Search Results (1,858)

Standardized urban indicators are essential for assessing smart and sustainable cities, yet their application in developing countries remains limited. This study addresses the critical gap regarding the availability of ISO 3712x standard indicators among local governments in Brazil—a nation marked by territorial and socioeconomic heterogeneity. Urban indicators based on open government data across all 5570 Brazilian municipalities were analyzed in this study using the ISO 37120, 37122, 37123, and 37125 standards. A synthetic smart and sustainable cities index was drawn up, supported by Factor Analysis and Principal Component Analysis (PCA). Considering the Local Indicator of Spatial Association (LISA), clustering patterns of municipal sustainability and smartness performance were identified: LISA analysis identified pronounced spatial clusters, with high-performance municipalities concentrated in the Southeast and South-Central regions, while low-performance clusters spread across the North and Northeast of Brazil. Despite the diversity of characteristics among Brazilian cities, 22 of the 302 ISO 3712x indicators (7.3%) could be collected with complete national data for all 5570 Brazilian municipalities; data for 59 indicators were available from open sources, though with gaps. Since the ISO 3712x standards offer a voluntary portfolio of indicators rather than a mandatory set, partial data coverage does not make the framework inapplicable; rather, they delimit the scope of the synthetic index presented here and highlight where open-data infrastructure must be strengthened. Municipal smartness and sustainability result from the multidimensional integration of technological innovation, human capital, social protection, and responsible environmental management. Despite the availability of ISO indicators, observations based on the authors’ institutional experience as members of ABNT/CEE-268—Brazilian mirror committee of ISO/TC 268—“Sustainable cities and communities”—reveal that local governments face challenges in systematically integrating them into strategic planning, presenting a significant opportunity for capacity building and evidence-based governance. In addition to the innovative aspect of this research—which involves using ISO-standardized indicators and collecting numerical data from official open data sources—this article presents a comprehensive index calculation for sustainable and smart cities based on these indicators, followed by the identification of its spatial clusters. Full article

Amid global urban transition from sprawling expansion to stock-oriented regeneration, exploring the spatiotemporal heterogeneity and mechanisms of urban spatial vitality in old urban areas is crucial for advancing sustainable urban renewal and enhancing human well-being. This study builds a built environment index system, taking the old urban areas of Wuwei City, China, as a case study, and employs the MGWR model to analyze spatial vitality and its drivers. Results show: (1) Diverse functional elements exhibit significant spatiotemporal variations, with basic living facilities having stable impacts, while cultural and catering facilities show morning local agglomeration and nighttime region-wide driving effects, respectively. (2) Regarding accessibility, the road network is a key spatial factor. It shows a positive statistical association with regional vitality during the day, but may correlate with traffic and environmental stress at night. This indicates a potential trade-off between commercial activity and residential comfort across different time periods. (3) Spatial quality elements show strong spatial stability. Specifically, floor area ratio and open space ratio exhibit positive statistical associations with vitality, while building density and height tend to show negative correlations. This may reflect structural bottlenecks imposed by high-density development on sustainable living spaces. (4) Strategies like micro-functional layouts, day-night differentiated traffic networks, and spatial chassis optimization are proposed to provide quantitative evidence for sustainable stock-oriented regeneration, balancing heritage conservation with modern urban vitality. Full article

Against the background of the global green transition, digitalization has become an important driver of energy-efficiency improvement and carbon mitigation, making its overall environmental effects worthy of further investigation. This study constructs a pollution and carbon mitigation pressure (PCMP) index covering emission load, governance support, and ecological carrying capacity to examine the effect of the digital economy on PCMP, its transmission mechanism, boundary conditions, and regional heterogeneity. Using panel data for 30 Chinese provinces from 2013 to 2024, we apply a two-way fixed-effects model, mechanism analysis, a moderation model, instrumental-variable estimation, and a spatial Durbin model. The results show that digital-economy development significantly reduces PCMP, and this conclusion remains stable across multiple robustness checks. The digital economy alleviates PCMP by promoting industrial structure upgrading, while urbanization significantly strengthens this effect. The effect is more pronounced in Northern China, with a statistically significant north–south difference. Spatial analysis further shows that higher digital-economy development in neighboring regions is significantly associated with lower local PCMP. These findings extend research on the environmental effects of the digital economy by showing how industrial upgrading, urban conditions, and cross-regional linkages shape its contribution to pollution control, low-carbon transition, and regional sustainable development, with implications for the broader goals of the 2030 Agenda. Given the limitations of provincial data and the identification strategy, future research could use city-level data to further examine the underlying mechanisms and causal effects. Full article

Urban vitality (UV) is the core index to measure the quality and sustainability of urban development. Accurately analyzing the complex association mechanism between UV and built environment (BE) is critical to urban planning practice. Focusing on the main urban area of Chengdu, this study integrates eight categories of multi-source data, including nighttime light data, WorldPop population distribution data, street view images, and POI data, to construct a four-dimensional UV evaluation system and identify 26 BE factors. Firstly, the UV level is quantified by objective weighting methods. Secondly, an XGBoost model combined with a SHAP framework is adopted to investigate the nonlinear association between UV and BE factors. Finally, a spatial autocorrelation model, SHAP spatial visualization and clustering methods are employed to reveal the spatial pattern of UV and the spatial heterogeneity of the association between UV and BE. The results indicate: (1) Various elements of the BE show a significant nonlinear association and threshold effect for UV. Catering services and public transit services are the core factors for UV prediction, with their combined contribution accounting for 37.47%. (2) UV shows obvious spatial differentiation and agglomeration characteristics. It presents a spatial pattern with a gradual decline from the core to the periphery. (3) The association between UV and BE presents spatial heterogeneity, and the predictive contribution logic differs distinctly across different concentric rings. The study conclusions provide a scientific basis for UV improvement and BE optimization in Chengdu. Full article

Coastal areas are complex territorial systems where natural processes and anthropogenic pressures interact, generating vulnerable yet culturally significant landscapes. While remaining attractive for tourism and urban development, they are among the areas most exposed to the impacts of climate change, requires resilient and adaptive planning approaches. This study assesses vegetation-related environmental changes associated with the regeneration of the Portici Maritime Park, Italy, through a comparison of Sentinel-2 Normalized Difference Vegetation Index (NDVI) data acquired before and after the intervention. Mean NDVI decreased from approximately 0.245 in 2018 to 0.167 in 2026, indicating a reduction in vegetation-related conditions associated with the conversion of previously vegetated or partially vegetated surfaces into paved areas. Based on this empirical evidence and on the environmental characteristics of the site, the study proposes the integration of Nature-Based Solutions (NBS), including permeable surfaces, Sustainable Urban Drainage Systems (SuDS), multifunctional Mediterranean and halophytic green strips, and ecological nourishment. These measures are framed within the proposed Waterfront 4.0 concept, which integrates ecological regeneration, digital environmental monitoring, participatory governance, and adaptive management. By linking ex-post remote-sensing assessment with NBS-oriented planning, the study provides a conceptual and case-study-based approach for improving the climate resilience and ecological performance of highly urbanized Mediterranean waterfronts. Full article

Population ageing challenges the social sustainability of high-density cities, where equitable eldercare access underpins SDG 3, SDG 10 and SDG 11. In China, rapid expansion of community-based eldercare facilities (CEFs) under the “90-7-3” framework has produced a tripartite system of government, operating enterprises and older adult users whose spatial priorities conflict, threatening both distributive equity and long-term operational viability. Existing single-dimensional evaluations inadequately capture this complexity. This study develops an integrated four-dimensional spatial evaluation framework—supply–demand accessibility, spatial equity, functional diversity and market competition—applying the Gaussian two-step floating catchment area method, isochrone-based service-area analysis and a preference-weighted Shannon index to 697 CEFs across 130 sub-districts in Beijing’s central urban area. Results reveal a pronounced core–periphery divide. For service-type CEFs, 90.17% of communities (87.95% of older adults) lie within a 15-min walking catchment, yet service-area overlap reaches 199.32%, indicating redundant resource deployment and intense localised competition in core districts. For residential-type CEFs, only 53.91% of communities are within walkable reach and total coverage drops to 15.84%, exposing care blind spots and spatial inequity in outer districts. Functional diversity, by contrast, is evenly distributed and micro-environmentally shaped. The framework offers replicable diagnostics for sustainable ageing-in-place provision in rapidly ageing high-density cities. Full article

Beautiful City construction is a core initiative to realize the Beautiful China vision and advance China’s progress toward the Sustainable Development Goals (SDGs). This study develops a unified evaluation framework aligned with official Chinese assessment guidelines and global sustainability objectives. Based on a 2015–2022 dataset of 126 prefecture-level cities in the Yangtze River Economic Belt (YREB), we adopt Dagum’s Gini coefficient decomposition, kernel density estimation (KDE), and Moran’s I to investigate the spatiotemporal characteristics of beautiful city construction. The results indicate that the regional Beautiful City Construction Index (BI) increased steadily at both the regional and subregional levels, with all sample cities achieving continuous improvement. A consistent development gradient of lower reach > middle reach > upper reach was identified, with gradually narrowing inter-regional gaps. Importantly, the primary source of regional disparity shifted from inter-subregional differences to intra-subregional differences around 2021. Statistically significant positive spatial clustering was observed, with high-value clusters concentrated in downstream areas and low-value clusters in upstream areas, while the overall clustering effect gradually weakened. This study provides empirical evidence for targeted urban governance and regional coordinated development, offering a typical Chinese practice for global SDG research. Full article

Despite the rising interest in examining factors associated with body mass index (BMI), little longitudinal evidence can be found regarding its associations with the built environment (BE) and commute, which are closely related to sustainable urban development. Employing two rounds of nationwide survey data in China, this research assesses the links between BE, commute, and BMI in both cross-sectional and longitudinal ways. The findings indicate that non-motorized commute duration is negatively associated with BMI in both analyses. Switching from non-motorized to motorized modes is positively associated with BMI change, whereas switching in the opposite direction is negatively associated with BMI change. Among BE factors, increases in density, diversity, and green coverage are negatively associated with BMI change. Additionally, the research highlights the role of urbanization and suggests a nonlinear association with BMI that is consistent with an inverted-U pattern. The findings highlight the potential relevance of non-motorized commuting to overweight prevention and sustainable mobility. This research provides implications for integrating transport planning, public health, and sustainable urban development. Full article

Wildland–urban interfaces (WUIs) are critical zones for wildfire prevention in Mediterranean and semi-arid landscapes, particularly where human settlements interact with continuous combustible vegetation. In Algeria, operational tools for delineating WUI configurations and spatially prioritizing preventive actions remain limited. This study develops a GIS-based structural wildfire-risk prioritization framework for the Djebel El Ouahch massif (Constantine, northeastern Algeria) by combining WUIMAP II settlement typologies with an Aggregation Index (AI) describing the horizontal continuity of arboreal and shrub vegetation derived from Sentinel−2 data. Built-up structures were classified as isolated housing, dispersed housing, main urbanized areas, or peripheral zones and combined with three AI classes to delineate relative structural-priority areas. Dispersed and isolated housing accounted for 55% and 37% of mapped housing structures, respectively, while the WUI contained an estimated 18,100 inhabitants distributed across 3620 housing units. The resulting WUI × AI structural-priority layer covered 0.863 km², of which high- and very-high-priority zones jointly represented 0.544 km² (63.04%). These priority areas identify locations where structurally exposed settlement configurations coincide with greater horizontal fuel continuity, providing a spatial basis for targeted fuel management, surveillance planning, emergency-access improvement, and wildfire-prevention actions. By improving the spatial targeting of preventive measures, the framework can contribute to sustainable forest and land management, disaster-risk reduction, ecosystem protection, and the resilience of WUI settlements. Full article

Electric vehicles (EVs) are attracting choice and adoption as a travel mode in global transportation systems, driven by technological innovation, economic considerations, and advancing sustainable urban development. The planning, development, design, and location of EV charging stations are challenging tasks for underdeveloped countries such as Pakistan. To propose the site location for an EV charging station, this study comprises Multi-Criteria Decision Analysis and Geographic Information Systems. The study adopts a mixed-methods design, combining qualitative expert input with quantitative spatial analysis to investigate technical, social, and infrastructural criteria. The study considers indicators, including site suitability, population density, interaction between land use and transport, road network, transportation interactions, existing electricity grid infrastructure, and existing fueling and charging stations. This research presents pairwise expert comparisons, indicating that grid capacity (0.28) and demand (0.30) are important factors to consider. A composite suitability Index (CSI) through GIS-weighted overlay was used to classify the area into low, medium, and high suitability zones. According to the CSI, 26% of the area falls in highly suitable areas for EV infrastructure in Islamabad, and 41% falls in medium-to-high suitable areas. The remaining 33% area lies in low-suitability peripheral zones near the hilly region of Islamabad city, which is not considered suitable for EV infrastructure. A total of 67% of the city’s area is suitable for EV infrastructure. Full article

Land-use change affects regional carbon accounting through ecological conversion and the concentration of energy-intensive economic activity. We combined 30 m China Land Cover Dataset maps for 2010, 2015, 2020, and 2025 with provincial socioeconomic and energy statistics to quantify land-use transitions and carbon emissions across nine Yellow River Basin provinces. Construction-land-associated emissions were decomposed using the logarithmic mean Divisia index, factors associated with land expansion were examined using random-forest models, and three 2030 scenarios were evaluated. Construction land expanded by 38.87% from 2010 to 2025, with 71.33% of new construction land converted from cropland and 17.75% from grassland. Net land-use carbon emissions increased by 69.82%, from 1139.06 to 1934.33 million t C. Economic-output density contributed 1144.84 million t C to the increase in construction-land-associated emissions, compared with 576.11 million t C from land expansion, whereas declining energy intensity offset 922.72 million t C. Projected 2030 emissions ranged from 2124.72 million t C under ecological protection to 2866.55 million t C under urban expansion. Construction-land expansion was substantial, but economic-output density made the larger positive contribution to historical emission growth. The projected 2030 estimates depended on the combined trajectories of construction-land demand, economic growth, and energy intensity. These findings highlight the importance of coordinating land-use planning, economic development, and energy-efficiency improvement for sustainable low-carbon transitions. Full article

Many current studies have purely regarded green finance as green credit, ignoring the background of carbon neutrality and energy transition. This paper investigates the relationships among green finance, green technological innovation, and urban ecological welfare performance. Using 279 Chinese cities as examples, this paper reveals the following: there is (1) a direct positive effect, where a 0.1-unit absolute increase in the green finance index (GFI) is associated with an average 0.0605-unit rise in ecological welfare performance (EWP); (2) a partial mediation mechanism through green technological innovation, establishing a “finance → technology → ecology” pathway; (3) temporal persistence of positive effects across pre-2012 and post-2012 policy periods; and (4) regional disparities with significant impacts in Eastern/Western/Northeastern China but insignificant effects in Central China due to lower green credit allocation and weaker R&D intensity. Robustness checks, including Winsorization and subgroup analyses, validate these results. This study advances the integration of environmental finance with sustainable development theory, offering actionable insights for achieving ecological welfare goals. Full article

Climate risk has become a major challenge for the development of sustainable finance and the enhancement of regional economic resilience. However, limited attention has been paid to how climate shock affects the spatial organization of financial dependence across cities. Using daily return data for firms listed on China’s A share market from 2021 to 2025, this study examines the relationship between climate shock and the urban equity risk network. Firm returns are first aggregated according to corporate location, after which annual networks and rolling backbone networks are constructed. The resulting network indicators are then matched with a national daily climate shock index. The empirical analysis combines comparisons across climate shock groups, regressions, alternative windows, lagged models, and descriptive analyses of extreme climate windows. The results show that urban equity risk in China is spatially uneven. Coastal urban regions and several major inland cities occupy influential positions in the network. Higher mean climate shock is significantly associated with greater average edge weight and average weighted degree, indicating stronger dominant risk connections across cities. The main findings remain stable in lagged models and specifications based on longer rolling windows, whereas acute extreme climate shocks are associated with more heterogeneous network responses. The findings suggest that sustainable financial governance should incorporate network monitoring across cities, regional regulatory coordination, and dynamic climate shock testing to strengthen the resilience of urban and regional financial systems to climate risk. Full article

Under climate change, the demand for high-quality urban ecological security is rising. This study focuses on how rapid urbanization and climate change affect ecological risk, resilience, and land use functions (LUFs) spatial co-variation in the Pearl River Delta. Land use was simulated under Shared Socioeconomic Pathways (SSPs) using system dynamics (SD) and the interaction network–Patch-generating Land Use Simulation (intPLUS) model. Ecological risk was quantified via the landscape ecological risk index (LERI) and habitat degradation index (HDI), while ecological resilience was obtained using an adaptability–resistance–recovery framework, producing a comprehensive ecological risk–resilience index (CERRI). Ecosystem services were assessed using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. Spearman correlation, geographically weighted regression (GWR), constraint lines, and extreme gradient boosting with SHapley Additive exPlanations (XGBoost-SHAP) revealed LUFs patterns, nonlinear relationships and threshold effects, and driving factors. The results indicate that construction land expands mainly at the expense of cropland (~4049–4157 km²) from 2023 to 2035, while woodland and water remain largely stable. CERRI shows a concentric pattern (2023 domain mean = 0.638), with safer peripheral belts and a more risk-dominated central–southern core; under coupling-weight uncertainty with 2023-fixed common-reference normalization, SSP245 was preferred in all Monte Carlo iterations (best-scenario probability = 1.000). EF–LF, EF–PF and LF–PF retain stable nonlinear forms. Elevation, economic vitality and transport accessibility are the leading drivers, with model-derived breakpoints near low-elevation, high-vitality and moderately accessible transport nodes. This study provides the CERRI framework to support ecological security monitoring and adaptive land-use management, contributing to more sustainable regional development under climate change. Full article

Improving water resource use efficiency (WRUE) is essential for achieving sustainable water management under increasing socioeconomic and environmental pressures. This study investigates the spatiotemporal evolution, associated factors, and spatial transition characteristics of WRUE across 11 provincial-level administrative regions in the Yangtze River Basin during 2010–2024. An integrated framework combining the super-efficiency SBM-window DEA model, Malmquist–Luenberger index, GeoDetector, and conventional and spatial Markov chain models was developed to characterize efficiency dynamics, productivity changes, explanatory factors, and state-transition pathways. The results showed that WRUE exhibited an overall fluctuating upward trend with a clear spatial gradient of lower reaches > middle reaches > upper reaches. The mean ML index was 1.004, indicating that technological change (TC) was the main contributor to productivity improvement. Urbanization rate, water use per CNY 10,000 of GDP, industrial water-use share, and primary-industry share exhibited relatively high explanatory power, and their interactions enhanced explanatory power. Markov analysis revealed strong persistence in WRUE states, while transition probabilities differed across spatial neighborhood conditions. Assuming stable transition probabilities, the high-efficiency state would reach a steady-state probability of 0.8155. These findings provide insights for differentiated water resource management and coordinated regional development. Full article