Towards generating highly detailed 3D CityGML models from OpenStreetMap

About one decade has passed since US vice president Al Gore articulated his vision of Digital Earth (DE). Within this decade, a global multi-resolution and three-dimensional (3D) representation of the Earth, which sums up the DE vision, increasingly gained interest in both public and science. Due to the desired high resolution of the available data, highly detailed 3D city models comprise a huge part of DE and they are becoming an essential and useful tool for a range of different applications. In the past as well as at present, 3D models normally come from a range of different sources generated by professionals, such as laser scans or photogrammetry combined with 2D cadaster data. Some models are generated with semi-automated or fully automated approaches, but in most cases manual fine tuning or even manual construction from architectural plans is required. Further beyond outdoor city models, DE additionally envisages the provision of indoor information. That is, the interior structure of public or publically accessible buildings, such as airports or shopping malls, is represented and made available in 3D; however, at the moment, such models are mostly created by hand and essentially based on professional data sources. In contrast to such professional data, which is mainly captured by surveyors or companies, the last few years revealed the phenomenon of crowdsourced geodata, which receives an increasing attractiveness as an alternative data source for many Geographic Information Systems (GIS). Former research already demonstrated the power and richness of such geodata – especially OpenStreetMap (OSM) – and it has also been proved that this non-standardized, crowdsourced geodata can be combined with international standards of the Open Geospatial Consortium (OGC). For example, CityGML Level-of-Detail 1 (LoD1) and LoD2 models have already been created automatically from OSM. The research presented in this article will further continue on the automated generation of CityGML models from OpenStreetMap. Essentially, a method for the creation of highly detailed CityGML LoD4 models with interior structures will be explained. By applying the invented approach on existing OSM data, limitations and restrictions of the IndoorOSM mapping proposal, the available data and the developed approach are revealed and discussed.     

Automatically enhancing CityGML LOD2 models with a corresponding indoor geometry

The international standard CityGML defines five levels of detail (LODs) for 3D city models, but only the highest of these (LOD4) supports modelling the indoor geometry of a building, which must be acquired in correspondingly high detail and therefore at a high cost. Whereas simple 3D city models of the exterior of buildings (e.g. CityGML LOD2) can be generated largely automatically, and are thus now widely available and have a great variety of applications, similarly simple models containing their indoor geometries are rare.

In this paper we present two contributions: (i) the definition of a level of detail LOD2+, which extends the CityGML LOD2 specification with indoor building geometries of comparable complexity to their exterior geometries in LOD2; and more importantly (ii) a method for automatically generating such indoor geometries based on existing CityGML LOD2 exterior geometries. We validate our method by generating LOD2+ models for a subset of the Rotterdam 3D data set and visually comparing these models to their real counterparts in building blueprints and imagery from Google Street View and Bing Maps. Furthermore, we use the LOD2+ models to compute the net internal area of each dwelling and validate our results by comparing these values to the ones registered in official government data sets.     

A continuous deployment-based approach for the collaborative creation,maintenance, testing and deployment of CityGML models

Georeferenced 3D models are an increasingly common choice to store and display urban data in many application areas. CityGML is an open and standardized data model, and exchange format that provides common semantics for 3D city entities and their relations and one of the most common options for this kind of information. Currently, creating and maintaining CityGML models is costly and difficult. This is in part because both the creation of the geometries and the semantic annotation can be complex processes that require at least some manual work. In fact, many publicly available CityGML models have errors. This paper proposes a method to facilitate the regular maintenance of correct city models in CityGML. This method is based on the continuous deployment strategy and tools used in software development, but adapted to the problem of creating, maintaining and deploying CityGML models, even when several people are working on them at the same time. The method requires designing and implementing CityGML deployment pipelines. These pipelines are automatic implementations of the process of building, testing and deploying CityGML models. These pipelines must be run by the maintainers of the models when they make changes that are intended to be shared with others. The pipelines execute increasingly complex automatic tests in order to detect errors as soon as possible, and can even automate the deployment step, where the CityGML models are made available to their end users. In order to demonstrate the feasibility of this method, and as an example of its application, a CityGML deployment pipeline has been developed for an example scenario where three actors maintain the same city model. This scenario is representative of the kind of problems that this method intends to solve, and it is based on real work in progress. The main benefits of this method are the automation of model testing, every change to the model is tested in a repeatable way; the automation of the model deployment, every change to the model can reach its end users as fast as possible; the systematic approach to integrating changes made by different people working together on the models, including the possibility of keeping parallel versions with a common core; an automatic record of every change made to the models (who did what and when) and the possibility of undoing some of those changes at any time.     

Quality assessment for building footprints data on OpenStreetMap

In the past two years, several applications of generating three-dimensional (3D) buildings from OpenStreetMap (OSM) have been made available, for instance, OSM-3D, OSM2World, OSM Building, etc. In these projects, 3D buildings are reconstructed using the buildings’ footprints and information about their attributes, which are documented as tags in OSM. Therefore, the quality of 3D buildings relies strongly on the quality of the building footprints data in OSM. This article is dedicated to a quality assessment of building footprints data in OSM for the German city of Munich, which is one of the most developed cities in OSM. The data are evaluated in terms of completeness, semantic accuracy, position accuracy, and shape accuracy by using building footprints in ATKIS (German Authority Topographic–Cartographic Information System) as reference data. The process contains three steps: finding correspondence between OSM and ATKIS data, calculating parameters of the four quality criteria, and statistical analysis. The results show that OSM footprint data in Munich have a high completeness and semantic accuracy. There is an offset of about four meters on average in terms of position accuracy. With respect to shape, OSM building footprints have a high similarity to those in ATKIS data. However, some architectural details are missing; hence, the OSM footprints can be regarded as a simplified version of those in ATKIS data.     

Establishing a national standard for 3D topographic data compliant to CityGML

This article describes a research project that realised a national standard for 3D geo-information. The standard was developed as part of a pilot in which more than 65 private, public and scientific organisations collaborated to analyse and push 3D developments in the Netherlands (run between March 2010 and June 2011). The 3D standard was established through several steps. First, a comparison between the existing 3D computer-aided design and GIS standards was carried out that selected the Open Geospatial Consortium (OGC) standard CityGML as the optimal 3D standard to align to. Second, the equivalent concepts in CityGML and the existing national standard for large-scale topography (Information Model Geography [IMGeo]) were identified. Third, IMGeo was extended to 3D following the principles of CityGML Application Domain Extensions. The model was tested by applying it to real data. Based on the experiences of this pilot, this article proposes a framework of guidelines and principles for extending CityGML for national purposes, deduced from the modelling experiences. This is a unique contribution since experiences on extending CityGML are new and not well described in the OGC CityGML specifications. Finally, this article presents the change requests (CRs) which have been submitted to OGC to make the CityGML standard more suited for integration with existing 2D topographic information models. The CRs were formulated based on experiences from developing this nationwide 3D standard.     

An evaluation of ontology matching techniques on geospatial ontologies

Standardization is one of the pillars of interoperability. In this context, efforts promoted by the Open Geospatial Consortium, such as CityGML (Technical University, Berlin), a standard for exchanging three-dimensional models or urban city objects, are welcomed. However, information from other domains of interest (e.g. energy efficiency or building information modeling) is needed for tasks such as land planning, large-scale flooding analysis, or demand/supply energy simulations. CityGML allows extension in order to integrate information from other domains, but the development process is expensive because there is no way to perform it automatically. The discovery of correspondences between CityGML concepts and other domains concepts poses a significant challenge.

Ontology matching is the research field emerged from the Semantic Web to address automatic ontology integration. Using the ontology underlying CityGML and the ontologies which model other domains of interest, ontology matching would be able to find the correspondences that would permit the integration in a more automatic manner than it is done now.

In this paper, we evaluate if ontology matching techniques allow performing an automatic integration of geospatial information modeled from different viewpoints. In order to achieve this, an evaluation methodology was designed, and it was applied to the discovery of relationships between CityGML and ontologies coming from the building information modeling and Geospatial Semantic Web domains. The methodology and the results of the evaluation are presented. The best results have been achieved using string-based techniques, while matching systems give the worst precision and recall. Only in a few cases the values are over 50%, which shows the limitations when these techniques are applied to ontologies with a partial overlap.     

3D building roof reconstruction from airborne LiDAR point clouds: a framework based on a spatial database

Three-dimensional (3D) building models are essential for 3D Geographic Information Systems and play an important role in various urban management applications. Although several light detection and ranging (LiDAR) data-based reconstruction approaches have made significant advances toward the fully automatic generation of 3D building models, the process is still tedious and time-consuming, especially for massive point clouds. This paper introduces a new framework that utilizes a spatial database to achieve high performance via parallel computation for fully automatic 3D building roof reconstruction from airborne LiDAR data. The framework integrates data-driven and model-driven methods to produce building roof models of the primary structure with detailed features. The framework is composed of five major components: (1) a density-based clustering algorithm to segment individual buildings, (2) an improved boundary-tracing algorithm, (3) a hybrid method for segmenting planar patches that selects seed points in parameter space and grows the regions in spatial space, (4) a boundary regularization approach that considers outliers and (5) a method for reconstructing the topological and geometrical information of building roofs using the intersections of planar patches. The entire process is based on a spatial database, which has the following advantages: (a) managing and querying data efficiently, especially for millions of LiDAR points, (b) utilizing the spatial analysis functions provided by the system, reducing tedious and time-consuming computation, and (c) using parallel computing while reconstructing 3D building roof models, improving performance.     

城市三维地理信息系统中三维模型的快速构建方法

大规模三维模型的快速构建一直是影响城市三维地理信息系统(3DUGIS)发展的一个重要因素.基于3DUGIS中景观模型的表达原则与分类,分别针对抽象的点、线、面状对象提出符号匹配和三角剖分的批量三维模型构建方法.这种建模方法方便、快捷、自动化程度高,可广泛应用于城市景观中地面、河流、道路、绿地、规则建筑物、地下管线等地物的三维建模.通过对上述三维模型快速构建方法的实现,验证了三维模型生成的效果和效率.     

A building label placement method for 3D visualizations based on candidate label evaluation and selection

Adding building labels greatly improves the recognizability of buildings and the readability of three-dimensional (3D) city scenes. However, building label placement is much more complex in 3D scenes than in two-dimensional (2D) maps. The annotation effect is influenced by the attributes of the 3D label, building visibility, and the spatial relationship between the building and viewpoint. In this context, automatically generating building labels for 3D scenes during interactions requires highly complex computations. By contrast, evaluating candidate labels and then selecting the suitable label for each building can be effectively implemented. This paper introduces an approach for labeling buildings in 3D scenes based on evaluations of label candidates. The proposed method predefines a candidate label set for each building. These candidates are then evaluated in terms of their attributes and the relationship between the labels and viewpoint at runtime. The best candidate label, or a situational alternative for each building, is then placed in order of comprehensive label priority to avoid annotation conflicts. A series of experiments demonstrate that this method effectively enhances the correlation of labels and buildings, improves interactive efficiency, and realizes a viable global label layout.     

民国时期广州市建成区主体建筑立体形态的恢复及其特征

基于1928年1﹕10 000的地形图,解译土地利用类型,确定建成区边界与建筑用地的空间范围。将建筑用地分为单体建筑、线状道路两侧的骑楼和面状同类建筑区3类。根据史料与现场调查,分别为点、线、面3类建筑的高度赋值,恢复不考虑海拔的建成区主体建筑立体形态。基于所建模型,从平面形态、平均高度、空间格局、宽高比、高度轴、天际线以及形态组合几方面对民国时期建成区立体形态特征进行分析归纳,得出如下结论：１）民国时期广州城市沿珠江发展使得城区轮廓呈狭长的带状;２）城市平均高度仅为6.07 ｍ,建筑物普遍低矮;３）建筑物在平面上为多级的棋盘网组合,而骑楼街构成的宽浅网格,成为当时空间尺度最大的建筑单元组合形态;４）道路宽度与两侧建筑物高度形成的宽高比大,城市具有较好的通透性;５）沿江西路与当时的城市中轴线中山纪念堂―市府合署大楼构成了倒“T”型城市空间高度轴,并在单体建筑高度空间分布与天际线的变化上得到很好的反映;６）城市立体形态主要由盆地、格网、谷地、台地等4种宽浅的单元组成。立体形态深层次上反映了当时生产力技术条件下政府与市场力量的综合作用,以及城市功能区分化在立体形态上的表现,从而也成为该时期华南地区依山傍水城市立体形态的重要标志。     

三维虚拟城市自动化生成方法研究

从城市元胞自动机模型的角度研究三维虚拟城市的自动化生成方法.通过建立城市元胞自动机模型,模拟城市土地单元的演化过程,根据演化结果确定各土地单元的空间位置和相应的建筑物类型.研究利用Creator进行三维场景建模,利用OpenGVS场景管理技术随机生成建筑物,并将其布设在三维场景的相应位置上,生成三维虚拟城市,并就三维虚拟城市自动化生成系统的功能结构设计和数据结构、空间坐标转换等技术问题进行了探讨.     

Characterizing mixed-use buildings based on multi-source big data

To-date few research has successfully integrated big data from multiple sources to characterize urban mixed-use buildings. In this paper, we introduce a probabilistic model to integrate multi-source and geospatial big data (social network data, taxi trajectories, Points of Interest and remote sensing images) to characterize urban mixed-use buildings. The usefulness of our model is demonstrated with a case study of the Tianhe District in megacity Guangzhou, China. The model predicted building functions at 85% accuracy based on ground truth data from field surveys. We further explored the spatial patterns of the identified building functions. Most mixed-use buildings are located along major streets. Our proposed model can identify mixed-use buildings in a city; information is useful for planning evaluation and urban policymaking.     

BUILDING DENSITY AND INTERIOR BUILDING TEMPERATURES: A PHYSICAL MODELING EXPERIMENT

The effect of building density on the interior temperatures of buildings is explored using scaled physical models. The urban canopy layer is modeled as a single-cube structure surrounded by a wall that represents neighboring structures. Each physical model was constructed of plywood and consisted of a cube 200 mm in height, enclosed by a wall 200 mm in height. Four models were constructed corresponding to height/width ratios (H/W) of 4, 2, 1, and 0.5 and placed at an exposed site located at 34°N. The interior air temperature of each cube, direct and diffuse solar radiation on a horizontal surface, and ambient air temperature and wind velocity were measured over a period from late November 1996 to early June 1997. To extract the influence of building density, air temperatures were compared against those measured in the model representing a H/W of 1. The results show that nighttime cooling is primarily a function of building density, but that daytime heating depends on the interaction of density with changing model-sun relationships. [Key words: urban canopy layer, building air temperature, building density, physical model.]     

Embedding user-generated content into oblique airborne photogrammetry-based 3D city model

Oblique airborne photogrammetry-based three-dimensional (3D) city model (OAP3D) provides a spatially continuous representation of urban landscapes that encompasses buildings, road networks, trees, bushes, water bodies, and topographic features. OAP3D is usually present in the form of a group of unclassified triangular meshes under a multi-resolution data structure. Modifying such a non-separable landscape constitutes a daunting task because manual mesh editing is normally required. In this paper, we present a systematic approach for easily embedding user-generated content into OAP3D. We reduce the complexity of OAP3D modification from a 3D mesh operation to a two-dimensional (2D) raster operation through the following workflow: (1) A region of interest (ROI) is selected to cover the area that is intended to be modified for accommodating user-defined content. (2) Spatial interpolation using a set of manually controlled elevation samples is employed to generate a user-defined digital surface model (DSM), which is used to reform the ROI surface. (3) User-generated objects, for example, artistically painted road textures, procedurally generated water effects, and manually created 3D building models, are overlaid onto the reformed ROI.     

A visualization-oriented 3D method for efficient computation of urban solar radiation based on 3D–2D surface mapping

The temporal and spatial distribution of solar energy in urban areas is highly variable because of the complex building structures present. Traditional GIS-based solar radiation models rely on two-dimensional (2D) digital elevation models to calculate insolation, without considering building facades and complicated three-dimensional (3D) shading effects. Inspired by the ‘texture baking’ technique used in computer graphics, we propose a full 3D method for computing and visualizing urban solar radiation based on image-space data representation. First, a surface mapping approach is employed to project each 3D triangular mesh onto a 2D raster surface whose cell size determines the calculation accuracy. Second, the positions and surface normal vectors of each 3D triangular mesh are rasterized onto the associated 2D raster using barycentric interpolation techniques. An efficient compute unified device architecture -accelerated shadow-casting algorithm is presented to accurately capture shading effects for large-scale 3D urban models. Solar radiation is calculated for each raster cell based on the input raster layers containing such information as slope, aspect, and shadow masks. Finally, a resulting insolation raster layer is produced for each triangular mesh and is represented as an RGB texture map using a color ramp. Because a virtual city can be composed of tens of thousands of triangular meshes and texture maps, a texture atlas technique is presented to merge thousands of small images into a single large image to batch draw calls and thereby efficiently render a large number of textured meshes on the graphics processing unit.     

Intelligent Identification of Building Patches and Assessment of Roof Greening Suitability in High-density Urban Areas: A Case Study of Chengdu

With the expansion of a city, the urban green space is occupied and the urban heat island effect is serious. Greening the roof surfaces of urban buildings is an effective way to increase the area of urban green space and improve the urban ecological environment. To provide effective data support for urban green space planning, this paper used high-resolution images to (1) obtain accurate building spots on the map of the study area through deep learning assisted manual correction; and (2) establish an evaluation index system of roof greening including the characteristics of the roof itself, the natural environment and the human society environment. The weight values of attributes not related to the roof itself were calculated by Analytic Hierarchy Process (AHP). The suitable green roof locations were evaluated by spatial join, weighted superposition and other spatial analysis methods. Taking the areas within the Chengdu city’s third ring road as the study area, the results show that an accurate building pattern obtained by deep learning greatly improves the efficiency of the experiment. The roof surfaces unsuitable for greening can be effectively classified by the method of feature extraction, with an accuracy of 86.58%. The roofs suitable for greening account for 48.08%, among which, the high-suitability roofs, medium-suitability roofs and low-suitability roofs represent 45.32%, 38.95% and 15.73%. The high-suitability green buildings are mainly distributed in the first ring district and the western area outside the first ring district in Chengdu. This paper is useful for solving the current problem of the more saturated high-density urban area and allowing the expansion of the urban ecological environment.     

Propagation of positional error in 3D GIS: estimation of the solar irradiation of building roofs

While error propagation in GIS is a topic that has received a lot of attention, it has not been researched with 3D GIS data. We extend error propagation to 3D city models using a Monte Carlo simulation on a use case of annual solar irradiation estimation of building rooftops for assessing the efficiency of installing solar panels. Besides investigating the extension of the theory of error propagation in GIS from 2D to 3D, this paper presents the following contributions. We (1) introduce varying XY/Z accuracy levels of the geometry to reflect actual acquisition outcomes; (2) run experiments on multiple accuracy classes (121 in total); (3) implement an uncertainty engine for simulating acquisition positional errors to procedurally modelled (synthetic) buildings; (4) perform the uncertainty propagation analysis on multiple levels of detail (LODs); and (5) implement Solar3Dcity – a CityGML-compliant software for estimating the solar irradiation of roofs, which we use in our experiments. The results show that in the case of the city of Delft in the Netherlands, a 0.3/0.6 m positional uncertainty yields an error of 68 kWh/m²/year (10%) in solar irradiation estimation. Furthermore, the results indicate that the planar and vertical uncertainties have a different influence on the estimations, and that the results are comparable between LODs. In the experiments we use procedural models, implying that analyses are carried out in a controlled environment where results can be validated. Our uncertainty propagation method and the framework are applicable to other 3D GIS operations and/or use cases. We released Solar3Dcity as open-source software to support related research efforts in the future.     

基于正交多项式的平原城区机载LiDAR数据滤波算法

从机载LiDAR点云数据中分离地面点与非地面点生成城区DEM,是构建数字城市的首要工作。该文对机载LiDAR数据处理中的滤波关键算法进行了研究。首先,利用常用的区域增长方法对机载LiDAR点云数据进行了滤波处理,然后基于正交多项式分带滤波方法进行了点云滤波,比较了两种算法的运行效率,分析了二者的特点,并通过试验对比进行了阈值参数优选,试验表明该算法具有较好的滤波效果,在平原城区的数字城市三维建模中具有很好的应用价值。     

A comparison of neighbourhood relations based on ordinary Delaunay diagrams and area Delaunay diagrams: an application to define the neighbourhood relations of buildings

ABSTRACT

The aim of this article is to describe a convenient but robust method for defining neighbourhood relations among buildings based on ordinary Delaunay diagrams (ODDs) and area Delaunay diagrams (ADDs). ODDs and ADDs are defined as a set of edges connecting the generators of adjacent ordinary Voronoi cells (points representing centroids of building polygons) and a set of edges connecting two centroids of building polygons, which are the generators of adjacent area Voronoi cells, respectively. Although ADDs are more robust than ODDs, computation time of ODDs is shorter than that of ADDs (the order of their computation time complexity is O(nlogn)). If ODDs can approximate ADDs with a certain degree of accuracy, the former can be used as an alternative. Therefore, we computed the ratio of the number of ADD edges to that of ODD edges overlapping ADDs at building and regional scales. The results indicate that: (1) for approximately 60% of all buildings, ODDs can exactly overlap ADDs with extra ODD edges; (2) at a regional scale, ODDs can overlap approximately 90% of ADDs with 10% extra ODD edges; and (3) focusing on judging errors, although ADDs are more accurate than ODDs, the difference is only approximately 1%.