Search Results (1,483)

The regionalization of input–output tables enables a granular understanding of economic systems, allowing for interregional and interindustry analysis for goods and services in a local economy. This paper details the construction of an intermunicipal IO matrix for the state of Rio Grande do Sul (Brazil), a region marked by both economic diversification and significant territorial disparities. Using the 16-sector state IO matrix (base year 2019) provided by the state-level treasury (SEFAZ-RS) as a starting point, we adapt the Interregional Input–Output Adjustment System (IIOAS), integrating gravity-based trade modelling and RAS balancing, to produce a disaggregated structure for 497 municipalities. The regionalization follows three main steps: (i) generation of an initial matrix assuming proportional municipal shares in sectoral supply and demand; (ii) iterative RAS-based adjustments to align with municipal and state-level constraints; and (iii) incorporation of complementary municipal data—including employment, GDP, household consumption, and exports—to refine final demand and value-added allocations. The results demonstrate the feasibility of deriving spatially intermunicipal IO structures from limited data. The results show that, while industrial and service activities are concentrated around the Porto Alegre metropolitan area, rural subregions remain specialized in low value-added primary sectors. Full article

Mountainous urban areas like Guiyang face unique fire safety challenges due to rugged terrain and complex road networks, which hinder fire station accessibility. This study proposes a GIS-based framework that integrates nighttime light (NPP/VIIRS) and point of interest (POI) data to assess fire risk and accessibility. Kernel density estimation quantified POI distributions across four risk categories, and the Spatial Appraisal and Valuation of Environment and Ecosystems (SAVEE) model combined these with NPP/VIIRS data to generate a composite fire risk map. Accessibility was evaluated using the enhanced two-step floating catchment area (E2SFCA) method with road network travel times; 80.13% of demand units were covered within the five-minute threshold, while 53.25% of all units exhibited low accessibility. Spatial autocorrelation analysis (Moran’s I) revealed clustered high risk in central basins and service gaps on surrounding hills, reflecting the dominant influence of terrain alongside protected forests and farmlands. The results indicate that targeted road upgrades and station relocations can improve fire service coverage. The approach is scalable and supports more equitable emergency response in mountainous settings. Full article

Due to the increasing demand for accurate and robust GNSS positioning for location-based services (LBS) in urban regions, the impacts prevalent in metropolitan areas, like multipath reflections and various interferences, have become persistent challenges. Consequently, developing effective strategies to address these sophisticated influences has become both a primary research focus and a shared priority. In this paper, the authors explore an approach to identify and mitigate the drawbacks arising from multipath effects in urban positioning. Unlike conventional ways for building complex models, an adaptive data-driven methodology is proposed to identify the fingerprints of a multipath in GNSS observations. This approach utilizes the Fourier transform (FT) to examine code multipath and other error sources in terms of frequency, as represented by the power spectrum. Wavelet decomposition and signal spectrum methods are subsequently applied to seek traces of code multipath in multilayer decompositions. Based on the exhibited multipath features, the impacts of multipath in GNSS observations are detected and mitigated in the reconstructed observations. The proposed method is validated for both static and dynamic positioning scenarios, demonstrating seamless integration with existing positioning models. The feasibility has been verified through a series of experiments and tests under urban environments using navigation terminals and smartphones. Full article

The growing demographic trend of an aging population, particularly in remote rural areas, exacerbates social isolation and limits access to essential goods and services. This vulnerability highlights a pressing need to develop sustainable solutions for their mobility and support. Using Geographic Information Systems (GISs) and network analysis, a workflow was developed to optimize road-based transport for the elderly. The analysis utilized an electric vehicle, with its range limitations, influenced by road slopes, being a critical variable for assessing route efficiency. Two potential solutions were investigated: (1) the delivery of goods and medicines and (2) the transport of passengers and medicines. The methodology was tested using the Municipality of Seia, Portugal, as a case study, with a defined weekly visit frequency. The results demonstrate that both proposed solutions are technically viable for implementation, with the transport of passengers and medicines being the most effective option. This study provides a foundational framework for developing practical, demand-oriented, sustainable transport and logistics services to support isolated elderly populations. Full article

Cultural ecosystem services (CES) play a key role in the sustainable development of rural areas—yet they remain poorly quantified in planning practice. This study examines the relationship between the supply and demand of CES provided by various types of Ecological Focus Areas (EFAs) in a rural landscape, using the municipality of Sosnowica (eastern Poland) as a case study. Landscapes such as forests, agricultural land, wetlands, and inland waters were evaluated using a set of biophysical and socio-economic indicators that reflect both their potential (supply) and actual use (demand) in terms of services such as recreation, landscape aesthetics, and cultural heritage. The findings reveal significant spatial disparities between CES supply and demand: forests and inland waters exhibit the highest supply potential, while agricultural land shows untapped opportunities in tourism and recreation. Wetlands, in particular, face notable service deficits—highlighting the need for targeted infrastructure and management interventions. Statistical analyses (Pearson correlation, Kruskal–Wallis test, Tukey HSD test) confirmed that the key factors shaping CES are accessibility and environmental attractiveness. The results indicate that CES mapping is a valuable tool for supporting sustainable rural planning, reinforcing local identity, counteracting depopulation, and stimulating socio-economic development. Full article

China has entered a period of urban renewal, with the focus shifting from large-scale incremental construction to both upgrading existing building quality and adjusting incremental structures. There are three main types of urban renewal: demolition and reconstruction, comprehensive improvement, and organic renewal. The latter systematically optimizes and enhances urban functions, spaces, and culture through gradual renovation methods and is, therefore, suitable for use in ancient cities. To promote organic renewal, the problem of limited space resources must first be addressed, which can be resolved to a certain extent by the moderate development of underground spaces; preliminary evaluations of the development potential are also required. In consideration of the demands of organic renewal, we constructed a novel indicator system for evaluating underground space development potential (USDP) in ancient cities that assesses two dimensions: development demand and development suitability. A multi-factor comprehensive evaluation method was adopted to quantify the indicators of USDP, taking Shaoxing Ancient City (SAC) as the case study. According to the USDP evaluation, SAC can be divided into four kinds of areas: high-potential, general-potential, low-potential, and prohibited development areas. High-potential areas accounted for 16.38% of the total evaluation area and were primarily concentrated in or near key locations: train transit stations (Shaoxing Railway Station), public service facilities, evacuated land, and cultural and tourism facilities around historic districts (Shusheng Guli Historical and Cultural Street). The proposed development strategies for these areas included the interconnection of metro stations, redevelopment of relocation-related and vacated land, construction of underground cultural corridors, and supplementation of parking facilities. For developed underground spaces with low utilization efficiency, functional renewal and management improvement measures were put forward. Our method of evaluating the USDP of ancient cities and the strategies proposed to optimize the utilization of underground space can provide reference examples for SAC and other similar ancient cities. Full article

With the rapid urban aging trend in China, evaluating the age-friendliness of street environments is critical for inclusive urban planning. This study proposes the Age-Friendly Environment Assessment Tool (AFEAT) to assess street-level age-friendliness in high-density urban contexts, grounded in the World Health Organization’s (WHO) Global Age-Friendly Cities: A Guide and adapted to the spatial characteristics of Nanjing’s Qinhuai District. By integrating multi-source data such as street-view image segmentation, Point of Interest (POI)-based network accessibility, kernel density estimation, Analytic Hierarchy Process (AHP)-derived indicator weights, and Random Forest regression, the study develops a comprehensive and spatialized evaluation framework. The results reveal significant spatial disparities in age-friendliness across street segments, with Safe Mobility, Healthcare Services, and Walkable Environment identified as the most influential factors for older adults. High-performing areas are concentrated in the central urban core, while peripheral zones face challenges such as poor walkability, insufficient lighting, and a lack of facilities. The study recommends strengthening a walkability-based age-friendly safety and healthcare support system and optimizing the spatial distribution of recreational and medical facilities to address mismatches between supply and demand. These findings provide practical guidance for targeted, evidence-based interventions aimed at fostering equitable and resilient urban environments for aging populations. Full article

Partial Differential Equation (PDE)-based hydrologic models demand extensive preprocessing, creating a bottleneck and slowing down the model setup process. Mesh generation typically lacks integration with hydrological features like river networks. We present GHOST Mesh (GMesh), an automated, watershed-oriented mesh generator built within the Watershed Modeling Framework (WMF), to address this. While primarily designed for the GHOST hydrological model, GMesh’s functionalities can be adapted for other models. GMesh enables rapid mesh generation in Python by incorporating Digital Elevation Models (DEMs), flow direction maps, network topology, and online services. The software creates Voronoi polygons that maintain connectivity between river segments and surrounding hillslopes, ensuring accurate surface–subsurface interaction representation. Key features include customizable mesh generation and variable refinement to target specific watershed areas. We applied GMesh to Iowa’s Bear Creek watershed, generating meshes from 10,000 to 30,000 elements and analyzing their effects on simulated stream flows. Results show that higher mesh resolutions enhance peak flow predictions and reduce response time discrepancies, while local refinements improve model performance with minimal additional computation. GMesh’s open-source nature streamlines mesh generation, offering researchers an efficient solution for hydrological analysis and model configuration testing. Full article

Under the dual backdrop of the Healthy China strategy and the concept of sustainable development, optimizing the spatial layout of primary healthcare facilities is important for fairly distributing healthcare resources and strengthening the resilience of the public health system in a sustainable way. This study introduces an innovative 3D spatial resilience evaluation framework, covering transmission (service accessibility), diversity (facility type matching), and stability (supply demand balance). Unlike traditional accessibility studies, the concept of “resilience” here highlights a system’s ability to adapt to sudden public health events through spatial reorganization, contrasting sharply with vulnerable systems that lack resilience. Method-wise, the study uses an improved Gaussian two-step floating catchment area method (Ga2SFCA) to measure spatial accessibility, applies a geographically weighted regression model (GWR) to analyze spatial heterogeneity factors, combines network analysis tools to assess service coverage efficiency, and uses spatial overlay analysis to identify areas with supply demand imbalances. Harbin is located in northeastern China and is the capital of Heilongjiang Province. Since Harbin is a typical central city in the northeast region, with a large population and clear regional differences, it was chosen as the case study. The case study in Harbin’s main urban area shows clear spatial differences in medical accessibility. Daoli, Nangang, and Xiangfang form a highly accessible cluster, while Songbei and Daowai show clear service gaps. The GWR model reveals that population density and facility density are key factors driving differences in service accessibility. LISA cluster analysis identifies two typical hot spots with supply demand imbalances: northern Xiangfang and southern Songbei. Finally, based on these findings, recommendations are made to increase appropriate-level medical facilities, offering useful insights for fine-tuning the spatial layout of basic healthcare facilities in similar large cities. Full article

Under the accelerating demographic aging trend, the rational allocation of elderly care facilities has emerged as a critical challenge. Although existing studies have investigated elderly care facilities planning using conventional methods, they frequently overlook the nonlinear interactions between built environment factors and heterogeneous demands across different elderly care facility types. This study addresses these gaps by proposing a data-driven framework that integrates machine learning with spatial analysis to optimize elderly care facility distribution in Xi’an City central area, Shaanxi Province, China. Leveraging multi-source datasets encompassing points of interest (POIs), road networks, and demographic statistics, we classify facilities into three categories (service-oriented, activity-oriented, and care-oriented) and employ an XGBoost model with SHAP interpretability to evaluate spatial distributions and influencing factors. The results demonstrate that the XGBoost model outperforms comparative algorithms (Random Forest, CatBoost, LightGBM) with superior performance metrics (accuracy rate of 97%, precision of 95%, and F1-score of 90%), effectively capturing nonlinear thresholds effects. Key findings reveal the following: (1) Accessibility and road density exert threshold effects on care-oriented facilities, with facility attractiveness saturating when these values exceed 6; (2) Land use intensity and medical resources positively correlate with activity-oriented facilities, while excessive retail density inhibits their distribution; (3) Service-oriented facilities thrive in areas with balanced accessibility and moderate commercial diversity. Spatial analysis identifies clustered distribution patterns in urban core areas contrasted with peripheral deficiencies, indicating need for targeted interventions. This research contributes a scalable methodology for equitable facility planning, emphasizing the integration of dynamic built environment variations with model interpretability. The framework provides significant implications for formulating age-friendly urban policies applicable to global cities undergoing rapid urbanization and population aging. Full article

The rapid growth of the aging population, alongside functional decline and more older adults living independently, has increased demand for age-friendly infrastructure and walkable communities. This study proposes a quantitative framework to assess how multi-scale built environments influence older adults’ walkability, addressing the scarcity of scalable and interpretable models in age-friendly urban research. By combining the cumulative opportunity method, street-scene semantic segmentation, XGBoost, and GeoSHapley-based spatial effect analysis, the study finds that (1) significant spatial disparities in walkability exist in Xiamen’s central urban area. Over half of the communities (54.46%) failed to meet the minimum threshold (20 points) within the 15 min community life circle (15-min CLC), indicating inadequate infrastructure. The primary issue is low coverage of older adults’ welfare facilities (only 16.26% of communities are within a 15 min walk). Despite renovations in Jinhu Community, walkability remains low, highlighting persistent disparities. (2) Communities with abundant green space are predominantly newly developed areas (64.06%). However, these areas provide fewer facilities on average (2.3) than older communities (5.7), resulting in a “green space–service mismatch”, where visually appealing environments lack essential services. (3) Human perception variables such as safety, traffic flow, and closure positively influence walkability, while visual complexity, heat risk, exposure, and greenness have negative effects. (4) There is a clear supply and demand mismatch. Central districts combine high walkability with substantial older adults’ service demand. Newly built residential areas in the periphery and north have low density and insufficient pedestrian facilities. They fail to meet daily accessibility needs, revealing delays in age-friendly development. This framework, integrating nonlinear modeling and spatial analysis, reveals spatial non-stationarity and optimal thresholds in how the built environment influences walkability. Beyond methodological contributions, this study offers guidance for planners and policymakers to optimize infrastructure allocation, promote equitable, age-friendly cities, and enhance the health and wellbeing of older residents. Full article

Supplementary cementitious materials (SCMs) provide a practical solution for reducing greenhouse gas emissions associated with Portland cement production while enhancing the economy, performance, and service life of concrete and mortar. Currently, there is a significant disparity in the availability, supply, and utilisation levels of SCMs worldwide, particularly in South Africa. This paper presents an in-depth analysis of the characteristics and performance of various SCMs, including local availability, factors driving demand, production, and utilisation. The findings indicate that fly ash and limestone calcined clay are the most widely available SCM resources in South Africa, with deposits exceeding 1 billion tonnes each. Fly ash stockpiles continuously increase due to the reliance on coal-fired power plants for 85% of generated electricity and a low fly ash utilisation rate of 7%, significantly below international utilisation levels of 10–98%. Conversely, slag resources are depleting due to the steady decline of local steel production caused by energy and input costs, alongside the growing importation of steel products. Combined, the estimated production of slag and silica fume is about 1.4 million tonnes per annum, leading to their limited availability and utilisation in niche applications such as high-performance concrete and marine environments. Furthermore, 216,450 tonnes of SCM could potentially be processed annually from agricultural waste. In addition to quality, logistics, costs, and other challenges, this quantity can only replace 1.5% of clinker in South Africa, raising concerns about the viability of SCMs from agricultural waste. Based on its findings, this study recommends future research areas to enhance the performance, future availability, and sustainability of SCMs. Full article

Urban blue-green infrastructure (UBGI) has been recognized as an effective nature-based solution (NbS) for mitigating urban overheating through temperature reduction. However, there is a paucity of research examining whether UBGI spatial configurations align with the geographical distribution of the heat exposure risks of urban residents. This study focuses on this research gap, employing a population-weighted algorithm to conduct a refined assessment of the blue-green spaces exposure and heat exposure risks of urban residents. Then, the heat exposure risk was conceptualized as the demand for cooling services, with exposure to blue-green spaces serving as the supply. A comprehensive assessment was finally conducted of the supply–demand relationship and coupling coordination level for cooling services in central Wuhan. The following findings were revealed: (1) Both heat exposure risks and blue-green exposure demonstrate distinct “west high–east low” spatial gradients. It is evident that extreme high/high-risk zones, which encompass 17.1% of the study area, house 74.49% of the permanent population; (2) A substantial and pervasive positive correlation exists between UGBI exposure and the heat exposure risk. “High-demand–high-supply” areas (14.90% coverage) concentrate in urban cores, overlapping with 61.25% high-risk populations, while 0.29% of zones show “high-demand–low-supply” mismatches, revealing concentrated but ineffective UGBI distribution; (3) A pervasive supply–demand imbalance is evident, with 90.64% of regions exhibiting an unacceptable coupling type range (0 < D ≤ 0.4) and a mere 1.39% attaining an acceptable range (0.6 < D ≤ 1). These findings underscore the inadequacy of prevailing urban blue-green infrastructure configurations in addressing heat exposure risks. The construction of cities with greater heat resilience necessitates the implementation of multidimensional strategies aimed at risk mitigation. Full article

With the acceleration of global population aging, rural areas face particularly severe challenges due to youth outmigration and uneven resource distribution. Taking Jiashan Village in Wuhan as a case study, this research combines the planning–activity model of new time–geography with Maslow’s hierarchy of needs to investigate the behavioral and emotional characteristics of the elderly and their spatial adaptation requirements. Using GPS tracking of 30 participants, questionnaires (152 valid responses; 73.4% response rate), facial expression recognition, and the stated preference (SP) method, the study classified elderly lifestyles into four types: leisure-oriented, agricultural-labor-oriented, caregiving-oriented, and self-employment-oriented. The results show significant heterogeneity in spatial needs, social intensity, and emotional responses. A quantitative analysis using the multinomial logit model indicates that farmland optimization had the greatest positive utility (+1.5873), followed by the addition of new plazas and leisure facilities, both significantly enhancing satisfaction. A correlation analysis further revealed that prolonged use of farmland, parks, and walking paths was negatively correlated with satisfaction, underscoring the urgency of targeted renovations. On this basis, the study proposes a three-tiered demand framework of “local service–social interaction–personal value”, offering both theoretical support and practical strategies for multi-level and collaborative retrofitting of suburban rural public spaces, aiming to mitigate “aging depression” and promote urban–rural integration. Full article

The wide adoption of environmentally friendly solutions for transportation, such as Electric Vehicles (EVs), is crucial to reducing greenhouse gases and mitigate the effects of climate change. To meet the growing demand of EVs, enough Charging Stations (CSs) must be deployed. In this study, the Ultra-Fast Charging (UFC) technology is investigated, and a method is proposed to locate the minimum indispensable UFC infrastructure to enable a nationwide travel, considering both infrastructure costs and power losses. To address the location problem, first the average electric range of the EVs currently on the market is analyzed to estimate the maximum allowable distance between two consecutive CS. In the assessment of the driving range all the factors which influence the energy consumption are considered. The CSs are then located within the existing Service Areas (SAs) to save infrastructure costs while meeting the maximum distance constraint between charging stations. Then, a cost comparison is performed between the economic impact of power losses and the savings from reduced infrastructure costs. The methodology is applied to the Italian highway network. Results show that installing charging infrastructure within existing SAs is more cost-effective than placing them near Medium Voltage (MV) cabins. Full article