing steadily, with the 2010s being a particularly rapid period of growth. The projections for 2030 also depict a continuous growth pattern. This study was further developed by integrating multi-decadal averaging coupled with selected-year analysis to distinguish gradual land transformation from relatively accelerated phases of urban expansion of Lahore. Also, by combining NDVI and NDBI values on both Lahore and its tehsil level, the research provides a collective sub-district- and district-level perspective into the spatial heterogeneity of peri-urban transformations. The findings of the study explain how major infrastructural projects shape the urban growth patterns of cities like Lahore and cause a decline in the green areas of fast-growing cities in South Asia. This study further highlights the consequences of unplanned urban expansion in regions where high population growth has compromised green infrastructure and threatened ecological balance. In addition, it supports several Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 15 (Life on Land) by providing spatial evidence of urban expansion of the city and losses of its green spaces. The findings offer empirical insights to support climate-resilient developments. The study also demonstrates the necessity of integrating green infrastructure and providing robust strategies for forthcoming urban planning projects and policy development regarding urban expansion. Full article

Balancing tourism development with ecological integrity remains a central challenge in the management of protected areas. This study proposes a spatial framework that integrates the Outdoor Recreation Suitability Index (ORSI) and the Landscape Ecological Risk Index (ERI) to identify and optimize low-impact recreation corridors within Giant Panda National Park, China. Recreation suitability and ecological risk were modeled using environmental variables and landscape metrics, respectively. The results reveal a clear spatial pattern: high-suitability zones are concentrated in the central and northeastern areas, characterized by gentle terrain and extensive forest cover, while ecological risk is elevated in fragmented, human-disturbed peripheral regions. Although ORSI and ERI exhibit an overall negative spatial correlation, bivariate analysis reveals localized mismatches—areas where high recreation potential coincides with ecological vulnerability—indicating potential conflict zones. These zones are typically located along transitional park boundaries where accessibility intersects with ecological sensitivity. To mitigate such conflicts, a least-cost path analysis was conducted based on a composite resistance surface combining ORSI and inverted ERI values. The resulting corridor network connects 40 core areas while effectively avoiding ecological hotspots. Corridor buffers are predominantly composed of forest and shrubland, suggesting high environmental compatibility, particularly in the Qinling region. By translating spatial trade-offs into practical corridor design, this study provides a replicable approach for harmonizing recreation planning with conservation objectives. The proposed framework offers actionable guidance for evidence-based zoning, visitor flow management, and adaptive tourism development in ecologically sensitive protected landscapes. Full article

The mechanisms by which the regional hydroclimate responds to global climate forcing are complex, particularly in geographically heterogeneous countries like China. Focusing on Hunan Province, this study employs the Standardized Precipitation Index (SPI) derived from long-term precipitation records at 87 meteorological stations to delineate climatic sub-regions with coherent dry–wet variability. Using rotated empirical orthogonal function analysis, we systematically characterize the spatiotemporal patterns of SPI components and quantify their teleconnections with global ocean–atmosphere circulation modes. The analysis of multi-timescale SPI reveals four distinct sub-regions and a pronounced northwest–southeast dipole in long-term trends. Despite an overall reduction in annual drought, the northwestern sub-region experienced intensification. Seasonally, a pattern of spring/autumn drying versus summer/winter wetting emerged. Wavelet analysis identified dominant interannual (2–7 years) and interdecadal (13–71 months) oscillations. These periodicities are significantly teleconnected to large-scale circulation indices (e.g., Southern Oscillation and Pacific Decadal Oscillation), with influences peaking at 16–64-month and 2–5-year scales. Importantly, the primary circulating driver differs by sub-region, revealing a complex teleconnection landscape. The findings delineate region-specific atmospheric pathways, offering insights to bolster drought preparedness and optimize water allocation, thereby enhancing climate resilience in vulnerable monsoon transition zones. Full article

The cultural services of urban cultural landscape ecosystems are easily perceived by visitors, and their quantitative assessment and exploration of influencing factors can provide a scientific basis for the optimization of urban cultural landscapes. Existing studies rarely reveal the spatial distribution of the social values of urban cultural landscape ecosystem cultural services and the influencing factors of this spatial distribution from the visitors’ perspective. To reveal the spatial distribution pattern of the social values of urban cultural landscape ecosystem cultural services from the visitors’ perspective, explore its influencing factors, and verify the applicability of the SolVES model in urban cultural landscapes, this study obtained the overall perception and preferences of visitors towards Cangzhou Garden Expo Park through a questionnaire survey. Combining the questionnaire survey data with geographical data, the SolVES 3.0 model was employed to conduct quantitative assessments and spatial distribution analyses of six social values of the ecosystem: esthetic, biodiversity, historical, recreation, learning, and life-sustaining values. The following conclusions were drawn: (1) The maximum value index of recreation value and esthetic value were highest, and showed significant spatial concentrated characteristics, with hotspots concentrated at the northeast side of the park. (2) Biodiversity value and historical value were prominent near areas rich in plant resources and industrial heritage sites. (3) The distance to roads and slope significantly influenced the assessment of social values; social values showed a significant negative correlation with distance to roads. (4) The Garden Expo Park had strong advantages in ecological restoration and social value supply, but there were still problems such as inconvenient transportation and uneven value distribution. Based on the above results, this study proposed suggestions for enhancing the social values of the ecosystem services in Cangzhou Garden Expo Park, and further provided targeted optimization suggestions for the construction and management of urban cultural landscapes. The SolVES model showed good performance in assessing the social values of the ecosystem services of an urban cultural landscape, with high reliability and promising application prospects. Full article

The construction of high-speed railways (HSRs) is the core engine for promoting the economic integration and spatial structure optimization of the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Changes in land use along HSR corridors are inextricably linked to the efficacy of regional coordinated development and ecological protection initiatives, as well as the realization of regional sustainable development. Nevertheless, past relevant studies exhibit prominent limitations. First, the lack of effective methodologies for the intuitive comparison of multiple research subjects makes it difficult to accurately portray the differential characteristics of land use across various HSR routes. Second, the insufficient comprehensive analysis of the dynamic evolution of landscape patterns along routes, coupled with the absence of intuitive spatial visualization expressions, fails to explicitly reveal the spatiotemporal differentiation of landscape fragmentation, which hinders sustainable land resource utilization and ecological protection. To address these gaps, this study introduces the intensity comparison map and the comprehensive index map of landscape fragmentation and takes six typical HSRs in the GBA to conduct an intuitive comparative analysis of land use changes along multiple routes. Results show that land use evolution along HSRs presents distinct phased characteristics, with construction land acting as the core driving factor. Its proportion increases continuously, while the proportions of cultivated land and water bodies decline dramatically. Significant disparities exist in land use evolution across different HSR routes, which are closely associated with the natural and economic conditions of the traversed regions, reflecting the heterogeneous adaptability between individual routes and regional development dynamics. High landscape fragmentation areas are predominantly distributed in the transition zones between construction land and natural landscapes; fragmentation intensifies during the planning and construction phases and stabilizes or even diminishes along certain routes during the operation phase, with human activities identified as the pivotal influencing factor. This research deepens the understanding of the interaction mechanism between transportation infrastructure and land use changes in the GBA and provides a scientific basis for sustainable HSR construction planning, the rational utilization of land resources, and the coordinated advancement of ecological protection in the GBA and other similar regions worldwide, thus facilitating the sustainable development of high-density urban agglomerations globally. Full article

Rapid urbanization has significantly exacerbated the Urban Heat Island (UHI) effect in high-density megacities, driven by the intensifying competition between built-up morphology and natural cooling infrastructure. Current research, however, often fails to accurately predict land surface temperatures (LST) because traditional models frequently overlook the complex spatial dependencies and neighborhood spillover effects inherent in urban environments. Existing studies often ignore the spatial dependence of heat transfer. This study proposes an explainable machine learning framework incorporating spatial lag variables to capture the thermal spillover from adjacent neighborhood context—such as green space cooling diffusion or built-up heat accumulation—which is frequently treated as noise in traditional models. Taking Shenzhen as a case study, we integrated multi-source data (Landsat 8, building vectors, DEM) and developed an XGBoost regression model (R² = 0.806) augmented with SHAP (Shapley Additive exPlanations) to quantify the contributions of local and contextual features. The results revealed that: (1) Non-linear Thresholds: Vegetation cooling exhibits a saturation effect, with the highest marginal benefit observed in the NDVI range of 0.2–0.4, while building warming effects converge at extremely high densities due to mutual shading; (2) Neighborhood Spillovers: Spatial interaction analysis confirms significant cool island synergy (where clustered green spaces provide amplified cooling) and heat island agglomeration effects—e.g., green spaces surrounded by high ecological backgrounds provide amplified cooling benefits; (3) Spatial Antagonism: A novel Interaction Balance Index (IBI) based on game-theoretic SHAP contributions was constructed to map the source-sink competition patterns, identifying distinct heat-dominated (West) and cool-dominated (East) zones. Unlike traditional area-weighted source-sink landscape metrics, IBI enables a pixel-level additive decomposition of warming and cooling factors, quantifying the net thermal outcome of local morphology and neighborhood spillover. By explicitly encoding spatial context into non-linear modeling, this study provides a more mechanistically robust understanding of urban thermal environments. The identified thresholds and dominant driver maps offer precise, spatially differentiated guidance for urban climate-adaptive planning and ecological restoration. Full article

Urban hydrological risks are endangering vulnerable populations, particularly in densely populated metropolitan areas undergoing rapid land use transformation. This study uses geospatial analysis to identify zones in the Athens metropolitan area that are prone to surface water accumulation and stream flow development during extreme rainfall events. Two spatial indices were developed by integrating digital elevation models, flow accumulation, slope, aspect, the topographic wetness index, and classified road network data: a Surface Water Accumulation Index and a Stream flow Pathway Index. Roads were categorized based on their orientation relative to the direction of the slope, which allowed for an assessment of their influence on hydrological flow. Both indices were classified into five risk levels representing gradients of hydrological vulnerability. The spatial patterns revealed by this analysis show strong correlations with flood-prone areas and natural drainage systems. These insights are essential for guiding urban planning efforts aimed at reducing hydrological hazards, particularly for at-risk groups such as the homeless. This approach offers a valuable tool for promoting sustainable, socially inclusive landscape management. Full article

The spread of Xylella fastidiosa, a xylem-limited bacterial pathogen, has caused widespread mortality among olive trees in Apulian region, Italy in more than a decade, and represents a significant threat to Mediterranean agroecosystems. To encourage evidence-based containment strategies, we developed a stochastic, spatiotemporal simulation model that represents pathogen transmission at the individual-tree level. This work integrates high-resolution georeferenced olive-tree data and implicitly incorporates vector population dynamics through a tree-specific vulnerability index, which considers local host density and landscape connectivity. Vector dispersal is approximated using a radial transmission kernel, which preserves host–vector spatial interactions while avoiding the explicit modeling of insect trajectories. The system’s spatial structure is additionally formulated as a proximity graph, facilitating network-based analysis of spread pathways. A series of Monte Carlo simulation experiments is employed for calibration against the observed epidemic footprint, while validation utilizes independent infection records and global sensitivity analysis of key parameters. The findings indicate that the model effectively replicates realistic propagation patterns, and its calibrated parameters are consistent with out-of-sample data. This makes it an appropriate exploratory tool for scenario testing, assessing the potential impact of intervention strategies, and offering risk-based decision support for handling Xylella fastidiosa outbreaks. Subsequently, graph centrality metrics are used to identify epidemiologically critical trees that function as transmission bridges, thus representing priority targets for surveillance or removal efforts. Thus, multiple tests have been conducted using betweenness and closeness centrality, while comparing both methods leads to effective node-tree removal decisions. Full article

Under the intensifying pressures of climate change and human activities, the characteristics of land-use types and landscape patterns are widely recognized to exert significant influences on river water quality. Nevertheless, in dry-hot valley basins characterized by fragile ecological conditions and frequent geological hazards, the responses of river water quality to changes in landscape characteristics under the combined effects of natural disasters and anthropogenic disturbances remain poorly understood. In the present study, the Xiaojiang River Basin, a typical dry-hot valley basin subjected to intensive anthropogenic activities and frequent geological hazards, was selected. Through the integration of landscape pattern indices analysis and redundancy analysis, the spatial and temporal variations in river water quality in the Xiaojiang River Basin were quantified, and the effects of land-use types and landscape patterns on river water quality were systematically elucidated. Results showed that (1) the key water quality indexes such as total phosphorus, total nitrogen, ammonia nitrogen and COD in the Xiaojiang River Basin were shown as flood season > non-flood season; for example, the average TN increased from 1.37 mg/L (non-flood season) to 2.90 mg/L (flood season), and the average COD increased from 3.24 mg/L to 15.98 mg/L. In contrast, DO decreased from 8.07 mg/L (non-flood season) to 6.72 mg/L (flood season), and conductivity decreased from 561.4 µs/cm to 480.90 µs/cm. (2) Spatially, these key water quality indicators were shown as hazard-prone area > residential area > cultivated land area. (3) The larger the area of the debris flow trace areas, the greater the fluxes of nitrogen and phosphorus in the tributaries and the main stream in the flood season, and the worse the water quality of the river; after heavy rainfall, the fluxes of key water quality indicators generally showed a geometric multiple increase, with average growth rates of 1.95 (TP), 2.41 (TN), 2.34 (NH₃-N) and 4.74 (COD), respectively. (4) The ability of landscape patterns in flood season to explain the change in water quality is better than that in non-flood season. On different spatial scales, in the down-stream hazard-prone areas, upstream residential areas and cultivated land areas, the changes in river water quality indicators were mainly affected by landscape pattern indicators such as PD_hazard-influenced areas, IJI_residential areas and DIV_cultivated land. Our results can provide scientific guidance for the soil and water conservation practice, ecological restoration, and land-use management in the dry-hot valley of Southwest China and the water environment protection of the Baihetan Reservoir area. Full article