Search Results (1,502)

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

Rapid and unplanned urbanization in Dhaka is reshaping land use, intensifying peripheral expansion, and increasing pressure on urban and ecological resources. Understanding these growth dynamics is essential for effective urban growth boundary delineation and sustainable planning, yet integrated assessments of historical and future urban growth remain limited. The current study evaluates spatiotemporal urban expansion from 2010 to 2025, delineates the urban growth boundary using a morphological framework, and simulates future growth for 2030 through a coupled cellular automaton-neural network model. Multi-temporal Landsat imagery (2010, 2015, 2020, and 2025) was classified in Google Earth Engine using supervised Maximum Likelihood Classification. Urban growth patterns were quantified using the urban expansion intensity index (UEII), annual urban expansion rate (AUER), and landscape expansion index (LEI). The urban largest continuous patch index (ULCPI) approach was applied to extract functional urban boundaries. Model performance was validated using the Chi-square (χ²) goodness-of-fit test. Results show a substantial increase in built-up land from 115.85 km² to 171.42 km² between 2010 and 2025, accompanied by a decline of approximately 60 km² in urban green spaces. LEI results demonstrate a transition from compact infilling growth (2010–2015) to dominant edge and outlying expansion (2015–2020), indicating progressive peri-urbanization. The urban largest continuous patch (ULCP) nearly doubled from 78.58 km² to 152.13 km² over the same period, accentuating rapid spatial consolidation. The 2030 projection anticipates continued corridor-oriented expansion, particularly toward the northern and eastern peripheries, with predictive agreement from the CA–ANN model (χ² = 0.03 < 7.8). The study identifies a clear transition from monocentric compactness to polycentric expansion, emphasizing the necessity for enforceable growth containment, transit-oriented development, and ecologically responsive planning strategies to ensure long-term urban sustainability. Full article

Rapid urban development has intensified conflicts between land development and ecological conservation, making spatially explicit land-use planning increasingly important for resource-depleted cities. This study develops a geoinformation-based decision-support framework for Huangshi, China, by integrating multi-scenario land-use modeling, production–living–ecological space analysis, landscape pattern assessment, and SDG 15 diagnostics. Four 2035 policy-oriented scenarios were compared: Business-as-Usual (BAU), Ecological Restoration Priority (ERP), Economic Development Priority (EDP), and Sustainable Development (SD). The results show that ERP delivers the strongest ecological performance, with ecological space reaching 46.47%, forest cover increasing from 35.40% to 36.80%, water area rising to 9.65%, net land degradation declining to −2.04%, and mean habitat quality reaching 0.484. SD provides a more balanced pathway, with ecological space of 44.80%, living space of 8.93%, a land-use stability rate of 96.36%, and a relatively low net degradation rate of 1.33%. BAU and EDP show higher ecological risks. The framework demonstrates how multi-source geospatial data and spatially explicit SDG diagnostics can support adaptive planning in resource-depleted cities. Full article

Rapid urbanization is reshaping land-use patterns and threatening regional ecological security, with different functional zones facing distinct pressures and ecological requirements. Existing studies predominantly apply conventional ecological source-corridor methods to formulate regional ecological network, overlooking the heterogeneity in ecological network and its resilience across functionally heterogeneous zones. To address this gap, we propose an ecological baseline-differentiated threshold method in Wuhan Metropolitan Area, which determines source selection criteria based on the ecological land proportion of each county group, and simulate progressive node removal under probabilistic, importance-based, and protection-priority scenarios to assess network resilience. Compared with the conventional uniform threshold approach, our method retains 23 additional ecological sources in urbanized zones and improves network connectivity from 0.43 to 0.51. The differentiated network sustains resilience above 0.4 until 91% of nodes are removed under the protection-priority scenario, whereas the uniform network collapses at a 66% removal rate under random attacks. We identify that 12.0% of nodes function as structural backbones, and their targeted removal drives resilience below 0.2 at a 12% removal rate, confirming cascading failure risks. Zone-specific strategies are formulated based on the identified vulnerability patterns. These findings demonstrate that incorporating ecological baseline heterogeneity into source selection enhances both structural organization and dynamic robustness, offering a cost-effective pathway for strengthening regional sustainability in functionally heterogeneous landscapes. Full article

Tree-related microhabitats act as key links between forest structure and biodiversity, but these pathways may be altered in urban forests. In Mediterranean urban forests, we found that deadwood-related processes were weaker than hypothesized, while structural diversity remained the primary driver of microhabitat richness. We evaluated whether hierarchical pathways linking structure, diversity, and richness are maintained under urban conditions. A Structural Equation Model was applied to 180 plots across three Italian cities (Florence, Rome, Campobasso), assessing relationships among tree and deadwood volume, diversity, richness, and landscape variables (forest area, patch shape complexity, canopy cover). A consistent bottom-up hierarchy emerged, in which structural heterogeneity was associated with microhabitat richness through diversity-mediated pathways. However, deadwood-related pathways were positive but less consistent than living-tree-related pathways. Landscape context acted mainly as a secondary filter, although canopy cover positively influenced some richness components. Overall, urban forest microhabitat richness depended more on structural heterogeneity than biomass; patterns are consistent with the hypothesis that management, including deadwood removal, may constrain habitat continuity. Maintaining structurally diverse stands, retaining deadwood where compatible with public safety, and integrating microhabitat monitoring into spatial planning are essential to support biodiversity and ecosystem services in urban forests. Full article

Although conventionally quantified as an urban–rural thermal anomaly, urban heat islands are systematic expressions of development choices that shape unequal exposures and health risks across cities. This article develops an integrated urban development-health framework explaining how imperviousness, vegetation deficit, landscape configuration, urban morphology, thermally absorptive materials and nocturnal heat retention connect heat exposure with physical disease, mental well-being and climate-responsive planning. A critical integrative review reported using PRISMA 2020 and PRISMA-ScR principles, organised evidence from urban climate, public health, environmental epidemiology and planning. The synthesis covers the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Local Climate Zones (LCZs), sky-view factor (SVF), height-to-width ratio (H/W), land-surface temperature (LST), Universal Thermal Climate Index (UTCI), Physiological Equivalent Temperature (PET), wet-bulb globe temperature (WBGT) and nocturnal minimum temperature, together with cardiovascular, respiratory, psychiatric, sleep, mortality and well-being outcomes. Six recurrent amplification pathways were identified: imperviousness and low canopy cover; nocturnal heat retention; social vulnerability; blue-green and cool infrastructure; heat–pollution–humidity interaction; and sleep/mental-health disruption. The Urban Heat-Health Development Index (UHHDI) and Urban Heat-Health Amplification Pattern (UHHAP) are proposed as transparent, review-derived tools for urban diagnosis and policy prioritisation. A Spanish/Mediterranean climatic-zone transition analysis illustrates how future climatic severity can be translated into planning-relevant exposure potential. The findings support a shift from simply describing urban heat to diagnosing development-driven heat-health risk, with implications for urban regeneration, thermal justice, public-health adaptation and healthy-city governance. Full article

Urban wetlands and agricultural lands are among the most important socio-ecological systems in urban areas. They support food production, biodiversity conservation, water regulation, climate resilience, and human well-being. However, rapid urbanization negatively affects wetland–agricultural coexistence (WAC) by destroying habitats, fragmenting landscapes, and intensifying land-use conflicts. Our study proposed a Wetland–Agriculture Coexistence Index (WACI) to assess the spatial pattern of WAC in Colombo, Sri Lanka. We considered four components for the WACI framework: wetland condition (WC), agricultural condition (AC), urban pressure (UP), and hydrological connectivity (HC). The WACI was developed using Landsat 8/9, Sentinel-1 Synthetic Aperture Radar (SAR), and Advanced Land Observing Satellite (ALOS) data, along with road network, population, and hydrological network data. Variables used in this study include land surface temperature (LST), Enhanced Vegetation Index (EVI), Modified Soil-Adjusted Vegetation Index (MSAVI), Bare Soil Index (BSI), soil moisture, elevation, slope, population density, distance to roads, hydrological connectivity, and built-up %, which were normalized and integrated into four dimensions using an equal-weighted approach to develop the WACI. The results showed substantial spatial heterogeneity in WAC across Colombo. The average WACI was 0.51, indicating a moderate WAC. This study further identified that favorable environmental conditions, rich hydrological connectivity, and low urban pressure increased coexistence potentials. The spatial pattern of WACI identified priority areas for conservation, restoration, and sustainable urban planning implications in Colombo. Our WACI framework provides a practical and transferable method for assessing WAC in urban areas. The findings of this study support balanced urban wetland–agricultural management, conservation, food security, and long-term sustainability of rapidly urbanizing cities. Full article

Nomadism and the tent tradition constitute foundational pillars of Anatolia’s vernacular building culture, yet the spatial continuity between nomadic dwelling practices and their urban coastal adaptations remains underexplored in the literature. This study examines how nomadic spatial strategies were reproduced in Antalya’s coastal oba settlements, evaluating them as architectural expressions of indigenous material culture and collective building knowledge rather than provisional structures. Employing a qualitative approach, the research synthesizes data from literature reviews, archival analysis, and semi-structured interviews with former residents, utilizing Lefebvre’s Rhythmanalysis as an analytic framework to examine how seasonal cycles, recurring daily rituals, and patterns of collective occupation shaped the spatial logic of these now-vanished settlements. Findings reveal three distinct oba typologies with traceable morphological continuities to the nomadic tent tradition, particularly in semi-open spatial configurations, modular organization, and the flexible adaptation of indigenous materials to coastal conditions. Interpreted through the lens of cultural landscape, the oba emerges as a site where tangible building practice and intangible cultural heritage converge. The study concludes that Antalya’s coastal obas represent a significant yet under documented chapter of vernacular architectural heritage, one whose physical erasure under post-1980 tourism-driven development has rendered its preservation in collective and embodied memory all the more urgent. By transitioning from physical fabric to intangible heritage, these settlements persist as a critical representational field for cultural and social sustainability discourse. Full article

Improving the flood adaptability of urban waterfront spaces is an essential entry point for enhancing regional stormwater regulation capacity, scientifically preventing flood disasters, and stabilizing urban water security. Existing flood adaptability assessments mostly rely on single weighting methods and individual evaluation models, inevitably causing systematic bias and low result robustness. Against this limitation, this study integrates remote sensing intelligent interpretation, spatiotemporal landscape pattern analysis, and multi-criteria decision theory to construct a comprehensive flood adaptability evaluation system under the pressure–state–response (PSR) framework. Innovatively, a game-theoretic combined weighting scheme integrating the entropy weight method, CRITIC method, and standard deviation method is proposed, and three complementary models including TOPSIS, VIKOR, and EDAS are coupled for cross-verification evaluation, which effectively improves the objectivity and robustness of spatial flood adaptability quantification. Taking Anqing City as a typical case, this study adopts Sentinel-2 time-series remote sensing images from 2016 to 2023 and applies an optimized random forest algorithm to automatically classify land cover. Five underlying surface types, including water bodies, vegetation, farmland, built-up areas, and bare land, are accurately extracted with an overall classification accuracy of around 90% for most years. Core landscape metrics such as Shannon’s diversity index and patch density are selected to systematically analyze the spatiotemporal differentiation characteristics of waterfront landscape patterns during the study period. The results indicate the obvious spatial heterogeneity of flood adaptability in Anqing City. Yingjiang District and Yuexi County present high comprehensive flood adaptability, while Wangjiang County and Huaining County show relatively low performance. Urban areas gain strong flood resistance from complete disaster prevention infrastructures and economic resilience; mountainous areas possess natural advantages in flood retention and drainage due to high vegetation coverage and topographic relief; by contrast, plain districts are severely restricted by low-lying terrain and insufficient drainage systems, resulting in prominent flood vulnerability. The proposed method is helpful for providing reliable scientific support for waterfront landscape optimization, zoned flood disaster management, and resilient water space planning in riverine cities. Full article

Urban green-space carbon sinks can contribute to reducing urban carbon emissions and supporting carbon-neutrality goals. This study examined the associations between urban green-space landscape patterns and above-ground carbon storage (AGCS) in Shenyang. The spatial distribution of estimated AGCS was mapped using ArcGIS and remotely sensed imagery. Pearson correlation analysis, geographically weighted regression, and an exploratory data-binning approach were used to evaluate associations between landscape pattern metrics (LPMs) and AGCS and to identify their thresholds. At the study-area scale, AGCS exhibited strong positive correlations with class area (CA) and largest patch index, weak negative correlations with patch density and landscape division index, and a weak positive correlation with Connectivity Index (CONNECT). These relationships varied among the three ring zones. Spatially, CA was positively associated with AGCS throughout the study area, whereas positive local coefficients for CONNECT occurred in 51.8% of the study area. The low- and high-carbon-storage thresholds were 7.26 and 10.79 for CA and 8.33 and 12.08 for CONNECT, respectively. Higher CA and CONNECT values above their low-carbon-storage thresholds were associated with a lower probability of a low-carbon-storage zone. These findings provide context-specific evidence that may inform urban green-space planning in Shenyang and offer a methodological reference for comparable case studies. Full article

Rapid urban-industrial development has intensified surface warming in global cities, including India, posing critical challenges for sustainable urban environments. While advanced AI and remote sensing methods have mapped urban heat patterns, a fundamental thermodynamic understanding of how cities generate, absorb, store, and dissipate heat with the urban land transformation remains underexplored. This study conceptualizes the urban geo-thermodynamics mechanism as a comprehensive framework to quantify urban surface energy exchanges, heat flux dynamics, and thermal responses in the Haldia urban-industrial region (103.84 km²) of eastern India. The analysis employs Landsat-derived impervious surface expansion, land surface temperature (LST), and normalized difference vegetation index (NDVI), NASA POWER radiation fluxes, world settlement footprint 3D structural (2023) and material stock (2024) data, and census-based population records (1991–2021). The integrated mathematical formulations were developed after the remote sensing-GIS-based statistical analysis for the urban energy balance through the Urban Thermodynamic Index (UTI), Urban Heat Retention Efficiency (UHRE), and Urban Cooling Potential (UCP) indices, which were developed from energy balance equations linking net radiation (Q*), anthropogenic flux (${\mathrm{Q}}_{\mathrm{F}}$), sensible and ground heat (${\mathrm{Q}}_{\mathrm{H}}$, ${\mathrm{Q}}_{\mathrm{G}}$), and latent heat flux (${\mathrm{Q}}_{\mathrm{E}}$). The results reveal a 36% increase in UTI and a 28% rise in UHRE between 1991 and 2021, indicating enhanced surface heat accumulation and anthropogenic energy input associated with built-up area and population growth (22.87–53.37 km²) and (1452–2375 person/km²). In contrast, UCP declined by 22%, reflecting reduced evaporative cooling due to vegetation loss, with the regression-based calibration (R² = 0.89; RMSE = 0.74 °C) validating strong correspondence with observed LST. These findings demonstrate a quantifiable link between thermodynamic processes and the transformation of the urban morphological landscape. The proposed mathematical-thermodynamic structure provides a scientific, GIS-based statistical method for urban heat risk assessment, energy-efficient planning, and geo-thermal environmental management, supporting global initiatives toward climate-resilient and sustainable urban development. Full article

From a Historic Urban Landscape (HUL) perspective, varying conservation intensities and statutory boundaries may create “zonal differentiation” within historic districts. However, conventional homogenized renewal strategies frequently overlook this heterogeneity, affecting physical townscapes and human perception. This study analyzes 1714 panoramic street-view images from the Core Protection Zone and Construction Control Zone of Jimei School Village. Eleven objective visual features and six model-predicted perception dimensions were examined, with locally experienced participants providing contextual validation. Integrating K-Means clustering, Random Forest modeling, and SHapley Additive exPlanations (SHAP) feature attribution, the study investigates nonlinear, model-based contribution patterns across the two zones. Results reveal significant but non-binary differences in objective features and predicted perceptions. Street-view typologies show zonal tendencies while also indicating within-zone diversity and cross-zone overlap. Feature attribution shows that color composition, greenery, building interfaces, and vehicle presence are more prominent in the Core Protection Zone, whereas greenery, spatial openness, and road-space organization play stronger roles in the Construction Control Zone. This study establishes an interpretable street-view-based framework for historic-district assessment, providing empirical support for differentiated and human-oriented zonal renewal. Full article

Understanding the spatiotemporal dynamics of land-use and cover change (LUCC) and ecosystem service (ES) responses is essential for assessing ecological functions in regional landscapes. However, conventional LUCC simulations often rely on historical trends and inadequately represent the spatially heterogeneous effects of top-down policy constraints. Taking the Henan section of the Yellow River Basin (HYRB) as a case study, we developed a policy-to-rule framework that translated ecological redlines, urban development boundaries, and restoration requirements into explicit spatial constraints and land-use transition rules in the PLUS model. A policy-constrained High-Quality Development Scenario (HQDS) was established, with the Natural Growth Scenario (NGS) as a reference. Five ESs were assessed using InVEST from 1985 to 2050, and the results were integrated with the Minimum Cumulative Resistance (MCR) model and circuit theory to construct an ecological security pattern (ESP). Historical reconstruction of the 2022 land-use pattern achieved an overall accuracy of 90.18% and a Kappa coefficient of 86.39%. The five ESs remained relatively stable overall: water yield, soil conservation, and the sediment-related indicator increased, whereas habitat quality and carbon storage declined slightly. Ecological source areas expanded from 7140.54 km² in 1985 to 12,039.17 km² under the HQDS in 2050, a 68.6% increase. Compared with the NGS, the HQDS increased source areas by 562.42 km² (4.9%), reduced ecological corridors from 26 to 24, and increased their total length from 1068.89 to 1099.61 km. These differences represent the projected, scenario-conditioned consequences of the specified policy constraints and provide quantitative decision support for future ecological management. Full article

To characterize the spatiotemporal evolution of land use and landscape ecological risk in mountainous tourism cities, this study uses Huangshan City as a representative case. Land use data from 2002 to 2022 are analyzed, and future land use patterns for 2032–2042 are projected using the integrated patch-generating land use simulation (intPLUS) model. Meanwhile, by coupling landscape ecological risk indices with terrain gradient metrics (T1–T5), we identify the spatiotemporal evolution patterns and quantify how terrain constraints shape risk distribution. The results indicate that: (1) From 2002 to 2042, forest land remains dominant and consistently accounts for more than 85% of the area. Nevertheless, strong pressure from future urbanization is expected. Between 2032 and 2042, built-up land is projected to expand sharply from 163.08 km² to 255.46 km², increasing encroachment pressure on the extensive forest matrix. (2) Over the past two decades, landscape ecological risk shows a complex “improve-then-rebound” trajectory. In the future, however, it exhibits distinct phase characteristics: risk is relatively stable and improves from 2022 to 2032, but undergoes a sudden reversal and deterioration from 2032 to 2042. This pattern reflects the intensified risk to ecological security resulting from the concentrated release of construction land quotas during the mid-to-late stage of urbanization. Spatially, risk follows a radiation-like pathway, diffusing outward in concentric patterns, with core towns and tourist scenic areas functioning as the source regions. (3) Terrain gradients impose strong constraints on both land use patterns and ecological risk. Anthropogenic disturbance decreases stepwise as terrain gradient increases. The low-gradient zone (T1) is the primary location for built-up expansion and risk enhancement; the mid-gradient zone (T2) represents a highly sensitive ecotone, marked by pronounced tension between human disturbance and natural recovery. In contrast, the high-gradient zones (T4–T5) preserve exceptionally high forest connectivity due to topographic barriers, thereby serving as a crucial natural ecological barrier. Overall, this study clarifies the spatial conflicts among rapid urbanization, tourism development, and ecological conservation in mountainous urban regions, offering actionable insights for differentiated spatial governance and sustainable development. Full article