3D Urban Models Research Articles

Under the Dome: A 3D Urban Texture Model and Its Relationship with Urban Land Surface Temperature

The spatial distribution of buildings is one of the key factors influencing the local environment within a city. The quantitative measurement of building distribution can provide critical information for exploring local climate patterns in urban areas. Previous studies mainly focused on the two-dimensional spatial distribution of buildings and ignored the differences in height. In this study, a three-dimensional (3D) urban texture model based on an improved radial distribution function is proposed to describe the 3D spatial distribution of urban buildings. Using a set of concentric domes above the ground, a texture curve can be generated at any location in a city, from which a variety of numerical features are extracted to depict the local 3D urban landscape quantitatively. The proposed model was applied to Wuhan, one of the largest cities in central China, and the results demonstrated that the proposed model could identify various building distribution patterns in the city. Additionally, the relationship between urban texture and land surface temperature in Wuhan was analyzed. It was found that the 3D urban texture model effectively improved the accuracy of land surface temperature estimation. This study provides a new tool for urban environmental assessment and urban planning decision making.

Urban thermal environment and surface energy balance in 3D high-rise compact urban models: Scaled outdoor experiments

This study investigates the diurnal characteristics of air-surface temperatures and surface energy balance (SEB) of outdoor scaled arrays under different sky conditions from October to December 2017 in Guangzhou. Key geometrical parameters of the arrays include aspect ratio H/W = 2.4 (building height H = 1.2 m, street width W = 0.5 m), building area density λp = 0.25, and frontal area density λf = 0.6. Two types of buildings are investigated: “hollow” model means hollow concrete buildings and “water” model filled with water.Direct solar radiation, wall height, and wall orientation are significant factors that affect the diurnal variations of air-wall surface temperatures. The wall temperature shows a common declining trend from the upper heights to the lower heights. The water model experiences a smaller mean daily temperature range (DTR) of about 10 °C than the hollow model (mean DTR = 15.5 °C) due to heat storage. Moreover, 50%~60% net radiation (Q*) are partitioned into heat storage (estimated by the element surface temperature method) for the water model, which is about two times for the hollow model between 10:00 to 16:00. For the hollow model, the sum of sensible and latent heat fluxes contributes to the majority fraction of Q*. On clear sky days, the diurnal variation of short-wave radiation shows a single peak, while more complicated variations in occasionally cloudy days. The mean albedo is mainly affected by solar altitude angle, sky conditions which ranged from 0.21 to 0.23 with H/W = 2.4 in current study. The present study may provide experimental data to validate numerical and theoretical models for urban climate studies.

Examining runner's outdoor heat exposure using urban microclimate modeling and GPS trajectory mining

It is important to quantify human heat exposure in order to evaluate and mitigate the negative impacts of heat on human well-being in the context of global warming. This study proposed a human-centric framework to examine human personal heat exposure based on anonymous GPS trajectories data mining and urban microclimate modeling. The mean radiant temperature (Tmrt) that represents human body's energy balance was used to indicate human heat exposure. The meteorological data and high-resolution 3D urban model generated from multispectral remotely sensed images and LiDAR data were used as inputs in urban microclimate modeling to map the spatio-temporal distribution of the Tmrt in the Boston metropolitan area. The anonymous human GPS trajectory data collected from fitness Apps was used to map the spatio-temporal distribution of human outdoor activities. By overlaying the anonymous GPS trajectories on the generated spatio-temporal maps of Tmrt, this study further examined the heat exposure of runners in different age-gender groups in the Boston area. Results show that there is no significant difference in terms of heat exposure for female and male runners. The female runners in the age of 45–54 are exposed to more heat than female runners of 18–24 and 25–34, while there is no significant difference among male runners. This study proposed a novel method to estimate human heat exposure, which would shed new light on mitigating the negative impacts of heat on human health.

AN EFFICIENT REPRESENTATION OF 3D BUILDINGS: APPLICATION TO THE EVALUATION OF CITY MODELS

Abstract. City modeling consists in building a semantic generalized model of the surface of urban objects. These could be seen as a special case of Boundary representation surfaces. Most modeling methods focus on 3D buildings with Very High Resolution overhead data (images and/or 3D point clouds). The literature abundantly addresses 3D mesh processing but frequently ignores the analysis of such models. This requires an efficient representation of 3D buildings. In particular, for them to be used in supervised learning tasks, such a representation should be scalable and transferable to various environments as only a few reference training instances would be available. In this paper, we propose two solutions that take into account the specificity of 3D urban models. They are based on graph kernels and Scattering Network. They are here evaluated in the challenging framework of quality evaluation of building models. The latter is formulated as a supervised multilabel classification problem, where error labels are predicted at building level. The experiments show for both feature extraction strategy strong and complementary results (F-score > 74% for most labels). Transferability of the classification is also examined in order to assess the scalability of the evaluation process yielding very encouraging scores (F-score > 86% for most labels).

IMAGE-BASED REALITY-CAPTURING AND 3D MODELLING FOR THE CREATION OF VR CYCLING SIMULATIONS

Abstract. With this paper, we present a novel approach for efficiently creating reality-based, high-fidelity urban 3D models for interactive VR cycling simulations. The foundation of these 3D models is accurately georeferenced street-level imagery, which can be captured using vehicle-based or portable mapping platforms. Depending on the desired type of urban model, the street-level imagery is either used for semi-automatically texturing an existing city model or for automatically creating textured 3D meshes from multi-view reconstructions using commercial off-the-shelf software. The resulting textured urban 3D model is then integrated with a real-time traffic simulation solution to create a VR framework based on the Unity game engine. Subsequently, the resulting urban scenes and different planning scenarios can be explored on a physical cycling simulator using a VR helmet or viewed as a 360-degree or conventional video. In addition, the VR environment can be used for augmented reality applications, e.g., mobile augmented reality maps. We apply this framework to a case study in the city of Berne to illustrate design variants of new cycling infrastructure at a major traffic junction to collect feedback from practitioners about the potential for practical applications in planning processes.

Investigating the spatial distribution of resident’s outdoor heat exposure across neighborhoods of Philadelphia, Pennsylvania using urban microclimate modeling

Cities are experiencing more and more frequent extreme heat events in hot summers in the context of rising global temperatures. A precise understanding of the spatial distribution of the human outdoor heat exposure across neighborhoods in cities is of great importance for urban heat management. Different from remote sensing based the land surface temperature, this study calculated the mean radiant temperature, which is more objective to indicate human heat stress, to study the spatial distribution of human outdoor heat exposure in Philadelphia, Pennsylvania. The SOLWEIG (SOlar and LongWave Environmental Irradiance Geometry) model was applied to estimate the mean radiant temperature based on the high-resolution urban 3D model and meteorological data. This study further examined the spatial distributions of heat exposure levels across neighborhoods of different groups in Philadelphia. Results show that there is no significant disparity in terms of outdoor heat exposure levels for different racial/ethnic groups in Philadelphia. Generally, the elderly, who usually are more vulnerable to extreme heat, tend to live in neighborhoods with less outdoor heat exposure in summer (p<0.001). The higher-income people tend to live in thermally more comfortable neighborhoods (p<0.001). The study provides a precise understanding of the heat distribution across neighborhoods, which would further help to develop strategies to allocate resources to the most needed neighborhoods to maximumly mitigate the negative impact of urban heat.

Surfer: A fast simulation algorithm to predict surface temperatures and mean radiant temperatures in large urban models

Outdoor thermal comfort simulation simulations rely on the mean radiant temperature (MRT) seen by pedestrians as an important input that remains difficult to compute. Especially for large urban models, computing relevant surface temperatures and radiation fluxes that make up the MRT is a daunting task in terms of simulation setup and the computational overhead. We propose a new algorithm to estimate exterior surface temperatures of building facades, roofs, and ground surfaces in an arbitrary urban 3D model. The algorithm discretizes all model surfaces and clusters them by material properties and sky and sun exposure to reduce computational complexity. The model setup is fully automated, and the algorithm is implemented in the popular Rhino3d CAD environment. We demonstrate the accuracy of the algorithm by comparing both the resulting external surface temperatures against a high-fidelity simulation and the final MRT against real-world measurements. We report an RMSE of 1.8 °C and 2.0 °C, respectively, while reducing simulation times by a factor of ~80. Envisioned applications of the algorithm range from rapid microclimate simulations in fast-paced urban design processes to large scale urban comfort evaluation of existing cities.

Deep Neural Networks for Road Sign Detection and Embedded Modeling Using Oblique Aerial Images

Oblique photogrammetry-based three-dimensional (3D) urban models are widely used for smart cities. In 3D urban models, road signs are small but provide valuable information for navigation. However, due to the problems of sliced shape features, blurred texture and high incline angles, road signs cannot be fully reconstructed in oblique photogrammetry, even with state-of-the-art algorithms. The poor reconstruction of road signs commonly leads to less informative guidance and unsatisfactory visual appearance. In this paper, we present a pipeline for embedding road sign models based on deep convolutional neural networks (CNNs). First, we present an end-to-end balanced-learning framework for small object detection that takes advantage of the region-based CNN and a data synthesis strategy. Second, under the geometric constraints placed by the bounding boxes, we use the scale-invariant feature transform (SIFT) to extract the corresponding points on the road signs. Third, we obtain the coarse location of a single road sign by triangulating the corresponding points and refine the location via outlier removal. Least-squares fitting is then applied to the refined point cloud to fit a plane for orientation prediction. Finally, we replace the road signs with computer-aided design models in the 3D urban scene with the predicted location and orientation. The experimental results show that the proposed method achieves a high mAP in road sign detection and produces visually plausible embedded results, which demonstrates its effectiveness for road sign modeling in oblique photogrammetry-based 3D scene reconstruction.

A “Smartly Functional” Urban 3D Model: A New Way to Preserve the State of Health and Quality of a Complex Masonry Structure

The 3D model is the primary information of an integrated support system for the assessment of structural safety under vertical loads and seismic vulnerability of a masonry building. The available approaches for evaluating seismic demand and capacity still appear inadequate and today aims to improve the process of knowledge of the seismic behavior of masonry structures and of the reliability of the numerical analysis of evaluation methods. Discrete modeling approaches (macro-elements) can lead to more reliable results if accurate surveys of the geometry and construction details of the masonry structure are used, especially in contexts where advise against the execution of invasive on-site tests for assessments both under vertical and seismic loads, limiting the investigation campaigns. In order to improve digital processes, oriented to the knowledge of the state of health and quality of a masonry structure, this study illustrates a new overture to virtual modeling and assessment of the structural safety of this type of work. The survey and relief methodology here proposed integrates digital data sensors—configured within an IoT (Internet of Things) network—in a geometric model with a level of accurate and precise detail, processed downstream of the laser scanner and photogrammetric survey of the single masonry building, as “S. Domenico Church in the “Sassi” of Matera.

Statistical Road-Traffic Noise Mapping Based on Elementary Urban Forms in Two Cities of South Korea

Statistical models that can generate a road-traffic noise map for a city or area where only elementary urban design factors are determined, and where no concrete urban morphology, including buildings and roads, is given, can provide basic but essential information for developing a quiet and sustainable city. Long-term cost-effective measures for a quiet urban area can be considered at early city planning stages by using the statistical road-traffic noise map. An artificial neural network (ANN) and an ordinary least squares (OLS) model were developed by utilizing data on urban form indicators, based on a 3D urban model and road-traffic noise levels from a normal noise map of city A (Gwangju). The developed ANN and OLS models were applied to city B (Cheongju), and the resultant statistical noise map of city B was compared to an existing normal road-traffic noise map of city B. The urban form indicators that showed multi-collinearity were excluded by the OLS model, and among the remaining urban forms, road-related urban form indicators such as traffic volume and road area density were found to be important variables to predict the road-traffic noise level and to design a quiet city. Comparisons of the statistical ANN and OLS noise maps with the normal noise map showed that the OLS model tends to under-estimate road-traffic noise levels, and the ANN model tends to over-estimate them.

Three-dimensional geological modeling and spatial analysis from geotechnical borehole data using an implicit surface and marching tetrahedra algorithm

Three-dimensional (3D) geological modeling based on borehole data usually requires many manual operations, and the modeling process remains very complicated and time consuming. This paper presents an automatic implicit 3D geological modeling and visualization method that can be applied to urban geotechnical drilling data. First, by analyzing the general characteristics of these types of data, the implicit Hermite radial basis function (HRBF) surface is used to simulate geological interfaces according to lithological layers/units in boreholes. Second, the marching tetrahedra (MT) visualization method is optimized with new data structures and split operations to extract explicit mesh models from implicit geological surfaces. Then, the optimized tetrahedron used in the field of 3D urban drilling modeling is described in detail. Finally, the local geotechnical engineering data of two Chinese cities are used to verify the modeling algorithm, and several kinds of spatial analyses are carried out, including visualization, data querying, accuracy assessment and multiple cutting methods. The results show that the proposed urban subsurface 3D geological modeling method is effective in visualizing the structural shape, topological relationship and formation properties of strata that can be used to predict underground conditions and reduce construction risks during urban geotechnical engineering projects.

Chiuro laboratory: integration of workflows from digital survey to optimised 3D urban models for interactive exploration

The digital acquisition of Chiuro (Italy) is part of a research action of the still ongoing project “Le radici di una identità” (“An identity and its roots”), dealing with the documentation of the original urban structure of Chiuro, a small settlement located in northern Italy, whose interesting remains of mediaeval towers and Renaissance palaces are still well preserved. The paper focusses on the complete workflow developed by the group to create an explorative and implementable 3D digital model of the urban centre, constructed by a set of optimised mesh models. From the acquisition phase to geometric processing methodologies, different modelling strategies have been investigated to solve problems related to survey integration, and optimisation of the architectural digital assets. The main challenge is in fact the utilisation of the huge amount of data gathered during the previous surveying campaigns, providing a specific workflow to obtain an optimised 3D model. Moreover, the paper analyses some outputs: one is the storytelling of historical and cultural heritage in an attractive way, using game engines to visualise and give access to detailed digital contents to the general public.

Urban growth prediction with parcel based 3D urban growth model (PURGOM)

While cities grow horizontally over natural areas, they also grow vertically with high-rise construction in time. The Floor Area Ratio (FAR) is defined as the ratio of the amount of construction area on a parcel to the parcel area. FAR is one of the essential indicators for detecting and measuring 3D (three-dimensional) change. The amount and trends of change differ for each urban settlement and on its internal dynamics.This study consists of two stages: determining and modeling the variables and their weights that affect the FAR values and generating future estimates. First, the criteria affecting the growth trends between the years of 2012 and 2019 in the study area of Saray were examined as five groups at the parcel level with statistical and spatial analysis. It has been determined that the criteria; accessibility, accessibility in line with planning decisions, zoning and land-use decisions, land values, and the built environment affect the FAR value distribution. As a result of the analysis, the selected criteria were evaluated with Geographical Information Systems (GIS) and the weighted linear combination method. The probable spatial distribution of FAR coefficients of each parcel was found. The FAR coefficients obtained were calibrated by real FAR values for 2019. Future predictions for the years 2030 and 2040 were revealed according to the demand scenario. As a result, it was determined that there is a construction pressure on the urban center and near the transportation routes.The primary purpose of this study is to determine current trends by creating a 3D urban growth model based on parcel-level FAR values, making predictions, and producing decision support tools for city managers.•Determination of criteria and weights according to spatial dynamics of the study area.•Determination of the amount and type of urban growth demand specific to the study area and its compatibility with different scenarios.•Prediction of parcel-based 3D urban growth

Retracted] 3D City Online Visualization and Cluster Architecture for Digital City

As an important carrier of human production, life, and social development, the emergence of cities symbolizes the maturity and civilization of mankind. For more than 40 years of reform and opening up, our country’s economic development has become increasingly prosperous, and urbanization is booming. At present, our country is in a decisive period for building a well‐off society in an all‐round way, with rapid progress in socio‐economic growth and urbanization. Based on this, this article is oriented towards urban visualization modeling work and proposes a cluster modeling method that is compatible with the combination of urban geological structure and three‐dimensional urban space, so that urban space modeling work not only pays attention to the rationality of above‐ground planning and construction but also fully considers underground geology the stability and safety of the structure. This paper uses the 3D city online visualization modeling technology to efficiently and reasonably complete the 3D urban geological modeling under the fusion of multiple geological data and combines the organic combination of multisource heterogeneous model data to convert the geological model data into a 3D geographic information model; the universal standard format analyzes the rapid construction of large‐scale complex geological structure models and the integrated expression of multisource heterogeneous model data. Experiments have proved that from the cluster capacity of 5,000 to 100,000, no matter how much the modeling time is different, whether it is to search the entire territory or part of the scope, the search time of the 3D city visualization model is less than 20 ms, and the 3D city visualization model map of the city can be well established. This shows that the three‐dimensional city visualization model highlights the impact of the urban geological environment on urban construction and development and visually and vividly displays region geological structure and other information in a three‐dimensional way, providing corresponding information for urban geological stability assessment and geological disaster rescue reference and help.

A reformative framework for processes from building permit issuing to property ownership in Turkey

A smart built environment has become necessary for ensuring social well-being due to uncontrolled population growth and unrestrainable urban sprawl. In this connection, effective land administration is a significant element to actualize sustainable development. Yet existing building permit procedures fail to satisfy the need for current construction demands because of the insufficient transparency and inefficient procedures. Two dimensional (2D) based systems also remain incapable to unambiguously delineate the property ownership related to complex buildings. Keeping up-to-date the three dimensional (3D) urban models is another key for smart cities but this issue has become difficult owing to the rapid changes in the cities. In this sense, this paper first examines thoroughly the current situation in Turkey in terms of the building permit procedures, land administration, and 3D city modeling. Then, the paper detailedly proposes a reformative framework. The framework consists of the use of digital building models for both building permit processes and 3D registration of property ownership, as well as updating the 3D city model databases. The proposed framework is evaluated in terms of its applicability with a discussion of the prospective directions.

VISUALIZING 3D CLIMATE DATA IN URBAN 3D MODELS

Abstract. In order to understand and explain urban climate, the visual analysis of urban climate data and their relationships with the urban morphology is at stake. This involves partly to co-visualize 3D field climate data, obtained from simulation, with urban 3D models. We propose two ways to visualize and navigate into simulated climate data in urban 3D models, using series of horizontal 2D planes and 3D point clouds. We then explore different parameters regarding transparency, 3D semiologic rules, filtering and animation functions in order to improve the visual analysis of climate data 3D distribution. To achieve this, we apply our propositions to the co-visualization of air temperature data with a 3D urban city model.

A Promotional Construction Approach for an Urban Three-Dimensional Compactness Model—Law-of-Gravitation-Based

Urban sprawl has led to various economic, social, and environmental problems. Therefore, it is very significant to improve the efficiency of resource usage and promote the development of compact urban form. It is a common topic that measuring urban compactness is done with certain ways and methods as well. Presently, most urban compactness measurement methods are based on two-dimensional (2D) formats, but methods based on three-dimensional (3D) formats that can precisely describe the actual urban spatial conditions are still lacking. To measure the compactness of the 3D urban spatial form accurately, a 3D Compactness Index (VCI) was established based on the Law of Gravitation and the quantitative measurement model. In this model, larger 3D Compactness Index values indicate a more 3D-compact city. However, different urban scales may influence the discrepancy scale of different cities. Thus, the 3D Compactness Index model was normalized as the Normalized 3D Compactness Index (NVCI) to eliminate such discrepancies. In the Normalized 3D Compactness Index model, a sphere with the same volume of real urban buildings in the city was assumed as the most compact 3D urban form, and which was also calculated by 3D Compactness Index processing. The compactness value of the normalized 3D urban form is obtained by comparing the 3D Compactness Index with the most compact 3D urban form. In this study, 1149 typical communities in Xiamen, China, were selected as the experimental fields to verify the index. Some of communities have a quite different Normalized 3D Compactness Index, although they have a similar Normalized 2D Compactness Index (NCI), respectively. Moreover, comparing with the 2D Compactness Index (CI) and Normalized 2D Compactness Index (NCI), the 3D Compactness Index and Normalized 3D Compactness Index can describe and explain reality more precisely. The constructed 3D urban compactness model is expected to contribute to scientific study on urban compactness.

LONG-SHORT SKIP CONNECTIONS IN DEEP NEURAL NETWORKS FOR DSM REFINEMENT

Abstract. Detailed digital surface models (DSMs) from space-borne sensors are the key to successful solutions for many remote sensing problems, like environmental disaster simulations, change detection in rural and urban areas, 3D urban modeling for city planning and management, etc. Traditional methodologies, e.g., stereo matching, used to generate photogrammetric DSMs from stereo imagery, usually deliver low-quality results due to the matching errors in homogeneous areas or the lack of information when observing the scene under different viewing angles. This makes the tasks related to building reconstruction very challenging since in most cases it is difficult to recognize the type of roofs, especially if overlaid with trees. This work represents a continuation of research regarding the automatic optimization of building geometries in photogrammetric DSMs with half-meter resolution and introduces an improved generative adversarial network (GAN) architecture which allows to reconstruct complete and detailed building structures without neglecting even low-rise urban constructions. The generative part of the network is constructed in a way that it simultaneously processes height and intensity information, and combines short and long skip connections within one architecture. To improve different aspects of the surface, several loss terms are used, the contributions of which are automatically balanced during training. The obtained results demonstrate that the proposed methodology can achieve two goals without any manual intervention: improve the roof surfaces by making them more planar and also recognize and optimize even small residential buildings which are hard to detect.

Web 3D: a CityGML viewer for cross-domain problem resolution

3D urban models are a key component of diverse applications based on geospatial data, such as urban management and urban planning. CityGML models (OGC standards) are interoperable and allow the integration and dissemination of data within the spatial data infrastructures (SDI) objectives. 3D web viewers must allow model visualization and user interaction with geospatial data. This paper presents a system architecture for web visualization of a CityGML urban model. The system allows geospatial data structuring and storage as well as model visualization and access through a Web3D viewer. During the development of the system, the cross-domain problem was solved using GeoJSON. This change in format improved user access to the 3D urban model and its data. This standard also enabled the integrated storage of geospatial information and allows access to information from other geospatial data servers without cross-domain problems.

Urban Geological 3D Modeling Based on Papery Borehole Log

Borehole log is important data for urban geological 3D modeling. Most of the current borehole logs are stored in a papery form. The construction of a smart city puts forward requirements for the automatic and intelligent 3D modeling of urban geology. However, it is difficult to extract the information from the papery borehole log quickly. What is more, it is unreliable to rely entirely on automated algorithms for modeling without artificial participation, but there is no effective way to integrate geological knowledge into 3D geological modeling currently. Therefore, it is necessary to research how to use existing papery borehole logs efficiently. To overcome the above obstacles, we designed a method that combines structural analysis and layout understanding to extract information from the borehole log. Then, the knowledge-driven three-dimensional geological modeling is proposed based on dynamic profiles. With these methods, the papery borehole log can be converted into structured data which can be used for data analysis directly, and geological knowledge can be integrated into the process of 3D geological modeling. The 3D geological modeling of Xinyang City based on a papery borehole log has been taken as an example to verify the feasibility of the method.