Spatial Distribution Of Buildings Research Articles

A large‐scale urban 3D model organisation method considering spatial distribution of buildings

AbstractThe rendering of urban 3D scenes involves a large number of models. In order to render scenes more efficiently, the main solution is to build a level of detail model (LOD). This may have the problem of building fragmentation, while relying on building a level of detail model (LOD) alone cannot meet the accuracy and fluency of large‐scale scene visualisation. Effective and reasonable data organisation has important research significance for the authors to achieve accurate and fast rendering of scenes. Therefore, the authors propose a large‐scale city model data organisation method considering building distribution to solve the above problems. This method first classifies the buildings in the scene at macro‐, meso‐ and microscales and records the classification using R‐trees. Then an adaptive quadtree is used to construct the data index of the city model. Finally, the data organisation of the large‐scale 3D city model is achieved by using the information of each node of the R‐tree as a constraint and combining with the adaptive quadtree. The results show that the method not only ensures the integrity of the user's area of interest but also can improve the efficiency of 3D scene construction.

Contribution of local climate zones to the thermal environment and energy demand.

Urban heat islands (UHIs) and their energy consumption are topics of widespread concern. This study used remote sensing images and building and meteorological data as parameters, with reference to Oke's local climate zone (LCZ), to divide urban areas according to the height and density of buildings and land cover types. While analyzing the heat island intensity, the neural network training method was used to obtain temperature data with good temporal as well as spatial resolution. Combining degree-days with the division of LCZs, a more accurate distribution of energy demand can be obtained by different regions. Here, the spatial distribution of buildings in Shenyang, China, and the law of land surface temperature (LST) and energy consumption of different LCZ types, which are related to building height and density, were obtained. The LST and energy consumption were found to be correlated. The highest heat island intensity, i.e., UHILCZ 4, was 8.17°C. The correlation coefficients of LST with building height and density were −0.16 and 0.24, respectively. The correlation between urban cooling energy demand and building height was −0.17, and the correlation between urban cooling energy demand and building density was 0.17. The results indicate that low- and medium-rise buildings consume more cooling energy.

Combining cluster analysis and GIS maps to characterise building stock: case study in the historical city centre of Viseu, Portugal

The first step towards rehabilitation actions is deep knowledge of buildings characteristics and their conservation state. Studies comprehending large groups of buildings can be useful when dealing with significant amount of data, positively influencing decision-making processes starting from low level information. This paper describes a methodology that makes use of GIS-based maps to visualise the results of cluster analysis regarding defects in 495 buildings. This information was organised to apply a clustering technique with the purpose of identifying patterns related with defects. The GIS-based maps were created to support the interpretation of the clustering results. Conclusions regarding the most interesting number of clusters were drawn, as well as insights on the correlation between the spatial distribution of buildings and the defects observed. In two of the four analyses conducted, a pattern of buildings located in the central area of the historical zone was identified, which was associated with a higher number of defects probably related with the age of the constructions. These results are particularly relevant considering the definition of future rehabilitation actions and confirm the advantage of combining both tools, which is particularly meaningful in contexts where methodologies like this are scarce and limited in number.

Comprehensive flood vulnerability analysis in urban communities: Iowa case study

Floods are one of the most prevalent types of natural disasters affecting communities worldwide. It is expected to persist with increasing magnitude and frequency as a result of climate change, resulting in both direct and indirect negative consequences. The flood impact assessment is considered as a key component of flood risk management strategies, such as benefit-cost analysis for mitigation planning. This research aims to provide a comprehensive analysis of socio-economic impacts of the 100 and 500-year riverine flood scenarios for major communities in the State of Iowa, United States of America. The analysis includes impact on essential facilities, businesses, vehicles, loss of life, amount of debris transported downstream, and displaced population, using Hazards-United States (HAZUS) and the Hydrologic Engineering Center's Flood Impact Analysis (HEC-FIA) functions along with GIS-based analysis. Also, we have investigated the floodplain vulnerability using the combination of flood depth and velocity. Due to the differences in the topography and the spatial distribution of buildings and infrastructure, and the absence of sufficient flood prevention measures within the study area, our findings illustrate that some communities will suffer significant damage and losses during flooding. This research could aid communities in making more effective decisions regarding damage reduction, prioritizing mitigation actions, and preparing for future flood events.

MINHA CASA, MINHA VIDA PROGRAM AND ITS SPATIAL DISTRIBUTION IN RIO DE JANEIRO STATE

O presente artigo traz como tema aspectos significativos da problemática habitacional brasileira. A falta de moradias, sua qualidade e distribuição espacial são questões relevantes na urbanização do país e, em especial, no Estado do Rio de Janeiro. Nesse sentido, a partir de 2009 um novo ponto de inflexão se faz presente, o “Programa Minha Casa, Minha Vida” (PMCMV) foi criado de forma a dar subsídios a solvência do déficit habitacional brasileiro, se destacando pelos grandes subsídios orçamentários, do grande volume de construções e avanços na perspectiva social: o Programa buscava atender as faixas de renda mais baixas. Assim, o objetivo deste trabalho é verificar através da análise dos dados quantitativos e cartográficos um possível aumento da segregação socioespacial no estado do Rio de Janeiro em função da renda, além da concentração de unidades habitacionais nas faixas de renda com maior poder aquisitivo. A metodologia inclui análise de dados quantitativos e espaciais oficiais do Governo Federal, revisão da literatura ligada à habitação no Brasil e elaboração e análise de mapas a partir de dados espaciais.

Impact of coronavirus (COVID-19) spread-prevention actions on urban water consumption

This article aims to assess the impact of coronavirus (COVID-19) spread-prevention actions on water consumption, based on a case study in Joinville, Southern Brazil. Residential water consumption data, obtained through telemetry in two periods (before and after a governmental action imposing quarantine and social isolation), were analyzed. Complementarily, the analyses were also applied to the commercial, industrial and public consumption categories. For the analysis, Wilcoxon and Kruskal-Wallis non-parametric tests were applied and Prais-Winsten regression models were adjusted. The results of the Wilcoxon test show that there are significant differences between the analyzed periods, indicating a water consumption drop in the commercial, industrial and public categories, and an increase in the residential category. The regression model results confirm the effect of the restrictive actions in reducing consumption in non-residential categories. The results also indicate an increase in water consumption, which was steeper in apartment buildings than in houses, whether isolated or grouped in condominiums. A weak association was found between the variation in water consumption and the spatial distribution of buildings. Understanding water consumption related aspects is important to gather essential information to ensure the urban water supply system is resilient in a pandemic situation.

Urban air pollution caused by the emission of PM10 from the small household devices and abatement measures

This paper is focusing on particulate matter (PM10 ) as the one of the main pollutants in the urban environments, and the one of the main sources of PM emissions are small household furnaces. This paper shows a part of the results of the research related to measurements of the ambient concentrations of aerosols and definition of the sources of the pollution in one part of Banja Luka city area, with dominant private households. Spatial and seasonal variability of concentrations indicates a significant contribution of biomass and fossil fuel burning as well as specific meteorological conditions. By using positive matrix factorization, technique chemical composition data for PM10 were analysed in order to identify the possible sources and estimate their contribution to PM mass. A biomass combustion devices were identified as the one of dominant PM10 emission sources during the winter season, because highly determined correlation between PM10 and potassium content. From the other side, the results of the project ?Typology of Residential Buildings in Bosnia and Herzegovina?, were used as a tool for prediction and quantification of influence of the household?s appliances on the pollution as well as for definition of the possible measures for reduction for this specific location. This approach took in consideration spatial distribution of buildings, but also their type, which can give the opportunity to estimate their present energy needs and predict improvements, which can lead to reduction of the PM10 pollution at the end. On that base, some recommendations for the improvements were analysed.

Building simplification using backpropagation neural networks: a combination of cartographers' expertise and raster-based local perception

As a result of the complexity of building shapes and spatial distribution of buildings in urban and suburban areas, building generalization has been one of the most challenging tasks in automated map generalization. The key operator of the generalization is to resolve spatial conflicts inside building polygons caused by a reduction in map scale. Therefore, building simplification eliminates unnecessary details of the building, without the distortion of its original shape. Understanding that map generalization is an intelligent process, we proposed a novel approach for building simplification with raster-based local perception using a backpropagation (BP) neural network (BPNN) model for learning cartographers' knowledge. The model was structured in three layers, an input layer with a 24 × 24 retina, a hidden layer with four nodes, and an output layer with three nodes. Cartographers' expertise, coupled with a square detector designed for the perception of local contexts was presented to the model. In the test, a total of 468 building polygons were simplified, and the mean value of the similarity of building polygons before and after the simplification was 0.9796. The approach not only made the building simplification feasible but also produced satisfactory results.

Short-duration intense rainfall in the wards of Tokyo and its relationship with the spatial distribution of buildings

Short-duration intense rainfall in the wards of Tokyo and its relationship with the spatial distribution of buildings

Simulation of urban development in the City of Rome: Framework, methodology, and problem solving

In Italy’s case, the implementation of the UrbanSIM model involved the territory of Rome, including the municipalities of Rome and Fiumicino. The main goal was to build scenarios regarding the future of economic deconcentration. Rome is the largest municipality in Europe, with an inhabited surface area only slightly smaller than that of Greater London and almost double that of the inner Paris suburbs (the Petite Couronne). The spatial distribution of buildings within the municipality is distinctive. Unbuilt areas comprise 73 percent of the territory. These voids are often farmland (paradoxically, Rome is the largest rural municipality in Italy) or areas with high environmental, historic or cultural value. Fiumicino, previously part of the municipality of Rome, became an independent municipality in 1991. Its autonomy, made all the more significant because Fiumicino hosts the international airport, marked the start of an extensive process of economic deconcentration along the route connecting Rome to the airport. In Italy’s case, the implementation of the UrbanSIM model posed several challenges, notably the availability, homogeneity and completeness of data. This paper uses four specific cases (land use, travel times, accessibility, and residential land values) to propose a general methodology to solve problems related to missing or non-homogeneous data. For the land use, we simply combine two different land use data sources, while for accessibility and travel time data, we propose the use of geostatistical methods in order to estimate missing and unavailable data, calculating also the accuracy of the predictions. For the residential land values, which are discrete data, we suggest the use of deterministic interpolation techniques. While it has not yet been possible to implement the calibration stage, some simulation outputs are presented.

A Model of Students' Daily Activity Patterns

A model is described whose purpose is to predict the distribution of students in different activities and locations during the course of a typical day, depending on the effective restrictions imposed by the spatial distribution of buildings and sites, and by administrative and social constraints on the timing of activities. The model is of an entropy-maximising type; the data against which it is tested are drawn from time budget surveys made in two universities, using diary methods. A series of exploratory experiments made with the model are reported; these are designed to test the effects of alternative planning and administrative policies on activity patterns and the use of facilities.