Building Height Research Articles

Assessment of Health-Oriented Layout and Perceived Density in High-Density Public Residential Areas: A Case Study of Shenzhen

Rapid urbanization has intensified public housing development and building density, posing significant challenges to residents’ well-being and urban sustainability. With the population of the Greater Bay Area on the rise, enhancing the spatial quality of public housing is now essential. The study proposed a quantitative framework to evaluate the relationship between the residential design elements and perceived density in high-density public housing neighborhoods. It employed a virtual reality perception experiment to analyze the relationship between significant spatial indicators and perceived density by investigating 16 high-density residential layout models in 3 configurations: Tower-Enclosed, Balanced Slab-Enclosed, and Staggered Slab-Enclosed. The results indicate that: (1) greater building height intensifies perceived density, leading to sensations of overcrowding and discomfort; (2) an increased sky ratio mitigates perceived density, fostering a more open and pleasant environment; (3) recessed residential facades enhance residents’ density perception; and (4) Staggered Slab-Enclosed Layout configurations receive the most favorable evaluations regarding perceived density. The authors attempt to go beyond current regulations to propose tailored solutions for Shenzhen’s high-density context, improving spatial efficiency and residential comfort in future public housing designs. The finding provides scientific evidence to support urban planners and policymakers in developing more resilient and sustainable high-density neighborhoods.

Influence of Urban Morphologies on the Effective Mean Age of Air at Pedestrian Level and Mass Transport Within Urban Canopy Layer

This study adapted the mean age of air, a time scale widely utilized in evaluating indoor ventilation, to assess the impact of building layouts on urban ventilation capacity. To distinguish it from its applications in enclosed indoor environments, the adapted index was termed the effective mean age of air (τ¯E). Based on an experimentally validated method, computational fluid dynamic (CFD) simulations were performed for parametric studies on four generic parameters that describe urban morphologies, including building height, building density, and variations in the heights or frontal areas of adjacent buildings. At the breathing level (z = 1.7 m), the results indicated three distinct distribution patterns of insufficiently ventilated areas: within recirculation zones behind buildings, in the downstream sections of the main road, or within recirculation zones near lateral facades. The spatial heterogeneity of ventilation capacity was emphasized through the statistical distributions of τ¯E. In most cases, convective transport dominates the purging process for the whole canopy zone, while turbulent transport prevails for the pedestrian zone. Additionally, comparisons with a reference case simulating an open area highlighted the dual effects of buildings on urban ventilation, notably through the enhanced dilution promoted by the helical flows between buildings. This study also serves as a preliminary CFD practice utilizing τ¯E with the homogenous emission method, and demonstrates its capability for assessing urban ventilation potential in urban planning.

Investigation into the Mechanism of the Impact of Sunlight Exposure Area of Urban Artificial Structures and Human Activities on Land Surface Temperature Based on Point of Interest Data

With rapid urbanization, the urban heat island (UHI) effect has intensified, posing challenges to human health and ecosystems. This study explores the impact of sunlight exposure areas of artificial structures and human activities on land surface temperature (LST) in Hefei and Xuzhou, using Landsat 9 data, Google imagery, nighttime light data, and Point of Interest (POI) data. Building shadow distributions and urban road surface areas were derived, and geospatial analysis methods were applied to assess their impact on LST. The results indicate that the sunlight exposure areas of roofs and roads are the primary factors affecting LST, with a more pronounced effect in Xuzhou, while anthropogenic heat plays a more prominent role in Hefei. The influence of sunlight exposure on building facades is relatively weak, and population density shows a limited impact on LST. The geographical detector model reveals that interactions between roof and road sunlight exposure and anthropogenic heat are key drivers of LST increases. Based on these findings, urban planning should focus on optimizing building layouts and heights, enhancing greening on roofs and roads, and reducing the sunlight exposure areas of artificial structures. Additionally, strategically utilizing building shadows and minimizing anthropogenic heat emissions can help lower local temperatures and improve the urban thermal environment.

Automated Estimation of Building Heights with ICESat-2 and GEDI LiDAR Altimeter and Building Footprints: The Case of New York City and Los Angeles

Accurate estimation of building height is crucial for urban aesthetics and urban planning as it enables an accurate calculation of the shadow period, the effective management of urban energy consumption, and thorough investigation of regional climatic patterns and human-environment interactions. Although three-dimensional (3D) cadastral data, ground measurements (total station, Global Positioning System (GPS), ground laser scanning) and air-based (such as Unmanned Aerial Vehicle—UAV) measurement methods are used to determine building heights, more comprehensive and advanced techniques need to be used in large-scale studies, such as in cities or countries. Although satellite-based altimetry data, such as Ice, Cloud and land Elevation Satellite (ICESat-2) and Global Ecosystem Dynamics Investigation (GEDI), provide important information on building heights due to their high vertical accuracy, it is often difficult to distinguish between building photons and other objects. To overcome this challenge, a self-adaptive method with minimal data is proposed. Using building photons from ICESat-2 and GEDI data and building footprints from the New York City (NYC) and Los Angeles (LA) open data platform, the heights of 50,654 buildings in NYC and 84,045 buildings in LA were estimated. As a result of the study, root mean square error (RMSE) 8.28 m and mean absolute error (MAE) 6.24 m were obtained for NYC. In addition, 46% of the buildings had an RMSE of less than 5 m and 7% less than 1 m. In LA data, the RMSE and MAE were 6.42 m and 4.66 m, respectively. It was less than 5 m in 67% of the buildings and less than 1 m in 7%. However, ICESat-2 data had a better RMSE than GEDI data. Nevertheless, combining the two data provided the advantage of detecting more building heights. This study highlights the importance of using minimum data for determining urban-scale building heights. Moreover, continuous monitoring of urban alterations using satellite altimetry data would provide more effective energy consumption assessment and management.

Establishing the relationship between building height and foundation depth

Establishing the relationship between building height and foundation depth

Street trees: The contribution of latent heat flux to cooling dense urban areas

Trees are the most important natural factor to alleviate the urban heat island effect and the latent heat flux (LE) they release contributes significantly to urban cooling. In this study, the model ENVI-met was used to study the influence of building geometry on the LE exchanged by trees at the block scale in compact urban areas. The building density (BD), building height (BH) and sky view factor (SVF) were used to characterize building geometry. The sensitivity of LE to building geometry was estimated by multi-linear regression analysis. The following conclusions were drawn:(1) the LE of trees is sensitive to building geometry, higher during daytime than night-time in winter and the higher during night-time than daytime in summer; (2) LE changes as expected across the seasons, with LE larger in summer; (3) The shade affects the LE of a tree by influencing the solar irradiance; (4) In winter the average LE of a single tree is larger with 0.06 than 0.12 fractional vegetation cover (FVC). This study can provide useful leads towards further research to explore latent heat exchanges by trees at the street scale.

Punching Shear Capacity of RC Flat Slabs with Steel and Superelastic Ni-Ti Shape Memory Shear Reinforcement under Repeated Loads

Flat slab systems are a popular choice among engineers because of their numerous advantages, such as reduced building height, flexibility in spatial layout by eliminating the need for beams, and cost savings. However, Brittle slab failure under punching shear presents a considerable challenge. The primary objective of this study was to examine how flat slabs respond to PS and conduct an experiment using steel and superelastic Ni-Ti shape memory alloy (SMA) bars as shear reinforcement to assess their effectiveness in improving the PS capacity of flat slab-column connections under vertical Repeated load. Nine half-scale samples were tested, consisting of 1100 × 1100 × 120 mm slabs with a protruding column from one side of 150 × 150 mm and 400 mm height. The factors considered in this research were the type of materials, spacing between stirrups, stabilization method, and inner RFT. After that, finite element analysis by using ABAQUS 6.14 was developed to simulate all the tested specimens. The finite element analysis showed identical results compared to the experimental ones concerning energy absorption, load capacity, absorbed energy, and model stiffness. According to the experimental and finite element analysis findings, the flat slab reinforced with inclined stirrups exhibited a significant increase in punching strength, ranging from 28.8% to 51.3% compared with the control specimen. The stiffness increases by 8.5% when the distance between stirrups is reduced to 0.5d, and inclined-shaped memory alloy stirrups are employed.

Exploring the influence of block environmental characteristics on land surface temperature and its spatial heterogeneity for a high-density city

A fundamental understanding of the spatial change trends and driving mechanisms of land surface temperature (LST) under urbanization is a prerequisite for the development of effective strategies to mitigate the urban heat island effect. In this study, the built-up blocks of Shenzhen, a high-density city in China, were selected as the unit of analysis. Multi-source datasets were utilized to calculate a total of 44 environmental characteristic indicators, covering four categories. In order to comprehensively analyze the influence of each environmental feature indicator on LST and spatial heterogeneity, MLR, XGBoost and MGWR models were constructed. Furthermore, the nonlinear relationship between the variables was investigated using the SHAP method. The results demonstrated that the predictive efficacy of the MGWR and XGBoost models was markedly superior to that of the MLR model. The percentage cover of forest, the average elevation, NDVI, the frontal area index and the standard deviation of building height were identified as the primary determinants of the LST. These factors account for more than 52% to the explanation of the LST distribution. The effects of the majority of landscape pattern, building form and street view indicators on LST exhibited spatial heterogeneity. Furthermore, the indicators also showed nonlinear patterns and threshold effects on LST. The findings offer valuable insights for enhancing the urban thermal environment, particularly in high-density urban areas.

Towards Resilient Communities: Evaluating the Nonlinear Impact of the Built Environment on COVID-19 Transmission Risk in Residential Areas

Reflections on urban epidemics often drive improvements in the resilience of the built environment. However, the assessment regarding the nonlinear influence of the community environment on the spread of Corona Virus Disease 2019 (COVID-19) is inadequate. This study analyzed the influential mechanism of built environment factors on the epidemic risk in residential areas, using Shanghai as a case study. During the lockdown in April 2022, Shanghai reported daily data on COVID-19 outbreaks in residential areas, amounting to a total of 90,323 entries. Based on a GIS-based grid analysis approach, we employed a Random Forest (RF) model and a Multiscale Geographically Weighted Regression (MGWR) model to investigate the marginal effects and spatial heterogeneity of environmental factors on the mean count of COVID-19 outbreak days (MC) in residential areas within each grid zone. The results show that the value of MC forms a ring-mountain distribution surrounding the city's outer ring road. The RF model (R² = 0.57) demonstrates that the house price, population density, family number, and the standard deviation of building height (BH_SD) significantly correlated with MC, with the relative importance of 25%, 13%, 11%, and 6%, respectively. The MGWR model (R² = 0.63) highlights the spatial heterogeneity of family number, house age, house price, property fee, and delivery density. We also found that property fee and green rate were negatively correlated with the MC. These findings help improve responses to public health emergencies and create more resilient communities to cope with pandemics.

Research on 3D Model Calculation of Green and low-carbon New Buildings

Due to the widespread use of solid clay bricks in building houses in China, the annual destruction of farmland by burning bricks amounts to about 100000 acres. Faced with these problems, China has an extremely urgent demand for green and low-carbon buildings. Therefore, this article conducts computational research on the 3D model of a new type of green and low-carbon building. Due to the significant differences in the geometric form and texture representation of a large number of green and low-carbonl new buildings, it is difficult to uniformly quantify their level of detail. This article considers the usefulness and accessibility of 3D model calculation data separately. The shadow length is generally the distance from the selected building's facade roof to the end of the shadow, which can avoid the influence of building shape on its length. The determination of these two points and the calculation of the distance between them will directly affect the accuracy of shadow length calculation. Therefore, when users need to add an application subsystem to the system, they must add information such as the input and output data structures of the subsystem to the module. The height information calculation method uses the building and shadow imaging geometric modeling to calculate the building height by establishing the relationship between the shadow length and the corresponding building height.

Analysis of Soil-Structure Interaction of Framed Structure

This study examines the soil-structure interaction (SSI) effects on the seismic behavior of G+7 and G+12 reinforced concrete buildings. Using finite element modelling in SAP2000, we assess key seismic parameters, including base shear, time period, lateral displacement, and footing settlement, across three soil types: soft, medium, and hard. This comparative analysis provides insights into how building height and soil flexibility influence structural stability, suggesting optimal design considerations for enhancing earthquake resilience. Key Words: Soil-Structure Interaction (SSI), Base Shear, Lateral Displacement, Seismic Analysis, G+7, G+12, SAP2000, Soft Soil, Medium Soil, Hard Soil.

Plant responses to urban gradients: Extinction, plasticity, adaptation

Abstract Biodiversity‐oriented urban management and planning require information on the drivers of wildlife composition and ecosystem function within cities. Urban landscapes impose environmental gradients along which species may be filtered away, or respond by showing adaptive variation in functional trait values. Such trait variation may in turn be due to a species' phenotypic plasticity, or a consequence of microevolution leading to local adaptation. This study investigates three possible plant responses to urban environmental gradients, with different evolutionary consequences: extinction, plasticity and adaptation. We assessed whether individual functional traits (LMA—leaf mass per area, plant height and flower length), population performance traits (seed mass and germination rate), as well as species frequency in the plant community, responded to gradients in mowing frequency, soil fertility and structure, temperature and surrounding mean building height, among four herbaceous plant species present in the metropolitan area of Strasbourg. Using a common garden experiment, we tested whether the observed trait variation was hereditary, and may thus constitute evidence for local adaptation. Our results detected the three types of expected responses. Plantago lanceolata is plastic to urban gradients, and Trifolium pratense showed both plastic and hereditary responses. Dactylis glomerata and Medicago lupulina showed all three responses: they both declined under increasing mowing frequency, were plastic to surrounding mean building height, and showed hereditary responses to different urban gradients. Urban management and planning therefore impact on the evolutionary capabilities of plants in cities. In the case of management this is highlighted by the detected trends in species' traits and frequency in response to mowing. The consequences of urban planning are evidenced by mean building height eliciting most often plastic and adaptive responses. Synthesis. Herbaceous plants often change their morphology in response to urban conditions: grass cutting, altered soils, warmer temperatures and being surrounded by tightly packed buildings. These changes are sometimes hereditary, which suggests that city management and planning affect the ability of plants to survive and evolve in urban environments.

Urban Canopy Parameters’ Computation and Evaluation in an Indian Context Using Multi-Platform Remote Sensing Data

Urban Canopy Parameters (UCPs) are crucial for urban microclimate modeling; however, the scarce availability of precise UCP data in developing regions limits their application for urban climates. This study investigated the use of multi-platform remote sensing data viz. very high-resolution satellite (VHRS) optical stereo and Unmanned Aerial Vehicle (UAV) datasets for the computation of UCPs in high-density urban scenarios in India, with varied development characteristics. The results demonstrated high accuracy in terms of building height and footprint extraction from both datasets, key inputs for UCP computation. However, UCPs from UAV data have displayed relatively high accuracy for building footprints (86%), building height (RMSE ~ 0.05 m), and land use/land cover classification (90%). Performance evaluation of computed UCPs against a 3D reference geodatabase showed high prediction accuracy for most UCPs, with overall biases, mean absolute error, and root-mean-square error values significantly better than 1 m, with strong correlation (0.8–0.9). It was concluded that VHRS optical stereo and UAV datasets offer a secure, reliable, and accurate solution for UCP computation in urban areas, particularly in developing regions. These findings have significant implications for urban climate research and the sustainable development of rapidly urbanizing areas facing resource and policy constraints.

A Calculating Method for the Height of Multi-Type Buildings Based on 3D Point Cloud

Building height is a critical variable in urban studies, and the automated acquisition of the precise building height is essential for intelligent construction, safety, and the sustainable development of cities. The building height is often approximated by the building’s highest point. However, the calculation method of the building height of the various roof types differs according to building codes, making it challenging to accurately calculate the height of buildings with complex roof structures or multiple upper appendages. Consequently, this paper utilizes point clouds to propose an automated method for calculating building heights conforming to design codes. The model considers roof types and allows for fast, automated, and highly accurate building height estimation. First, roofs are extracted from the point cloud by combining normal vector density clustering with a region-growing algorithm. Second, combined with variational Bayes, a Gaussian mixture model is employed to segment the roof surfaces. Finally, roofs are classified based on slope characteristics, achieving the automatic acquisition of building heights for various roof types over large areas. Experiments were conducted on Vaihingen and STPLS3D datasets. In the Vaihingen area, the maximum error, root-mean-square-error (RMSE), and mean absolute error (MAE) of the measured heights are 1.92 cm, 1.18 cm, and 1.13 cm, respectively. In the STPLS3D area, these values are 1.79 cm, 0.82 cm, and 0.68 cm, respectively. The results demonstrate that the proposed method is reliable and effective, which offers valuable data for the development, construction, and planning of three-dimensional (3D) cities.

Expeditious numerical capacity assessment in precast structures via inelastic performance-based spectra

The seismic design of precast structures hinges on unique characteristics intrinsic to precast technology. Emphasis is placed on lightweight structural elements for efficient on-site assembly and cost reduction. This leads to increased slenderness in beams and columns compared to traditional cast-in-situ constructions, accentuating the role of second-order effects. Dry pinned joints, favoured for connecting beams and columns, contribute to the overall efficiency in assemblage. Cast-in-situ concrete is typically reserved for connection to foundations and topping precast floor elements. Pinned joints transform the structure into an ideal isostatic system, with cantilevered columns anchored securely at the base, in designers' mind. However, this transformation reduces the energy dissipation capacity, preventing plastic hinge formation in beams and amplifying P-Delta effects in columns. The simplified approach proposed herein assesses dynamic instability in single and multi-storey precast hinged frames, providing a tool for expeditious numerical capacity assessment, useful at the initial design stage. The goal is to predict dynamic collapse and/or the attainment of specific seismic-oriented limit states based on fundamental structural parameters. Incremental nonlinear dynamic analysis, utilising far-field ground motion records, is employed to evaluate performance of a variety of precast structures modelled as equivalent single-degree-of-freedom systems. The outcomes yield inelastic spectra that provide insights into the structural capacity in terms of response modification factor and could help analysts/designers towards seismic performance-based design as well as the assessment problem. These spectra, which can themselves be taken as metrics for structural performance evaluation (in addition to as a reliable tool/means for design), are generated based on various structural parameters, including building height, column aspect ratios, and floor mass configurations, in relation to different limit states typically deemed crucial in the design of these structures for earthquake-induced actions. Regression analyses of median spectra show that polynomial expressions could fit them with good accuracy, as testified by a coefficient of determination in the 0.76–0.98 range for most of the cases.

Revisiting building height restriction policy in the historic center of Seoul: Exploring performance-based height management using view shadow simulation

This study empirically explores 3D isovists to explore an alternative approach to a 90 m height cap in Seoul’s historic center. We introduced the concept of “view shadow” in the city center to explore potential room for growth: (1) areas hidden by existing buildings and (2) areas visible but not altering the current skyline. The proposed approach integrates the concept of view shadow cast by existing towers to minimize visual impact and preserve iconic and historic views. The simulation findings indicate that a significant portion, approximately 31 sites or 58.5% of the total, can accommodate taller towers than 90 m without compromising the integrity of the historic skyline. The study demonstrates the ability to increase the floor area by 74% and up to 137% from existing conditions to revitalize Seoul’s historic center.

Analysis of Urban Spatial Morphology in Harbin: A Study Based on Building Characteristics and Driving Factors

With the advancement of urbanization, the complexity and diversity of urban spatial forms have become increasingly prominent, profoundly and widely affecting aspects such as urban spatial layout and planning, as well as residents’ quality of life. This paper focuses on the buildings in Harbin City, comprehensively reflecting the spatial form of Harbin through multiple dimensions including building height, volume, and area. This research precisely quantifies three key indicators of urban buildings: building coverage, building expandability, and building staggeredness. Subsequently, these indicators are intertwined with the main driving factors of urban development (including economic development and resident population) to conduct a multidimensional spatial form analysis. The results indicate that the diversity of Harbin’s urban spatial form is the result of the interplay of multiple factors, including economic and demographic influences. These analytical outcomes not only reveal the evolution mechanism of Harbin’s current urban spatial form but also provide data support and theoretical basis for future urban planning and management.

Green space-building integration for Urban Heat Island mitigation: Insights from Beijing's fifth ring road district

In this research, we delve into the complex arrangement of urban landscapes, where green spaces and buildings are not merely co-existing but are interwoven into a cohesive fabric that shapes the thermal environment. Our approach transcends the conventional methods of analysis, which typically isolate the roles of greenery or built environments. Instead, we adopt a synergistic perspective that recognizes the collective influence of these landscape constituents on the urban thermal pattern. Key insights are: (1) A linear decrease in average land surface temperature with increasing green space coverage is observed. However, substantial temperature variations (up to 8 °C) within the same coverage interval highlight the significant impact of built-up pattern on thermal conditions; (2) High Building Height and Floor Area Ratio, and low Building Coverage Ratio and Sky View Factor, are linked to cooler temperatures in areas with up to 50 % green space; (3) The study suggests that low-temperature areas can inform the adjustment of built-up patterns in high-temperature areas, offering a strategy for thermal environment optimization within specific green space coverage intervals. This research contributes insights into the integrated planning of green spaces and buildings, with implications for urban development and renewal initiatives aiming to enhance the urban thermal environment.

Green Campus Transformation in Smart City Development: A Study on Low-Carbon and Energy-Saving Design for the Renovation of School Buildings

In the context of increasingly deteriorating global ecological conditions and rising carbon emissions from buildings, campus architecture, as the primary environment for youth learning and living, plays a crucial role in low-carbon energy-efficient design, and green environments. This paper takes the case of Yezhai Middle School in Qianshan, Anhui Province, to explore wind environment optimization and facade energy-saving strategies for mountainous campus buildings under existing building stock renovation. In the context of smart city development, integrating advanced technologies and sustainable practices into public infrastructure has become a key objective. Through wind environment simulations and facade energy retrofitting, this study reveals nonlinear increases in wind speed with building height and significant effects of ground roughness on wind speed variations. Adopting EPS panels and insulation layers in facade energy retrofitting reduces energy consumption for winter heating and summer cooling. The renovated facade effectively prevents cold air intrusion and reduces external heat gain, achieving approximately 24% energy savings. This research provides a scientific basis and practical experience for low-carbon energy retrofitting of other campus and public buildings, advancing the construction industry towards green and low-carbon development goals within the framework of smart city initiatives.

Exploring the regional cooling efficiency of urban residential vegetation using scenario simulation

The study of the cooling efficiency of vegetation in urban residential areas at a micro-scale is important for improving the thermal environment of those areas. The quantitative analysis of the effect of the layout of different building patterns on the cooling efficiency of green space is particularly crucial. This study takes a typical residential area with a row-column arrangement in Jiangning District, Nanjing City, Jiangsu Province, China, as the research object. Using the ENVI-MET model used for numerical simulation, 15 simulation scenarios were designed based on building orientation, height, and density. The research proposes the methodology of the regional cooling efficiency (RCE) of urban residential vegetation, reveals the daily variation characteristics of the RCE of vegetation in a residential area, and analyzes the factors influencing of regional cooling efficiency. The results showed that the daily variation in RCE for vegetation in the residential area exhibited a single-peak trend. The minimum and maximum RCE values appeared at 6:00 and 14:00, respectively. The average air temperature and building density in the residential area had a significant positive correlation with RCE, while average relative humidity had a negative correlation. Average wind speed, average building height, and average sky view factor showed nonlinear correlations with RCE, and the importance ranking of each factor's effect on RCE was air temperature > relative humidity > building density > wind speed > building height > sky view factor. This study will provide theoretical support for improving the thermal environment in urban residential areas during the urban planning process.