Search Results (13,591)

Urban neighborhoods in India face an uneven distribution and limited accessibility to parks and playgrounds, particularly in dense mixed-use areas where rapid urbanization constrains green infrastructure planning. To address these challenges, the Sustainable Transportation Assessment Index (SusTAIN) framework was developed to evaluate sustainable transportation in Indian urban neighborhoods, with ‘Accessibility’ identified as a crucial subtheme. Recent advancements in Geographic Information Systems (GISs) and urban data analysis tools have enabled accessibility assessments of parks and playgrounds at a neighborhood scale, yet the OSMnx approach has been only marginally explored and compared in the literature. This study addresses this gap by comparing three tools—the Quantum Geographic Information System (QGIS), OSMnx, and Space Syntax—for accessibility assessments of parks and playgrounds in Ward 60 of Kalyan Dombivli city, based on the 15-Minute City concept. Accessibility was evaluated using 25 m and 100 m grid resolutions under peak and non-peak conditions across public and private transportation modes. The findings show that QGIS offers highly consistent results at micro-scale (25 m), while OSMnx provides better accuracy at coarser scales (100 m+). The results were validated with space syntax through integration and choice values. The comparison highlights spatial disparities in accessibility across different tools and transportation modes, including Intermediate Public Transport (IPT), which remains underexplored despite its crucial role in last-mile connectivity. The presented approach can support municipal authorities in optimizing neighborhood mobility and is transferable for applying the SusTAIN framework in other urban contexts. Full article

Travel planning is a process that allows users to obtain maximum benefit from their time, cost and energy. When planning a route from one place to another, it is an important option to present alternative travel areas on the route. This study proposes a travel route planning (TRP) architecture using a Long Short-Term Memory (LSTM) and Extreme Gradient Boosting (XGBoost) model to improve both travel efficiency and environmental sustainability in route selection. This model incorporates carbon emissions directly into the route planning process by unifying user preferences, location recommendations, route optimization, and multimodal vehicle selection within a comprehensive framework. By merging environmental sustainability with user-focused travel planning, it generates personalized, practical, and low-carbon travel routes. The carbon emissions observed with TRP’s artificial intelligence (AI) recommendation route are presented comparatively with those of the user-determined route. XGBoost, Random Forest (RF), Categorical Boosting (CatBoost), Light Gradient Boosting Machine (LightGBM), (Extra Trees Regressor) ETR, and Multi-Layer Perception (MLP) models are applied to the TRP model. LSTM is compared with Recurrent Neural Networks (RNNs) and Gated Recurrent Unit (GRU) models. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Squared Error (MSE), and Normalized Root Mean Square Error (NRMSE) error measurements of these models are carried out, and the best result is obtained using XGBoost and LSTM. TRP enhances environmental responsibility awareness within travel planning by integrating sustainability-oriented parameters into the decision-making process. Unlike conventional reservation systems, this model encourages individuals and organizations to prioritize eco-friendly options by considering not only financial factors but also environmental and socio-cultural impacts. By promoting responsible travel behaviors and supporting the adoption of sustainable tourism practices, the proposed approach contributes significantly to the broader dissemination of environmentally conscious travel choices. Full article

Air pollution, a critical environmental threat, has worsened alongside urbanization and industrialization, particularly in rapidly developing economies like India. Despite efforts to curb emissions, the concurrent rise in energy consumption, industrial activity, and digitalization complicates the fight against air pollution. This study examines the interplay between air pollution, economic growth, clean energy transition, digitalization, and urbanization in India from 1990Q1 to 2020Q4. Using advanced econometric techniques, including multivariate quantile-on-quantile regression (MQQR) and the quantile ADF and quantile KPSS tests, we investigate the complex, non-linear relationships across these factors. Our findings suggest that while economic growth exacerbates air pollution, the clean energy transition can mitigate its impact, especially when integrated with digitalization. However, the effects of digitalization are nuanced, potentially increasing pollution unless paired with green energy policies. The study demonstrates that the combined strategies of promoting clean energy and digitalization can provide a sustainable pathway for reducing air pollution in India. This work offers novel insights into the role of digital technologies in enhancing environmental sustainability and highlights the need for policy interventions that balance economic growth with climate resilience. The results present a roadmap for India’s sustainable development, emphasizing the integration of clean energy, digital innovation, and urban planning. Full article

The reuse of abandoned mines is not a pure ecological project but a complex social public project. While it is unsustainable to reuse abandoned mines without ecological restoration, such restoration without comprehensive resource utilization will cause a serious waste of resources. Therefore, to reduce the contradiction between ecological restoration and resource utilization in the process of reusing abandoned mines, there is an urgent need to research the classification, grading development, and utilization evaluation index system of abandoned mine resources. Based on the concept of “energy, resource and functionalization” three-dimensional coordinated development and utilization, this paper analyzes the value connotation of abandoned mine reuse and constructs an evaluation index system for the reuse value of abandoned mine resources, including resource conditions, ecological conditions, and development conditions. Secondly, according to the priority needs of abandoned mine reuse, the minimum factor method is used to design a development sequence that can take into account the reuse of abandoned mines and the coordinated development of the ecological environment and the region. On this basis, the value of abandoned mine reuse is divided into four grades and three development stages. Taking the Jingxi Mining Area as an example, corresponding development and utilization suggestions are proposed, and the guiding value of the evaluation index system in assessing resource potential and optimizing of development paths is verified. The research results can provide scientific decision support for planning the development and utilization of abandoned mine resources. They also have practical significance for constructing green development technology standards and promoting ecological restoration and industrial transformation and upgrading in mining areas. Full article

Ground settlement is a multifaceted geological phenomenon driven by natural and man-made forces, posing a significant impediment to sustainable urban development. Thus, ground settlement susceptibility (GSS) mapping has emerged as a critical tool for understanding and mitigating cascading hazards in seismically active and anthropogenically modified sedimentary basins. Here, we develop an integrated framework for assessing GSS in the Pohang region, South Korea, by integrating Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR)-derived vertical land motion (VLM) data with seismological, geotechnical, and topographic parameters (i.e., peak ground acceleration (PGA), effective shear-wave velocity (V_s³⁰), site period (T_s), general amplification factor (A_F), seismic vulnerability index (K_g), soil depth, topographic slope, and landform classes) through ensemble machine learning models such as Random Forest (RF), XGBoost, and Decision Tree (DT). Analysis of 56 Sentinel-1 SLC images (2017–2023) revealed persistent subsidence concentrated in Quaternary alluvium, reclaimed coastal plains, and basin-fill deposits. Among the tested models, RF achieved the best performance and strongly agreed with field evidence of sand boils, liquefaction, and structural damage from the 2017 Pohang earthquake. The very-high-susceptibility zones exhibited mean subsidence rates of −3.21 mm/year, primarily within soft sediments (V_s³⁰ < 360 m/s) and areas of thick alluvium deposits. Integration of the optimal RF-based GSS index with regional building inventories revealed that nearly 65% of existing buildings fell within high- to very-high-susceptibility zones. The proposed framework demonstrates that integrating PSInSAR and ensemble learning provides a robust and transferable approach for quantifying ground settlement hazards and supporting risk-informed urban planning in seismically active and complex geological coastal environments. Full article

The paper proposes a multi-objective approach for optimizing the structure of electric power generation amid tightening requirements for the energy efficiency and environmental safety of power systems. The study identifies relevant directions for improving advanced natural gas-fired power plants. An algorithm for the multi-objective optimization of the power generation structure has been developed, based on the sequential application of mathematical tools such as principal component analysis, Pareto optimization, and the entropy-based TOPSIS method. It has been established that under the model’s given constraints, the share of highly efficient energy complexes in Pareto-optimal generation structures typically does not exceed 40% of the total generating capacity, while the share of low-carbon complexes does not exceed 60%. Furthermore, as the energy planning horizon extends, the share of carbon-free energy complexes in the most efficient generation structures increases, reaching 51% with the introduction of generating capacity in 2031, and 92% with a system commissioning date in 2035. The proposed methodology enables a quantitative analysis of the evolution of the optimal electric power generation structure over time, highlighting a priority pathway for the development of sustainable energy. Full article

Air pollution, soil contamination, and rising illness demand integrated, nature-based solutions. Willow trees (Salix spp.) uniquely combine ecological resilience with therapeutic value, remediating polluted environments while supporting human well-being. This review synthesizes recent literature on the established role of Salix spp. in phytoremediation and growing contribution to forest therapy through emissions of biogenic volatile organic compounds (BVOCs). As urbanization accelerates and environmental pressures intensify globally, the surprising adaptability and multifunctionality of Salix justify the utilization of this genus in building resilient and health-promoting ecosystems. The major points discussed in this work include willow-based phytoremediation strategies, such as rhizodegradation, phytoextraction, and phytostabilization, contributing to restoring even heavily polluted soils, especially when combined with specific strategies of microbial augmentation and trait-based selection. Salix plantations and even individual willow trees may contribute to forest therapy (and ‘forest bathing’ approaches) through volatile compounds emitted by Salix spp. such as ocimene, β-caryophyllene, and others, which exhibit neuroprotective (against Parkinson’s disease), anti-inflammatory, and mood-enhancing properties. Willow’s significantly extended foliage season in temperate regions allows for prolonged ‘forest bathing’ opportunities, enhancing passive therapeutic engagement in urban green infrastructures. Remarkably, the pharmacological potential of willow extends beyond salicin, encompassing a diverse array of phytocompounds with applications in phytomedicine. Finally, willow’s ease of propagation and adaptability make this species a convenient solution for multifunctional landscape design, where ecological restoration and human well-being converge. Overall, this review demonstrates the integrative value of Salix spp. as a keystone genus in sustainable landscape planning, combining remarkable environmental resilience with therapeutic benefits. Future studies should explore standardized methods to evaluate the combined ecological and therapeutic performance of Salix spp., integrating long-term field monitoring with analyses of BVOC emissions under varying environmental stresses. Full article

Human–wildlife conflicts can be broadly categorized from the perspective of human activities into conflicts (a) caused by the expansion of human activities into wildlife habitats, and (b) resulting from the re-expansion of wildlife habitats due to the decline of human activities. The first type of conflict has been managed through the systematic training of wildlife managers, field specialists, and well-organized institutional frameworks. In Japan, Asiatic black bears (Ursus thibetanus) and brown bears (Ursus arctos) have increasingly come into human contact because of habitat re-expansion. Short-term measures to protect human life and property include the implementation of the 2024 and 2025 revisions of the Wildlife Protection and Hunting Management Act, which designated bears as “managed wildlife” and “dangerous wildlife” and permitted emergency culling in residential areas. However, Japan’s approach remains limited in scope and depth, relies on ad hoc responses by local hunters, and lacks adequate public education and effective long-term sustainability planning. This study highlights the necessity of a multi-layered policy framework that integrates human–wildlife conflict management, particularly human–bear conflict, by comparing U.S. laws and policies and incorporating them into medium- and long-term strategies for community resilience and national land conservation. This approach may serve as a model for countries and regions facing similar demographic and ecological challenges. Full article

In recent years, European cities have experienced rapid changes in their functional and spatial organisation, which have affected, among others, the natural environment, the economy and society. The intensive and often uncontrolled growth of residential development associated with suburbanisation significantly impacts areas located around urban areas. Growing investment pressures usually lead to the transformation of rural and naturally valuable areas, altering their character and functions. Solving these problems requires developing a method to determine the main directions and intensity of land use changes in the context of urbanisation pressures and sustainable spatial development. This article presents the results of a spatiotemporal analysis of the dynamics of built-up area development in rural and suburban zones, utilising Geographic Information Systems (GIS) technology. The study focused on the expansion of single- and multi-family housing around the city of Białystok, Poland, between 1997 and 2022. The analysis was based on spatial data, including available orthomosaics and cadastral data from the Topographic Objects Database (BDOT10k). The GIS-based analysis covered an area of nearly 2000 km² and included methods for change detection, analysis, and land cover classification. The results indicated a marked intensification in landscape transformations, particularly in transition zones between rural and urban areas. At the same time, forests and protected zones significantly influenced the direction and pace of development, acting as natural barriers limiting spatial expansion. The results indicate the need to consider environmental factors (e.g., protected areas and forests) in spatial planning processes and sustainable development policies. The study confirms the high usefulness of GIS tools in monitoring and forecasting spatial change at both the local and regional scales. This research also contributes to the discussion on urbanisation, its characteristics, causes, and consequences, and highlights the role of green spaces in limiting sprawl. Full article

Marine Spatial Planning (MSP), the prevailing global governance paradigm for sustainable ocean development, confronts the critical challenge of integrating climatic uncertainty into its core processes. Reliance on the stationarity assumption compromises risk assessments for long-lifecycle assets within the Blue Economy, thereby impeding progress toward principal sustainability objectives. This article introduces and validates FARO (Framework for Adaptive Operational Risk Analysis), a methodological framework designed to operationalize the transition toward climate-smart MSP. The framework’s core innovation lies in furnishing a scalable quantitative structure that directly links high-resolution climatological projections with operational decision-making and capital planning, thereby converting climatic uncertainty into actionable operational risk indicators. Its applicability is demonstrated via a case study of Brazil’s emergent offshore wind industry (Southeastern Marine Region), analyzing impacts under the RCP 4.5 and RCP 8.5 scenarios (using INPE-Eta/CMIP5 regional projections). The findings quantify the critical role of technological resilience as a key adaptation variable, revealing a potential reduction in operational downtime from approximately 60% to 10% by enhancing operational capacity from Standard (SWH 2.0 m) to Flexible (SWH 2.5 m). In conclusion, the results indicate that FARO is a robust decision-support instrument, effectively bridging state-of-the-art regional climate science with participatory planning to foster genuinely sustainable and resilient maritime development. Full article

Rapid urbanization has increased private vehicle usage, generating intense parking demand in congested cities like Shiraz, Iran. The spatial distribution of parking is thus critical to sustainable urban transport, as a misalignment with local demand leads to prolonged travel times, higher fuel consumption costs, and elevated pollution, thereby impeding sustainable transportation planning. In this study, we aim to develop a statistical framework to assess equity in parking distribution in an urban context and address two core questions: how parking supply correlates with local demand and what the equity implications of this distribution are. To achieve this, we employ spatial statistical methods (ANNI, Kernel Density, and Moran’s I) and correlation analysis to examine parking supply and demand across 56 districts of Shiraz. Our analysis reveals statistically significant yet weak correlations between parking capacity and demand, indicating supply-demand mismatches across city zones that result in extended search times, increased congestion, higher fuel consumption, and amplified environmental impacts, thereby perpetuating socio-economic inequities. Overall, the innovation of this article lies in integrating spatial statistical methods with supplementary analyses as a framework to evaluate parking distribution, bridging the gap between quantitative descriptive analysis and justice-based assessments in the context of parking planning in an Iranian city. Full article

Urban flooding is a major challenge to sustainable development in rapidly urbanizing cities. This study applies an integrated approach that combines Sentinel-1 SAR data, geomorphological analysis, and the DPSIR (Drivers–Pressures–State–Impacts–Responses) framework to assess the relationship between urbanization and flooding in Hanoi during the 2010–2024 period (with Sentinel-1 time-series data for 2015–2024). A time series of Sentinel-1 images (2015–2024) was processed on Google Earth Engine to detect inundation and construct a flood frequency map, which was validated against 148 field survey points (overall accuracy = 87%, Kappa = 0.79). The results show that approximately 80% of newly urbanized areas are situated on geomorphologically sensitive units, including inside- and outside-dike floodplains, fluvio-marine plains, paleochannels, and karst terrains, characterized by low elevation and high flood susceptibility. Meanwhile, about 73% of the total inundated area occurs within newly developed urban zones, primarily in western and southwestern Hanoi, where rapid expansion on flood-prone terrain has intensified hazards. The DPSIR analysis highlights rapid population growth, land use change, and inadequate drainage infrastructure as the main pressures driving both the frequency and extent of flooding. To our knowledge, this is the first study integrating geomorphology, Sentinel-1, and DPSIR for Hanoi, thereby providing robust evidence to support sustainable urban planning and climate-resilient development. Full article

Background: The management of symptomatic uterine fibroids in women of reproductive age remains a clinical challenge, with uterine preservation being a primary objective in order to safeguard fertility. To date, no clear consensus has been established in the literature regarding the optimal treatment strategy, as therapeutic choices largely depend on individual patient characteristics. In selected cases, the use of preoperative measures aimed at minimizing the risk of major intraoperative hemorrhage has been associated with an increased likelihood of adopting a more conservative surgical approach. Case presentation: We report the case of a young patient treated at our institution who presented large uterine fibroids and underwent Preoperative Uterine Artery Embolization (PUAE) before planned open myomectomy with positive outcomes. In our case, this approach provided excellent intraoperative hemostatic control, minimizing blood loss. At post-discharge follow-up, the patient showed marked symptom relief and improved quality of life. Long-term follow-up will assess sustained treatment efficacy. Conclusions: PUAE should be considered a valuable therapeutic option in patients with symptomatic uterine fibroids at high risk of surgical bleeding. When integrated into a multidisciplinary treatment plan, PUAE may enhance surgical safety, support fertility preservation, and broaden the range of conservative options available for women with complex fibroid disease. Full article

Urban neighborhoods experiencing socio-spatial pressures increasingly struggle with sustainability, especially in contexts where top-down redevelopment models dominate. In Turkey, the commonly used “demolish-and-rebuild” approach is often criticized for neglecting urban identity and the continuity of local communities. This study examines the Kükürtlü Neighborhood in Bursa, a “double-aged” area characterized by both an elderly population and aging housing stock. Using a mixed-method approach, the study integrates the EcoDistricts framework with participatory spatial analysis and Interpretative Phenomenological Analysis (IPA) to assess sustainability across three priority areas: place, health and wellbeing, and connectivity. Results reveal that while the neighborhood faces structural limitations and underutilized public spaces, it benefits from strong social sustainability rooted in cultural continuity and intergenerational bonds, especially among long-term residents. Conversely, newcomers demonstrate weaker place attachment. These findings inform a set of inclusive, aging-in-place strategies aimed at balancing physical renewal with community preservation. Building on these insights, the study proposes a context-sensitive and potentially adaptable framework to guide sustainability efforts in similar aging urban contexts. The research contributes to international discussions on urban transformation by emphasizing the importance of integrating local lived experiences with spatial planning tools, offering a model for navigating demographic and physical aging in mid-sized cities. Full article

Reducing urban pluvial flooding susceptibility requires identifying dominant variables in different regions and offering quantitative management strategies, which remains a challenge for existing methodologies. To address this, this study delves into the characteristics of SHAP’s (Shapley Additive exPlanations) local interpretability and proposes a novel and concise framework based on explainable artificial intelligence (ensemble learning-SHAP) and applies it to the central urban area of Guangzhou as a case study. The research findings are as follows: (1) This framework captures the nonlinear and threshold effects of flood drivers, identifying specific inflection points where landscape features shift from mitigating to exacerbating flooding. (2) Anthropogenic variables, specifically impervious surface density (ISD) and vegetation (kNDVI), are identified as the dominant variables driving susceptibility in urban hotspots at the grid scale. (3) The interpretability results demonstrate high stability across model iterations. Finally, based on these findings, this study provides place-based and quantitative pluvial flooding management recommendations: for areas dominated by impervious surfaces and vegetation, maintaining the impervious surface density below 0.8 and the kNDVI above 0.25 can effectively reduce the susceptibility to urban flooding. This study provides a framework for achieving place-based and quantitative flooding management and offers valuable scientific insights for flooding management, urban planning, and sustainable urban development in the central district of Guangzhou, as well as in broader developing regions. Full article