Search Results (759)

Artificial intelligence (AI) is increasingly recognised for its transformative implications for sustainability transitions. Yet little is known about how AI co-evolves with green technological innovation systems and whether institutional adaptation keeps pace with technological diffusion. This study maps 3357 peer-reviewed publications between 2003 and 2025 using transformer-based topic modelling and cross-model triangulation to characterise structural evolution across enabling technologies, sectoral applications, and governance domains. Results reveal a reproducible triadic configuration consistent with innovation-system layering, alongside pronounced asymmetry in growth trajectories. While AI-enabled application domains (e.g., energy systems, waste and circularity, agriculture, and urban mobility) exhibit sustained expansion and increasing specialisation, governance and institutional strands demonstrate thinner density, greater model sensitivity, and delayed acceleration. These patterns are consistent with an asynchronous relationship between technological capability and institutional oversight, echoing the innovation-regulation lag observed in other technology-diffusion processes. The findings contribute to technological change literature by providing systematic evidence on the thematic structure and evolution of AI-enabled sustainability research and by proposing a co-evolution diagnostic framework for monitoring alignment between technological expansion and governance attention. Full article

Improving energy efficiency is essential for easing resource and environmental constraints and advancing sustainable development. Carbon emissions trading influences urban energy use through carbon pricing, but how it affects urban energy efficiency remains insufficiently understood. Using panel data for 278 Chinese cities from 2006 to 2023, this study evaluates the effects of China’s carbon emissions trading pilots with a staggered difference-in-differences design. The results show that the pilots significantly improve urban energy efficiency, and this finding remains robust across multiple identification tests and robustness checks. Mechanism tests indicate that the pilots promote green technological innovation and digital transformation while reducing capital and labor misallocation. Heterogeneity analyses reveal stronger effects in cities with tighter credit constraints, more stringent environmental regulation, and lower energy consumption elasticity. Further analyses indicate that the pilots promote economic growth and strengthen urban economic growth momentum. Overall, carbon emissions trading improves energy efficiency while enhancing urban economic performance. From an urban energy-efficiency perspective, this study clarifies the role of carbon emissions trading in advancing sustainable development and provides empirical evidence for refining carbon markets and promoting green, low-carbon urban development. Full article

Rapid urbanization and unplanned land development have transformed Dhaka into one of the most densely built metropolitan areas in South Asia, leading to increased surface heat accumulation and growing pressure on urban energy systems. Numerous studies have reported a progressive rise in Dhaka’s Land Surface Temperature (LST), accompanied by a strong negative correlation between the Normalized Difference Vegetation Index (NDVI) and LST and a positive correlation between the Normalized Difference Built-Up Index (NDBI) and LST. However, spatially explicit assessments that integrate multiple geospatial proxies to characterize urban energy-intensity patterns remain limited, particularly in data-scarce cities where direct energy-consumption data are unavailable. The present study aims to develop and map a proxy-based Urban Energy Intensity Index (UEI) for Dhaka by integrating remote sensing, GIS, and AHP-MCDA techniques. Landsat 9 imagery and VIIRS nighttime light data were processed to derive NDVI, NDBI, and LST layers, while building footprints and road networks were extracted from OpenStreetMap to represent urban form. Eight environmental, built-environment, and anthropogenic indicators were standardized and weighted using the Analytic Hierarchy Process (AHP) before integration through a GIS-based weighted overlay approach. Results show that dense, impervious, and intensely illuminated built-up cores exhibit elevated LST and UEI values, while peri-urban and vegetated areas consistently display lower values, producing spatially distinct high-UEI clusters concentrated within Dhaka’s urban core. Because the index is derived from proxy indicators and was not validated against observed energy-consumption data, the findings should be interpreted as relative spatial patterns rather than direct measures of energy use or energy efficiency. These findings demonstrate the effectiveness of integrating remotely sensed and geospatial indicators to capture intra-urban variability in proxy-based urban energy intensity. The study provides a scalable and data-efficient framework for identifying priority zones for urban planning interventions and supports targeted strategies such as urban greening, surface albedo enhancement, and sustainable land-use planning to mitigate thermal stress. Full article

The purpose of this research is to propose a sustainable urban support regeneration system aimed at recovering the historic urban landscape of Rimac, Lima (2024). The Historic Center of Rimac is currently undervalued due to several issues affecting the district, including citizen insecurity, the limited percentage of green areas, excessive and unplanned urban growth, the abandonment of the district’s historic centers, and its disconnection from the surrounding urban environment. The methodology was developed through a review of bibliographic documents, such as scientific publications, together with the use of 2D and 3D software tools, which enabled the collection of environmental, cultural, physical–spatial, and urban information. The implementation of sustainable public spaces within the historic urban landscape of Rimac will transform the area into an attractive tourist and cultural destination. The viewpoints will provide panoramic views, the urban forests will improve air quality and increase green areas, and the site museum will preserve and disseminate the rich local history. Together, these interventions will promote urban regeneration, community wellbeing, and the sustainable development of the area, thereby offering an efficient proposal aimed at optimizing the district’s potential and implementing strategies that contribute to the achievement of the Sustainable Development Goals (SDGs). Full article

The escalating climate crisis presents a profound challenge to global environmental equilibrium, with rapid urbanization acting as a primary catalyst for land-use transformation. This study investigates the intricate relationship between land use and land cover changes (LULC) and the intensification of the Surface Urban Heat Island (SUHI) effect within the Shillong Planning Area (SPA). By integrating remote sensing data with advanced geospatial modeling and machine learning architectures which include Random Forest (RF), Support Vector Machine (SVM), and XGBoost, the research provides a comprehensive analysis of environmental shifts from 2000 to 2024, with predictive projections extending to 2034 and 2044. The analysis reveals a significant expansion in the built environment, with the Normalized Difference Built-up Index (NDBI) rising from 0.17 to 0.26. This urban growth has come at the expense of ecological health, as evidenced by a decline in the Normalized Difference Vegetation Index (NDVI) from a peak of 0.87 down to 0.74. A strong negative correlation between vegetative density and Land Surface Temperature (LST) underscores the critical role of green infrastructure in regional climate regulation. SUHI projections using the RF model, which achieved an Area Under the Curve (AUC) of 0.868, estimate SUHI values of 6.02 °C for 2034 and 6.66 °C for 2044. Predicted LULC scenarios for 2034 and 2044 suggest continued urban expansion, likely intensifying thermal stress. The application of predictive modeling through machine learning provides a robust framework to inform climate-resilient urban planning and sustainable land management. Full article

To advance its green and low-carbon transition, China has implemented the Low-Carbon City Pilot Policy (LCCPP) as a strategic initiative. A critical question remains unanswered on whether this policy effectively improves urban carbon productivity and facilitates the decoupling of economic growth from carbon emissions. Using the phased expansion of the LCCPP across Chinese cities as a quasi-natural experiment, this study constructs a multi-period difference-in-differences (DID) model based on a panel dataset of 276 prefecture-level and above cities from 2007 to 2023. The empirical results show that the LCCPP significantly enhances urban carbon productivity in pilot cities relative to non-pilot counterparts. This finding remains robust across a series of sensitivity checks. Mechanism analysis provides suggestive evidence that the policy may operate through two primary channels: fostering green technological innovation and promoting economic agglomeration. Heterogeneity analysis indicates that the policy’s positive effects are more marked in developed cities, innovation-active cities, high-carbon-emission cities, and environmentally prioritized cities. Furthermore, moderation analysis demonstrates that stricter environmental regulations strengthen the policy’s effectiveness. These findings provide empirical evidence for optimizing the design of low-carbon policies and offer actionable insights for tailoring green urban transformation strategies to local conditions. Full article

Urban sustainability depends not only on environmental efficiency but also on cities’ capacity to withstand ecological shocks, maintain essential services, and adapt to long-term resource constraints. This study examines whether the intelligent economy strengthens urban green resilience, a key foundation of sustainable urban development. Using a balanced panel of 273 Chinese prefecture-level cities from 2013 to 2023, we construct entropy-weighted indices and apply two-way fixed-effects, instrumental-variable, mechanism, heterogeneity, and spatial models. A one-standard-deviation increase in the intelligent-economy index is associated with a 0.205-standard-deviation increase in urban green resilience, and the result remains robust across alternative samples, variable treatments, machine-learning estimation, and instrumental-variable specifications. Digital inclusive finance and industrial structure rationalization partially transmit this effect. The gains are greater in cities with stronger human capital, stricter environmental mandates, locations southeast of the Hu Line, and closer access to fiber-optic backbone nodes. Spatially, adjacent-city development generates a negative conditional neighboring effect, whereas the feedback-adjusted indirect effect is positive, with significant diffusion within 200 km and a non-monotonic pattern across distance bands. These findings show that intelligent development supports urban sustainability when technological capacity is converted into inclusive finance, coordinated industrial transformation, effective governance, and regionally shared resilience. Full article

Public pedestrian pathways have been widely adopted in planned cities to improve walkability and strengthen connections between residential areas and public spaces. However, existing studies have largely focused on management issues and post-occupancy privatization, with limited attention given to how these pathways evolve throughout the planning and development process. This study investigates the evolution of public pedestrian pathways in Sejong City, Korea, a state-led planned city developed through a phased planning system. Based on district unit plans, design competition guidelines, detailed design documents, as-built drawings, aerial imagery, and field verification of implemented conditions, the study analyzes the changing planning objectives, spatial characteristics, and functional roles of public pedestrian pathways across five planning generations. The results reveal three major trends. First, public pedestrian pathways evolved from lot-level circulation routes into integral components of neighborhood- and city-scale pedestrian networks linking parks, green corridors, schools, and community facilities. Second, planning approaches were continuously refined through district unit planning, housing design competitions, and implementation experience, leading to increasingly integrated and strategic spatial configurations. Third, the growing integration of public pedestrian pathways with community facilities, public open spaces, and green infrastructure transformed them from simple movement corridors into semi-public infrastructure intended to support social interaction and everyday community life. The findings suggest that public pedestrian pathways function not merely as circulation facilities but as planning mechanisms that enhance urban openness, connectivity, publicness, and community integration. The study demonstrates how public pedestrian pathways can evolve into semi-public infrastructure through the cumulative refinement of planning across successive planning generations and provides planning implications for future pedestrian-oriented urban development. Full article

Achieving a balance between economic expansion and environmental preservation is a core challenge of sustainable development. Based on panel data from 41 cities in the Yangtze River Delta region from 2006 to 2023, this study develops a digital economy index, measures GTFP using the SBM-GML framework, and examines the relationship between digital economy development and GTFP. The results show that digital economy development is positively associated with GTFP, and the findings remain robust after a series of robustness and endogeneity tests. Further moderating analysis indicates that industrial structure rationalization, industrial structure advancement, green innovation, and ecological compensation policy strengthen the relationship between digital economy development and GTFP. Heterogeneity analysis shows that this relationship is stronger in high-tier cities, highly urbanized cities, and Broadband China demonstration cities. Spatial analysis further suggests that digital economy development may generate spillover effects through intercity linkages within the Yangtze River Delta. By integrating digital transformation, ecological governance, regional interdependence, and green productivity improvement into a unified analytical framework, this study provides city-level evidence for promoting coordinated green transformation and sustainable regional development. Full article

Urban green areas are essential for human well-being, biodiversity, and environmental sustainability. Although railway renewal projects are celebrated today, Italy pioneered the Flowery Stations Contest (FSC) in the early twentieth century. This study provides the first comprehensive synthesis of the FSC experience (1911–1915), investigating its historical evolution, organizational features, and botanical aspects. A systematic review of 81 historical documents was conducted to reconstruct the contest’s framework. To evaluate long-term impact, we surveyed 90 historically top-ranked stations via satellite imagery and investigated the case study of Ripafratta station (a fraction of San Giuliano Terme, Pisa, Tuscany). Results show the FSC involved up to 291 stations, prioritizing esthetic decorum and hygiene against locomotive soot. Although organizers recommended 64% non-native genera, stationmasters favoured local biodiversity, increasing effectively employed native genera to 43%. Nowadays, 54% of surveyed stations retain their gardens, mainly located in rural areas, yet 82% of these are neglected following the decline of the resident stationmaster’s role. We conclude that the FSC established a significant physical and cultural legacy. Recovering its model of decentralized stewardship could offer a strategic framework for modern urban regeneration, transforming stations into multifunctional hubs while preserving regional floristic identity, in alignment with contemporary European sustainability models. Full article

Copenhagen is often regarded as a pioneer city in climate change adaptation and green–blue infrastructure deployment. However, when addressing extreme environmental problems such as heavy rainfall flooding and urban heat island effects, many interventions remain site-specific and insufficiently connected across spatial scales. This article investigates how Nature-Based Solutions (NBS) can be structured as an integrated spatial infrastructure system to enhance climate resilience and urban livability in Copenhagen. The research combines theoretical analysis, comparative project studies, GIS-based spatial analysis, and a multi-criteria evaluation matrix. Building on this method, a multi-scalar framework for NBS interventions is developed, which consists of site prioritization at the Meso scale, development strategies at the Micro scale, and NBS spatial design at the Nano scale. With the assessment criteria adapted from the UNalab project Nature-Based Solutions Technical Handbook Factsheets, the results demonstrate that Nano-scale design strategy can enhance green connectivity, create new inclusive urban public spaces, transform existing industrial areas, and improve new streets and parks for climate resilience. The Meso-scale distributed measures deliver localized benefits such as infiltration and flood buffering, while the most effective strategies integrate cross-scalar NBS interventions within a connected network. The case of Nordhavn is analyzed through multi-criteria selection and multifunctionality assessment as a qualitative process for a better demonstration of the practical application of NBS prioritization and spatial design analysis. Full article

Green and Blue Infrastructure (GBI) is increasingly addressed within climate adaptation and mitigation policies as a strategic operational measure for reducing climate-related impacts in urban environments. However, GBI effectiveness relies strictly on the biophysical condition of natural assets and on the capacity to monitor and interpret ecosystem processes over time, specifically vegetation quality and its physiological response to climatic stressors within complex urban fabrics. This variability emphasizes the need to integrate ecosystem performance into decision-making through digital frameworks capable of quantifying and accounting for ecological resources across temporal scales. In this context, Remote Sensing (RS) technologies provide a structured informational basis for assessing vegetation health and surface thermal patterns in relation to climatic stress thresholds and human exposure. This paper presents a policy-aligned geospatial evidence framework to bridge the gap between environmental monitoring and urban climate action. By integrating high-resolution multispectral remote sensing with heterogeneous spatial datasets and climate models, the framework enables the multitemporal assessment of ecological conditions to inform where GBI measures can support SECAP implementation, project refinement, and monitoring activities. Developed within the Horizon Europe KNOWING project and applied to the Naples East district, Italy, the framework was operationalized within the city’s Sustainable Energy and Climate Action Plan (SECAP). The application produces scenario-oriented outputs for interpreting the potential contribution of GBI and NbS measures to outdoor heat-stress reduction under SECAP conditions. Its practical value lies in translating biophysical data into reusable GIS/WMS layers that connect ecological performance, climate exposure, socio-energetic vulnerability, and planned urban transformations, thereby supporting SECAP implementation, project refinement, and monitoring. Full article

New-quality productive forces provide an important conceptual lens for understanding how innovation-driven development, digital empowerment, and the green transition jointly support sustainable regional development. From a geographical perspective, this study develops a multidimensional evaluation system for new-quality productive forces based on the three elements of productive forces: laborers, means of labor, and objects of labor. Using panel data for 31 provincial-level administrative units in China from 2012 to 2022, we integrate the entropy weight method, standard deviation ellipse, exploratory spatiotemporal data analysis, the obstacle degree model, and the random forest model to examine the spatiotemporal evolution and influencing mechanisms of new-quality productive forces. The results show that: (1) China’s new-quality productive forces increased steadily during the study period, but their overall level remained relatively low and regional disparities continued to widen. Spatially, they exhibited a pronounced “high in the east and low in the west” pattern, with South China and East China maintaining leading positions and Guangdong and Jiangsu forming a dual-core growth structure. (2) The spatial center of gravity remained southeast of the Hu Huanyong Line, and its expansion direction was broadly parallel to this line, indicating a relatively stable spatial configuration. The ESTDA results further reveal significant positive spatial autocorrelation, strong temporal inertia, and marked path dependence in local spatial transitions. (3) High-tech talent supply, innovation and entrepreneurship vitality, and ecological governance capacity constitute the main internal bottlenecks constraining the development of new-quality productive forces. The analysis of external factors indicates that economic scale and population size are the primary predictors of NQPF development, whereas government intervention, openness, urbanization, and industrial structure exhibit varying degrees of nonlinearity and regional heterogeneity. These findings enrich the geographical interpretation of new-quality productive forces and provide empirical evidence for formulating differentiated regional innovation policies and productivity transformation strategies. Full article

Rural green development is essential for coordinating ecological protection, rural revitalisation and spatial governance in ecological spaces within urban agglomerations. Taking the Chang-Zhu-Tan Ecological Green Heart region in China as a case study, this study evaluates rural green development in 10 counties, county-level cities and districts from 2013 to 2022. A combined weighting–TOPSIS model is used to measure development levels, while Global Moran’s I, the Theil index and XGBoost–SHAP are applied to examine spatial patterns, regional disparities and key associated factors. The results show that rural green development improved overall, with the regional average index increasing from 0.315 in 2013 to 0.378 in 2022. High-value areas gradually expanded, and the Changsha group formed the main high-value core, but no statistically significant global spatial clustering was identified. Regional disparities narrowed during the study period, although intra-group disparities, especially within the Zhuzhou group, remained the main source of imbalance. Human capital, medical resources, income level, urbanisation level, PM_2.5 concentration and pesticide use intensity were closely associated with rural green development, with socioeconomic factors generally contributing positively and environmental pressures acting as constraints. These findings suggest that rural green development in ecological green heart regions is a spatially differentiated and multi-factor process, providing empirical evidence for differentiated county-level governance, coordinated ecological protection and rural green transformation in urban agglomerations. Full article

Enhancing green total-factor energy efficiency (GTFEE) is a critical pathway for promoting the green transformation of economic and social development. However, the potential influence of the construction and development of urban functional networks (UFNs) on this process has received limited scholarly attention. Using panel data from 148 cities across nine major Chinese urban agglomerations from 2010 to 2023, this study finds the following: First, the development of UFNs at the urban agglomeration scale significantly enhances GTFEE. Second, UFNs improve GTFEE through two distinct mechanisms: “government action” and “market efficiency.” The “government action” mechanism primarily operates by promoting market integration, reducing land resource misallocation, and curbing urban sprawl. The “market efficiency” mechanism functions by enhancing factor mobility, optimizing the allocation of production factors, and accelerating the diffusion of green technological innovations. Third, the effect of UFNs on GTFEE varies according to local development conditions, infrastructure connectivity, and policy continuity and coordination. The enhancement effect is more pronounced in cities located near coastlines, those connected to other cities within the agglomeration by high-speed rail, and cities with longer-serving municipal Party secretaries. Fourth, urban agglomerations characterized by polycentric spatial structures and stronger agglomeration externalities are better able to leverage the functional node effects of their constituent cities, thereby further enhancing GTFEE. Full article