Search Results (3,246)

In an era prioritizing high-quality development and ecological civilization, optimal land resource allocation is vital for overcoming resource constraints and fostering new quality productive forces, with green technology innovation (GTI) serving as a key driver. Using data from 41 Yangtze River Delta cities (2003–2022), this study measures urban land resource misallocation (ULM) via the factor relative distortion coefficient and employs fixed effect, mediating effect, and spatial Durbin models to explore GTI’s impact and spatial spillovers on ULM. Results show a fluctuating yet rising ULM trend with significant spatial disparities. Land allocation efficiency is higher in central and southeastern coastal cities, while western and northern areas exhibit high-misallocation agglomeration. GTI significantly reduces ULM, particularly in non-resource-based cities, mainly through industrial structure optimization and agglomeration. Spatial spillover analysis reveals that GTI not only improves local land allocation but also positively influences neighboring regions via technology spillovers and industrial synergy. These findings suggest that incentive policies should strengthen GTI to enhance region-wide land utilization efficiency. Full article

The East Kazakhstan Region is characterized by heterogeneous mountain, steppe, agricultural, and urban–industrial landscapes. However, spatially integrated assessments of land-cover conditions, agricultural dynamics, settlement expansion, and atmospheric trace-gas patterns remain limited. This study combines open multi-source Earth observation datasets and products to assess regional land cover, cropland dynamics from 2003 to 2019, built-up-area expansion from 1985 to 2025, and tropospheric nitrogen dioxide (NO₂) column density from 2019 to 2024. The land-cover classification was based on Sentinel-2 imagery and ancillary geospatial datasets. Its random forest component achieved an overall accuracy of 90.17%, a Cohen’s kappa coefficient of 0.892, and a macro-averaged F1 score of 0.888. Grassland was the largest mapped land-cover class, covering 39.3% of the study region, followed by dense vegetation (16.2%), rock (14.9%), and sparse vegetation (10.6%). Mapped cropland extent increased from 4771.6 km² in 2003 to 5043.9 km² in 2019, representing a net increase of 272.3 km² (5.7%), although a minor decrease occurred after 2015. The harmonized built-up area time series showed expansion within all nine major settlements, with the largest absolute increase observed in Öskemen (Ust-Kamenogorsk). Newly detected built-up pixels during 2000–2024 were mostly associated with transition from grassland and dense shrubs. Annual Sentinel-5P observations showed recurring elevated tropospheric NO₂ column densities in northwestern East Kazakhstan, particularly around Öskemen. Over the built-up footprint, the area-weighted mean increased from 24.1 µmol m⁻² in 2019 to 29.2 µmol m⁻² in 2024. The integrated framework provides a spatially consistent regional baseline while identifying descriptive patterns that require further process-based investigation in future. Full article

This study analyzes land use dynamics in Fălticeni Municipality over four decades (1985–2025), examining the influence of major political, socio-economic, and demographic changes on urban development. The transition from a centrally planned economy to a market economy, Romania’s democratic transformation and European integration, together with migration and population dynamics, have driven largely unregulated urban expansion at the expense of agricultural land and natural landscapes. Recent urban growth has also extended into areas with varying geomorphological vulnerability, increasing exposure to landslide hazards, while the city continues to face challenges related to abandoned industrial areas and insufficient forested land and green spaces. By integrating land use change analysis with physical vulnerability indicators, this study highlights the need for risk-informed and sustainable urban planning in medium-sized cities. It proposes a planning framework based on ecological zoning, controlled urban expansion on suitable terrain, brownfield redevelopment, the establishment of peri-urban forests, and the implementation of essential infrastructure supported by comprehensive geomorphological susceptibility assessments. The proposed approach provides practical guidance for enhancing urban resilience and can be replicated in other cities facing similar environmental and development challenges. Full article

This study investigates the spatiotemporal distribution of heavy metals in urban soils of Thessaloniki, Greece, over a four-year monitoring period (2021–2024). A total of 664 soil samples were collected across diverse land-use types during both wet (winter) and dry (summer) seasons. Soil physicochemical properties were analyzed alongside cadmium (Cd), copper (Cu), lead (Pb), and zinc (Zn) concentrations. The results reveal distinct, element-specific accumulation dynamics driven by continuous anthropogenic inputs. Statistical and geospatial analyses confirm that Cd exhibits a highly significant, progressive accumulation and spatial expansion toward residential areas. In contrast, Cu and Pb demonstrate a gradual, chronic enrichment, eventually reaching a saturation point where winter precipitation is insufficient to offset summer deposition. Zn presents as a severe but temporally stable contamination burden, anchored to the northwestern industrial–port sector. Furthermore, the alkaline properties of the local urban soils were found to act as an effective sink, immobilizing contaminants and preventing downward leaching. The Geo-accumulation Index (I_geo) confirms a progressive decline in soil quality driven primarily by cadmium, while the other trace elements exhibit persistent, stable profiles. Overall, this study establishes a vital geochemical baseline of total heavy metal loading in Mediterranean urban soils, emphasizing the need for targeted emission controls and future mobile-fraction assessments to guide sustainable urban management. Full article

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

Nitrogen dioxide (NO₂) drives ozone and secondary aerosol formation and harms human health. Chongqing, a mountainous megacity of 32 million people, lacks a fine-scale satellite assessment of its NO₂ evolution. We analyzed tropospheric NO₂ vertical column density (VCD) over Chongqing for 2019–2024. The analysis used Sentinel-5P TROPOMI observations. We computed monthly, seasonal, and annual composites at 5.5 km resolution. Trends were quantified with the Theil–Sen slope and, at the pixel level, the Seasonal Mann–Kendall (SMK) test applied to the full 72-month series. A MODIS land-cover mask separated urban built-up from non-urban pixels. NO₂ concentrated in the central districts and along the Yangtze valley. The core exceeded the mountainous counties by a factor of 3 to 4. TROPOMI resolved the Wanzhou and Yongchuan–Jiangjin hotspots as separate features. The record was divided into three phases. The 2020 lockdown produced the minimum, 31% below the prior February. Rebound emissions produced the 2021 maximum of 5.6 × 10¹⁵ molecules cm⁻² under near-normal dispersion conditions, with ERA5 (the European Centre of Medium-range Weather Forecasts Reanalysis v.5) showing the January 2021 boundary layer 4.3% deeper than its climatological norm. Thereafter the regional mean stabilized: the area-weighted SMK slope was +0.042 × 10¹⁵ molecules cm⁻² yr⁻¹ and not significant (p = 0.14), because emission controls in the core and rising county emissions canceled in the average. Trends diverged sharply in space. The nine core districts declined (median urban Sen slope −0.11 × 10¹⁵ molecules cm⁻² yr⁻¹), whereas 41% of peripheral pixels rose significantly (p < 0.05). The urban-to-rural ratio narrowed from 3.0 in 2019 to 2.3 in 2024 (annual means). This convergence was robust to the built-up threshold (30–50%). Industrial relocation and county urbanization explain the peripheral rise. The results support extending vehicle and industrial emission standards from the core to the receiving counties. Full article

The Artificial Intelligence Pilot Zone Policy is an important strategic initiative for building artificial intelligence (AI) innovation hubs. It provides new opportunities to enhance manufacturing firm resilience and promote the sustainable development of the manufacturing sector. The creation of the National New-Generation Artificial Intelligence Innovation and Development Pilot Zones (AI Pilot Zones) is viewed in this study as a quasi-natural experiment. Using data from Chinese A-share-listed manufacturing firms from 2015 to 2023, we employ a staggered DID model to evaluate the impact of the policy on manufacturing firm resilience. We find that the AI Pilot Zone policy increases manufacturing firm resilience by an average of 0.0282 units. The analysis of potential mechanisms shows that the policy significantly promotes digital talent agglomeration, stimulates urban innovation vitality, and improves firm-level supply chain efficiency. These findings are consistent with the theoretical expectations and provide supportive evidence that these factors may constitute potential mechanisms associated with the policy’s effect on manufacturing firm resilience. The heterogeneity analysis reveals a pronounced “weakness-compensating” effect. At the regional level, the resilience-enhancing effect is stronger for manufacturing firms located in areas with relatively weak digital infrastructure. At the industry level, the effect is more pronounced among firms in low-technology manufacturing industries. At the firm level, the effect is stronger for firms with lower levels of human capital, weaker innovation capacity, and lagging digital transformation. Overall, this study provides micro-level evidence on the resilience effects of the AI Pilot Zone policy and offers policy implications for integrating AI more effectively with the real economy. Full article

Environmental noise is a major environmental and public health concern in rapidly urbanizing cities, yet integrated studies combining field measurements, GIS-based spatial analysis, and predictive modelling remain limited in Central Asia. This study assessed the spatial distribution of urban noise pollution in Samarkand (Uzbekistan) and explored its statistical association with selected public health indicators, forecasting future trends. Measurements were conducted at 50 georeferenced sites covering more than 300 streets. The measured data were processed and mapped using ArcGIS 10.5 (Esri, Redlands, CA, USA) to produce the spatial distribution of environmental noise across the study area. Official data on registered vehicles, industrial enterprises, and disease incidence (2014–2024) were analysed using Pearson correlation, Autoregressive Integrated Moving Average (ARIMA), and its extension incorporating exogenous variables (ARIMAX) models. Results revealed pronounced spatial heterogeneity in noise levels, highest along transport corridors and industrial zones. Industrial enterprises showed the strongest correlations with disease incidence; vehicle registrations were excluded from final models owing to collinearity with industrial activity. ARIMA projected continued industrial growth through 2030, while ARIMAX models identified significant associations between industrial activity and diseases of the ear and mastoid process and of the nervous system (MAPE 28.55% and 19.78%). As an ecological, exploratory study using infrastructural proxies rather than measured noise exposure, findings should be interpreted as associations rather than causation. The framework offers a transferable approach for environmental risk assessment and sustainable urban planning. Full article

Urban shrinkage in resource-based cities manifests not only as population decline but also as spatial mismatches between current human activities and inherited urban systems. Existing studies have mainly focused on single dimensions such as service accessibility or land-use efficiency, with limited attention to the multidimensional incompatibility between human activities, service systems, built environment, and industrial risks. This study develops a human activity-centered spatial mismatch framework to examine the spatial consistency between human activities and urban systems in shrinking resource-based cities. Taking the central urban area of Daqing as a case study, this study integrates multi-source urban big data across four spatial dimensions—human activity, public service provision, built environment, and industrial risk exposure—and identifies three types of spatial mismatch: service supply–demand mismatch, built environment mismatch, and industrial risk exposure conflict. The results show that human activities in central Daqing exhibit a polycentric pattern, while their spatial distribution is not fully consistent with existing urban systems. Specifically, service accessibility mismatch, built environment underutilization, and human activity–industrial risk overlap coexist across different areas, reflecting asynchronous adjustment between human activities and inherited urban structures. This study provides a human activity-centered framework for diagnosing multidimensional spatial conflicts in shrinking resource-based cities and supports a transition from expansion-oriented planning toward differentiated adaptive spatial governance. Full article

River ecosystems play a key role in both natural and urbanized environments, acting as essential links in ecological systems. However, they are increasingly exposed to the synergistic effects of anthropogenic pressure and hydrological instability. This study aims to identify and assess changes in land use and their impact on the phytosociological structure and functioning of ash-alder (Fraxino-Alnetum) patches in floodplains. Based on cartographic analyses (1941, 1961, 2025) and detailed geobotanical surveys (2024–2025) conducted at six representative sites, the spatio-temporal dynamics of land use and vegetation habitat conditions were evaluated using ecological indicator values. The results indicate a substantial landscape transformation: a transition from areas dominated by agricultural and forest ecosystems to zones heavily altered by urban expansion, transport infrastructure, and industrialization. Phytosociological analyses show that while species richness remains relatively stable, floristic composition is changing due to hornbeam succession and the emergence of mesophilous species. The presence of non-native species indicates ongoing anthropization in plant patches. Furthermore, hydromorphological modifications, including bank reinforcement and channel deepening in the vicinity of sports and railway infrastructure, have hindered natural river dynamics and accelerated floodplain drainage. The observed changes indicate that ash-alder forests in the Biała Przemsza valley are in a transitional phase between riparian and oak-hornbeam communities, with a clear oak-hornbeam transformation evident in many areas, driven by changes in water relations. This study highlights the urgent need to implement integrated restoration strategies that account for both hydrological catchment recovery and the mitigation of urban pressure to ensure the long-term resilience of riparian ecosystems. Full article

Vertical farming (VF) offers a smart way to grow crops in stacked layers inside controlled indoor environments. By doing so, it uses far less land and water than traditional open-field agriculture, making it a promising solution for cities with limited space and resources. In recent years, artificial intelligence (AI), machine learning (ML), and Internet of Things (IoT) technologies have begun to transform vertical farming. These tools are moving the industry away from rigid, rule-based systems toward more flexible, data-driven operations that can adapt in real time. This paper presents a systematic review of 208 peer-reviewed studies from 2015 to 2025. It explores how AI, ML, and IoT are applied across the VF ecosystem, focusing on key areas such as computer vision for disease detection, crop growth and yield prediction, smart climate control, and precision nutrient and irrigation management. This review examines the performance of different algorithms, including Convolutional Neural Networks (CNNs), Random Forest, XGBoost, and LSTMs across hydroponic, aeroponic, and aquaponic systems. The review also covers IoT setups with multi-sensor networks, edge-cloud computing, and automated control systems. Commercial farms have shown real gains in resource efficiency and shorter supply chains. However, challenges remain: high energy use (especially from LED lighting, which makes up 40–60% of costs), expensive setup, scattered datasets, and limited real-world testing. Many high-accuracy claims (>95%) come from lab conditions and need better validation in actual farms. Overall, AI-powered vertical farming has strong potential to support resilient urban food systems. Future work should focus on lightweight edge AI models, improved data standards, explainable AI, and robust life cycle assessments to ensure the benefits outweigh the environmental and economic costs. Full article

China’s resource-based cities are undergoing a dual transition in which industrial restructuring reshapes the economic foundations of urban development, while urban functional renewal, in turn, conditions the capacity and trajectory of industrial transformation. Based on panel data for 102 resource-based cities from 2013 to 2023, this study constructs a dual-system framework of urban functional upgrading and industrial transformation. The entropy method, coupling coordination degree model, spatial autocorrelation analysis, and spatial Durbin model are used to measure synergistic evolution, identify spatiotemporal patterns, and examine driving factors and spatial spillovers. The results show that both systems improved during the study period, but their evolutionary rhythms were not fully synchronized. The level of synergistic evolution increased steadily, although most cities remained at a relatively low coordination stage, with higher values in central areas and lower values in peripheral areas. Significant spatial dependence is observed for urban functional upgrading, industrial transformation, and their synergistic evolution. The spatial econometric results indicate that environmental-regulation attention, population density, human capital, digital infrastructure, and social consumption capacity play differentiated roles, with social consumption capacity showing the most stable positive association. Robustness tests confirm the reliability of the main findings. This study provides empirical evidence for differentiated governance and coordinated transformation in resource-based cities. Full article

Addressing the issue of ecological vulnerability and against the backdrop of urban expansion in arid regions, this study constructs a composite urban resilience capacity index (CURCI) for the urban agglomeration on the northern slopes of the Tianshan Mountains and examines its space-time evolution together with the relative contribution of key indicators. The evaluation system was constructed from economic, social, ecological, and infrastructure dimensions. The CRITIC-entropy combined weighting method, TFPW-MK method, standard deviation ellipse, and XGBoost-SHAP model were used to analyze urban resilience capacity from 2005 to 2022. Results show that, temporally, CURCI showed a sustained overall increase. Urumqi City and Karamay City grew relatively fast as dual core cities, while peripheral and county-level cities improved gradually. Spatially, resilience was higher in the north and west and lower in the south and east. High-value areas expanded, low-value areas gradually disappeared, and the resilience centroid point remained near the boundary between Urumqi City and Changji City, with a northwest–southeast orientation. In terms of factor contributions, economic factors contributed most, followed by social and ecological factors. Based on contribution differences, cities were classified into industrial-advantage, ecological-advantage, natural-constraint, and population-pressure types. These findings provide a reference for resilience assessment and differentiated governance in arid-region urban agglomerations. Full article

The wildland–urban interface (WUI) refers to areas where forests with little human influence and other vegetation types intersect with human development. Ecosystem management in the WUI presents special challenges. Human dwellings and other infrastructure can constrain management options, such as timber harvesting, prescribed burning, and managing wildlife. Humans can also negatively affect ecosystem functioning through the introduction of invasive plant and animal species, wildfire ignition, habitat fragmentation, and attracting nuisance wildlife species. Although there are WUIs throughout the world, this review will focus mostly on the eastern United States, where a high population density and maturing forests highlight exceptional challenges to forest management. Land ownership in the WUI in this region is dominated by non-industrial private forestlands with diverse ownership objectives and is often distributed in relatively small parcels, creating difficulties for coordinated forest management. Landowners and loggers often plan timber harvests without input from forest managers. On the frontlines of WUI management are extension agents, state and local agencies, non-government organizations, and consulting foresters. Public education, cost-share agreements, and local government engagement are needed to conserve and manage forests in the WUI. Full article

Habitat production in informal settlements and vulnerable urban areas faces critical challenges regarding habitability and lack of infrastructure. This article evaluates a prototype for progressive temporary housing based on a modular metal scaffolding structure, conceived as an autonomous housing response unit in the district of Chilca-Huancayo, Peru. Unlike conventional solutions, the proposal integrates metabolic independence systems through photovoltaic generation and rainwater harvesting to guarantee functional autonomy from public utility networks. Adopting a mixed-method, experimental-applied approach, the research articulates technical simulations, full-scale structural load tests, and a social perception assessment. The results demonstrate the technical feasibility of the model: the energy system covers the entirety of basic demand, and the structural component exhibits ductile behavior under seismic demands, guaranteeing stability without brittle failures. Furthermore, the social dimension reveals high acceptability among residents in emergency scenarios. The study concludes that the use of reusable industrial systems enables a resilient and rapidly deployable architecture. It is argued that this model constitutes a viable alternative for risk management and the mitigation of the housing deficit in the context of urban exclusion, highlighting its potential for territorial replicability as a response to the social production of habitat on the periphery. Full article