Neighborhood Scale Research Articles

Estimating ambient population density using physical features from GIS and machine learning: a study based on Japanese neighborhood

ABSTRACT This research aimed to develop an alternative method for estimating ambient population density at the neighborhood scale by utilizing a simple and universally available dataset. Physical environment data from GIS & OSM databases, basic statistics, and population density data from Mobile Spatial Statistics were combined to train tree-based Machine Learning models. The experiment resulted in an XGBoost model using 16 features capable of estimating ambient population density across three classes of outcome with 75.9% accuracy. The trained models were analyzed and visualized using SHAP and Partial Dependence Plot techniques to reveal feature importance and their threshold values. The study concludes that physical features can be effectively used as predictors of ambient population density and highlights areas for further investigation.

Impact of Microtopography and Neighborhood Effects on Individual Survival Across Life History Stages

Understanding drivers of plant community assembly and individual survival in forest ecosystems is crucial for effective conservation and management. While macro-scale factors influencing vegetation patterns are well documented, the combined impact of microtopographic variations and neighborhood effects at neighborhood scales, particularly in subtropical forests, requires further study. To contribute to this area of research, we established a 9.6 ha dynamic plot in a subtropical evergreen broad-leaved forest to examine the interplay between microtopographic factors and neighborhood effects on individual plant survival across different life stages. We conducted a comprehensive analysis of microtopographic variables and neighborhood effects, with individual plant survival censused through repeated surveys at 5-year intervals. Mixed-effects models were employed to assess the combined influence of these factors across life stages. Our results reveal that both microtopographic factors and neighborhood effects significantly influence plant survival, with their impacts varying across life stages. Water availability, represented by flow direction, emerged as a consistently critical factor throughout all life stages. Elevation and the topographic position index showed significant positive effects on survival, particularly in later life stages, possibly reflecting adaptations to light acquisition and water drainage. The influence of topographic factors intensified with succession, while the impact of neighborhood effects, particularly asymmetric competition and conspecific negative density dependence, changed as plants matured. This study enhances our understanding of forest community assembly, emphasizing the importance of considering abiotic and biotic factors across multiple scales for effective forest conservation and management. It provides insights into mechanisms driving spatial variation in community composition, crucial for preserving biodiversity in heterogeneous forest landscapes.

Psychological Understanding for Prevention of Juvenile Delinquency through Spatial Design

Children’s delinquent behaviour which is often met with rejection and misinterpretation of their immediate environment necessitates specific treatment for juveniles. The continuous rise in juvenile offences in India, particularly in crowded urban areas, has been an urgent challenge in recent years. According to the National Crime Records Bureau, 31,170 cases have been registered against juveniles in 2021, with a 4.7% increase over 2020. At the crux of such deviance is deprivation, poor-quality environment, and ignorance of its value causing adverse childhood experiences, social problems, and mental disorders. Neighbourhood design affects a person’s behaviour, directly influencing deviance, or creating a hostile communal bond with a juvenile who might eventually exhibit deviance. This study investigates the intersection of psychology, architecture, and policies regarding juvenile crime prevention at the neighbourhood scale. It explores how the built environment influences the behaviour and development of children, and how strategic design interventions can prevent juvenile delinquency. The study also examines the CPTED approach of various countries to understand the design principles that influence social behaviour. The inferences drawn are applied to understand crime preventive design strategies in Indian urban low-income neighbourhoods with higher juvenile crime rates. While CPTED focuses on general crime prevention strategies, juvenile crimes, which require a more comprehensive approach and an understanding of the root causes of future crimes, have not been delved into. Hence, this paper proposes an integrated framework that promotes holistic neighbourhood design to prevent juvenile delinquency by creating safe, inclusive communities that nurture positive youth development.

An Integrated Urban Building Energy Benchmarking Workflow to Support Urban Energy Evaluation: A Case Study of Sheffield UK

Understanding energy demand and supply flow at a large urban scale is an essential step for urban designers, planners and policymakers in investigating how buildings within an existing urban context could be designed as a whole to support the future sustainable built environment. The contemporary approach is to model energy use activities at various building and urban scales. This, albeit a practical approach, poses significant challenges in acquiring good quality data concerning buildings and their interactions at an urban scale at an affordable price. This paper presents a streamlined benchmarking methodology with a parametric modelling workflow to complement the mainstream urban building energy modelling (UBEM) approach. The proposed building energy benchmarking workflow integrates multiple databases concerning building energy consumption, energy generation and underlying grid infrastructure. Parametric modelling serves as a tool for integrating databases through the underlying sortable geometric characteristics. This is envisaged to afford stockholders, such as policymakers or urban planners, greater flexibility to investigate energy demand and supply scenarios at an urban neighbourhood scale and further explore potential applications. Using the proposed workflow, we look at renewable solar energy to experiment with offsetting urban building energy consumption through reconfiguring existing electricity microgrids in the Sheffield city centre. The result of this study demonstrates how the presented urban building energy benchmarking (UBEB) workflow would afford capabilities and flexibility to support stakeholders, e.g., urban planners, policymakers, and end-users, to better understand existing barriers and explore actionable opportunities via re-configurable electricity microgrids.

Storing Excess Solar Power in Hot Water on Household Level as Power-to-Heat System

PV technology has become widespread in the Netherlands, reaching a cumulative installed capacity of 22.4 GWp in 2023 and ranking second in the world for solar PV per capita at 1268 W/capita. Despite this growth, there is an inherent discrepancy between energy supply and demand during the day. While the netting system in the Netherlands can currently negate the economic drawbacks of this discrepancy, grid congestion and imbalanced electricity prices show that improvements are highly desirable for the sustainability of electricity grids. This research analyzes the effectiveness of a Power-to-Domestic-Hot-Water (P2DHW) system at improving the utilization of excess PV electricity in Dutch households and compares it to similar technologies. The results show that the example P2DHW system, the WaterAccu, compares favorably as a low cost and flexible solution. In particular, for twelve different households differing in size (1–6 occupants), PV capacity (2.4–8 kWp), and size of hot water storage boiler (50–300 L), it is shown that the total economic benefits for the period 2024–2032 vary from −€13 to €3055, assuming the current net metering scheme is abolished in 2027. Only for large households with low PV capacity are the benefits a little negative. Based on a multi-criteria analysis, it is found that the WaterAccu is the cheapest option compared to other storage options, such as a home battery, a heat pump boiler, and a solar boiler. A sensitivity study demonstrated that these results are overall robust. Furthermore, the WaterAccu has a positive societal impact owing to its peak shaving potential. Further research should focus on the potential of the technology to decrease grid congestion when implemented on a neighborhood scale.

WRF-HEATS coupling: Incorporating human behaviors and city topography into urban heat stress evaluation

Urban human thermal stress can be inaccurately estimated along with less-understood heat heterogeneity due to the absence of high-resolution meteorological information and realistic human behavior representation. To this end, we coupled a regional climate model (weather research and forecasting model, WRF) and a human energy balance model (human-environment adaptive thermal stress model, HEATS) to predict pedestrian's dynamic thermal stress at a neighborhood scale. The WRF-human coupling system resolves human-environment heat exchanges based on meteorological and topographical information with the consideration of dynamic human activities. The coupling system has been tested and utilized to study dynamic heat stress in a typical hot, humid, and mountainous city, Hong Kong. Our results revealed widespread heat heterogeneity with up to 7 °C difference in Physiological Subjective Temperature (PST) in the core urban area, and extreme heat exposure (up to 45 °C PST) in calm-wind zones at noon. Heat stress can be further aggregated considering realistic human behaviors such as extra clothing (e.g., protective facemask during pandemics) and physical exercise (e.g., walking along inclined terrain). Optimal-thermal-comfort routes have been designed and suggested based on the simulated neighborhood-scale heat stress map.

Investigating contestation around neighbourhood scale active travel infrastructure policy

Active travel infrastructure policy implemented at a neighbourhood scale has generated unexpected levels of socio-political contestation, leading to the removal of some schemes and widespread debates regarding equity and justice. Frequently, such contestation is framed as a discrete transport-centric phenomenon, engendering binary and objective pro-vs. anti-active travel infrastructure narratives, which obfuscate the intersection of policy with wider urban socio-spatial development dynamics. In response, this study adopts a critical urban approach to undertake a detailed investigation of contestation, through analysis of the subjective perspectives shaping contested discourses around neighbourhood scale active travel infrastructure. To achieve this, in-depth semi-structured interviews were conducted with stakeholders, using London as a case study. Our results show that divergent conceptualisations of sustainability, disparate experiences of decision-making processes, and heterogeneous socio-spatial contexts, all play a role in shaping and mediating contestation. Analysis of these themes highlights how processes of contestation are contingent upon the deployment of top-down technocratic policy. These findings reveal how current active travel infrastructure policy can further entrench, and give rise to, novel, uneven development processes. Thus, this study demonstrates the need for more transformative and strategic policy approaches, which offer truly participatory opportunities and consider active travel infrastructure within wider socio-spatial contexts.

Circularity assessment in buildings and built environment: an integrated multiscale framework

Abstract Circular transition requires systematic interventions in the built environment, particularly at the urban level, to close resource loops locally. The adoption of a design-operational approach focused on the life-cycle perspective and circularity, in line with the Green Building Approach, at the same time responds to resource scarcity and cuts CO2 emissions in the regeneration and integration of urban settlements. In this view, the dimension of the urban neighbourhood offers an ideal field of experimentation to test and scale up circular strategies and solutions, starting from the building scale. The contribution reports the results of an ongoing research whose aim is to propose a methodology to identify basic characteristics and performances allowing a neighbourhood to be defined as circular, and to promote their spread through design both in regeneration and new construction. Thus, the research addresses an important gap due to the limited number of studies on circularity metrics at the neighbourhood scale. From a methodological point of view, the research analyses a selection of case studies and, in parallel, existing circularity metrics at different levels, systematizing them with a set of indicators coming from sustainability protocols at the neighbourhood scale. The research therefore defines an integrated multiscale framework supporting circular design and assessment, valid at the building level but also - in a multiscale perspective - at the neighbourhood level, aiming to develop a support tool for public administrations and designers.

Towards integrated multi-risk reduction strategies: A catalog of flood and earthquake risk mitigation measures at the building and neighborhood scales

The integration of risk reduction measures for earthquakes and floods is a promising concept in the field of multi-hazard disaster risk reduction. However, existing studies mostly discuss it conceptually, often missing a focus on decision-making. This paper introduces a novel approach by examining synergies and trade-offs between earthquake and flood risk reduction measures. The paper first conducts a detailed analysis of selected measures for these two hazards. It then explores how these individual risk mitigation measures can be strategically integrated at the building level to maximize synergies, potentially resulting in time and cost savings. Furthermore, it discusses the limitations of current decision-making procedures for single-hazard risk mitigation selection when applied to multi-hazard risk (MHR) scenarios. To address these challenges, the study proposes new decision variables to be incorporated into existing Multi-Criteria Decision-Making frameworks with the aim of facilitating strategic risk reduction prioritization for MHR scenarios, ensuring sustainability and community resilience. To aid implementation (i.e., the phase in which the measure would be selected and tested in a series of case study buildings), a catalog of analyzed risk reduction measures is developed and provided as Supplementary Material. In future developments, this catalog will facilitate the integration of these measures into decision-support tools for evidence-based multi-hazard disaster risk reduction.

Integrating Nature-Based Solutions for urban stormwater management into existing urban fabrics

Abstract Nature-Based Solutions (NBSs) have been proven to address urban stormwater challenges effectively while providing multiple benefits to the economy, society, and environment. Urban fabrics profoundly influence flood risk as the changes in urban form, land use, and building layout will affect the urban hydrological cycle, thereby altering precipitation and runoff. However, few studies look at the connection between NBSs and urban fabrics, which can contribute to urban stormwater management. This paper aims to categorize the general types of urban fabrics and consider NBSs as strategic interventions that can improve water-related issues and help to create a resilient neighborhood. This paper elaborates on some strategic approaches to integrate NBSs in existing urban fabrics at the neighborhood scale to optimize their response capacity according to the local conditions. The novelty lies in adopting a systemic vision to deliver a design toolkit that can be adapted to different conditions and with different typologies across the places and countries facing similar water-related challenges. In conclusion, this paper emphasizes the importance of understanding how different NBSs fit various urban fabric types, and future work is needed to provide assessment tools to evaluate the efficiency of different design scenarios.

Optimization of temperature prediction algorithms and simulation of future neighborhood-scale thermal environments in Chongqing

With climate change and urbanization, predicting the outdoor thermal environment of residential areas has become increasingly crucial, particularly during extreme weather conditions. Existing studies lack a comprehensive approach to optimizing temperature prediction algorithms for Chongqing and simulating extreme thermal environments at the neighborhood scale for future decades. This study employed various algorithms, including Levenberg-Marquardt optimization, Monte Carlo simulation, ARIMA modeling, and SARIMA prediction, to simulate and forecast temperature data for the central urban area of Chongqing from 2014 to 2023. By assessing metrics such as root mean square error (RMSE), R-squared (R2), and mean absolute percentage error (MAPE), the most effective prediction algorithm was identified. Results indicate that the Levenberg-Marquardt optimization algorithm, known for its nonlinear curve fitting capabilities, demonstrated superior performance in both the test and training sets, achieving an RMSE of 0.82 °C, MAPE of 1.81 %, and R2 of 0.75. This algorithm was subsequently used to forecast the outdoor temperature trend in Chongqing from 2024 to 2050, while also simulating the outdoor wind field, temperature distribution, building surface temperatures, and wind speeds in a residential district at neighborhood scale for 2030, 2040, and 2050 at a building density of 40 %. Findings reveal that peak pedestrian-level temperatures could reach 45.62 °C, and peak roof surface temperatures could reach 93.93 °C under extreme conditions. Furthermore, the study proposes practical recommendations for building layouts and cooling strategies. These findings are expected to improve residential planning in Chongqing, enhance residents' quality of life, and provide insights for other regions facing future temperature changes.

Measuring community heatwave resilience: A comprehensive framework and tool

This article presents the first comprehensive, multi-sector heatwave resilience measurement framework and associated tool, available for use at the community or city neighbourhood scale. The question of how to live in a rapidly urbanising, climate change impacted world with more frequent and intense heatwaves is more urgent than ever. Most cities and communities around the world are critically underprepared for the growing reality of heatwaves. This paper presents the system of systems that come together to generate heatwave risk and action in which can, in-turn, support community-level heatwave resilience: features of urban heatwave risk, heatwave vulnerabilities, and heatwave governance. We then present the heatwave version of the Climate Resilience Measurement for Communities: a systems-based approach for conceptualising and measuring disaster resilience. The framework was co-designed by researchers and practitioners and is based on the most widely applied community flood resilience measurement endeavor in the world. This is, to our knowledge, the only standardized and holistic, yet globally applicable, heatwave resilience measurement framework available.

A Framework Proposal for the Developing Climate Sensitive Spatial Design Strategies: The Case of Kırklareli City Center

Climate change has emerged as a major challenge affecting urban sustainability. Increased population mobility due to social and economic factors has led to an expansion in urban density. This growth in urban space has resulted in the transformation of physical spaces into built environments lacking green areas. In the microclimate zones formed in dense urban areas, temperatures different from the current situation and thermal values that prevent the comfort level are observed. One of the most basic solutions that can prevent this temperature stress is the creation of recreational areas. In this study, the regulating effect of urban green spaces on microclimate is evaluated as a design element in urban planning. In this context, a study approach is proposed to develop climate-sensitive spatial design strategies. Micro-regions in the city center of Kırklareli are identified and comparative evaluations are made with recreation areas. The study aims to make two main contributions: (1) basic climatic conditions and problems are identified at the city and neighborhood scale, and (2) climate-sensitive spatial design strategies and recommendations are developed in urban and recreational themes.

High-resolution regional climate–CFD integrated modelling to inform climate responsive design of northern buildings in a changing climate

In permafrost regions, where climate change poses significant challenges to infrastructure stability, understanding the thermal behaviour of buildings is crucial. This study conducts a detailed investigation into the thermal performance of elevated buildings in permafrost regions within the context of a changing climate. High-resolution regional climate simulation-informed computational fluid dynamics (CFD) models were developed for northern buildings. The findings indicate that the presence of elevated buildings can disrupt the permafrost’s natural thermal equilibrium in the future. This disturbance can extend vertically and horizontally, potentially leading to altered ground temperature gradients and increased air and ground temperatures by 4.25% and 3.85%, respectively. The research findings also highlight a 12.75% reduction in wind speed beneath the study building when transitioning from the local scale (i.e., single-building) to the neighbourhood scale (i.e. with surrounding buildings). These results underscore the critical significance of exploring the neighbourhood scale in building design and planning within permafrost regions, emphasizing the need for comprehensive assessment tools to inform effective strategies and decisions. The holistic approach adopted in this study, sets out a clear vision to guide northern adaptation initiatives that address some of the climate change issues in the buildings’ design by utilizing integrated climate system-built environment modelling.

An Age-Friendly Neighbourhood Index as a Long-Term Urban Planning Decision-Making Tool

People responsible for shaping the future of cities often seek valuable tools to assist in their decision-making processes. Using objective, quantified, and analysed data proves highly beneficial when determining where to focus interventions at the city level. Various urban indexes have been established to measure different aspects of urban life, ranging from sustainability to liveability. These indexes encompass multiple dimensions of a city, including mobility and walkability, among others. The age-friendly cities initiative developed indicators for assessing the age-friendliness of cities. Some researchers further refined these indicators to focus on urban planning competencies. Building on this foundation, this article aims to present an Age-Friendly Neighbourhood Index (AFNI) validated by a panel of experts using the Delphi method. This index can serve as a valuable tool for urban planners when they need to prioritise interventions to enhance age-friendliness at neighbourhood scale. The article also outlines the necessary data and measurement techniques for these indicators. The AFNI has been applied to a real case study in the city of Santander (Spain). This application assesses the age-friendliness of various neighbourhoods in Santander, demonstrating the challenges in acquiring sub-local quality data and emphasising the need for data-driven urban management.

Analyzing the impact of planning schemes on the neighborhood-scale PM2.5 distribution through Pix2PixGAN and crowd-source data

The distribution of PM2.5 concentrations at the neighborhood scale is interfered with not only by spatial morphology, but also by spatial functions, and this effect shows heterogeneity in different urban locations due to differences in spatial dynamics. Taking the area within the Fourth Ring Road of Beijing in 2020 as an example, this paper provides urban planners with an evaluation framework for fine-grained prediction of neighborhood-scale PM2.5 distribution based on the Pix2PixGAN model and the multi-source data with crowd-source data at its core. Through the crowd-source data, the spatial functions and corresponding spatial dynamics in the neighborhood scale can be characterized in detail. Then the framework utilizes Geographically weighted poisson regression (GWPR) to screen spatial functions with significant geographic correlation with PM2.5 distribution and their heterogeneity coefficients. Based on the filtered functions, heterogeneity coefficients, and PM2.5 distribution raster, the dataset of Pix2PixGAN model is composed, and the optimal model with the most accurate PM2.5 distribution prediction is trained and selected. Finally, the paper illustrates how to analyze the qualitative and quantitative impacts of planning proposals on the distribution of PM2.5 through the optimal model, using six planning scenarios as examples.

Research on the Effects of Spatial Forms in Residential Blocks on Road Traffic Noise Distribution in Typical City of China

Integrating the block system into construction is the current trend in the development of residential areas in China. Road traffic noise is the major noise source in residential blocks, and its relationship with spatial forms of blocks remains unclear. In this study, 852 block models (258 block road network models and 594 models with buildings inside) were established and simulated with SoundPLAN 8.2 software, in order to reveal the impact of spatial forms (road network morphology, neighborhood scale, and architectural texture) on the road traffic noise distribution in residential blocks. Meantime, a prediction model based on spatial morphology parameters is proposed. It was found that (1) Without considering the impact of buildings, both the road network morphology and neighborhood scale parameters have significant effects on the distribution of road traffic noise, but road network morphology has a larger effect than neighborhood scale. (2) In the presence of buildings within the block, architectural texture parameters have effects on the distribution of road traffic noise, but to a lesser extent than road network morphology and neighborhood scale parameters. (3) This research employs principal component analysis to reduce the dimensionality of urban spatial form parameters. Subsequently, a model was developed to predict overall noise exposure levels in residential areas, which was validated by example. This model can be used as a tool for rapid prediction and diagnosis of the block acoustic environment. These findings offer insights for the planning and design of residential blocks from the perspective of optimizing the acoustic environment.

Urban mobility and air pollution at the neighbourhood scale in the Megacity of São Paulo, Brazil

Developing countries’ megacities, characterised by dense populations and socioeconomic disparities, often face high levels of pollutants, mainly from vehicle emissions. Poor air quality can lead to a range of public health problems which in turn, need to be addressed by public policies. The main goal of this article is to examine the impact of public policies and the influence of transport modes on air pollution of three districts from the Metropolitan Region of São Paulo, in Brazil: Pinheiros, Parque Dom Pedro II and Taboão da Serra. The method was held through a comparative analysis, which in turn, took into account urban indicators, urban mobility data and pollutants levels (CO and NOx). These data were collected from the 2007 and 2017 São Paulo Metrô Origin and Destination Surveys and the Air Quality Database of the Environmental Company of the State of São Paulo. As key findings, the three study areas’ pollutant concentrations presented a downward trend from 2007 to 2017 as the same time there was an increase in the public transport and non-motorized transport modes. However, it is important to highlight the confluence of the state and federal public policies occuring at the same period such as PRONCOVE, Rodoanel and the Yellow Subway Line. The identified socio-environmental disparities in the urban realm highlight the importance of localised analyses in order to reveal problems and opportunities to get a better response in terms of urban mobility and air quality. Thus, the perpetuation of constant policy’s updates and interdisciplinary collaboration is crucial.

FBDPN: CNN-Transformer hybrid feature boosting and differential pyramid network for underwater object detection

Despite advancements in underwater object detection (UOD) from optical underwater images in recent years, the task still poses significant challenges due to the chaotic underwater environment, as well as the substantial variations in scale and contour of objects. Existing deep learning-based schemes generally overlook the enhancement and refinement between multi-scale features of densely distributed underwater objects, leading to inaccurate localization and classification predictions with excessive information redundancy. To tackle the above issues, this article presents a novel feature boosting and differential pyramid network (FBDPN) for precise and efficient UOD. The salient properties of our paper are: (1) a heuristic feature pyramid network (FPN)-inspired architecture is constructed, which employs a convolutional neural network (CNN)-Transformer hybrid strategy to simultaneously facilitate the learning of multi-scale features and the capture of long-distance dependencies among pixels. (2) A neighborhood-scale feature boosting module (NSFBM) is developed to enhance contextual information between features of neighborhood scales. (3) A cross-scale feature differential module (CSFDM) is designed further to achieve effective information redundancy between features of different scales. Extensive experiments are conducted to reveal that our proposed FBDPN can outperform other state-of-the-art methods in both UOD performance and computational complexity. In addition, sufficient ablation studies are also performed to demonstrate the effectiveness of each component in our FBDPN. The source code is available at https://github.com/jixun-dmu/FBDPN.

The Nonlinear Relationship and Synergistic Effects between Built Environment and Urban Vitality at the Neighborhood Scale: A Case Study of Guangzhou’s Central Urban Area

The Nonlinear Relationship and Synergistic Effects between Built Environment and Urban Vitality at the Neighborhood Scale: A Case Study of Guangzhou’s Central Urban Area