A REVIEW OF 3D GIS FOR USE IN CREATING VIRTUAL HISTORIC DUBLIN

This paper illustrates how BIM integration with GIS is approached as part of the workflow in creating Virtual Historic Dublin. A design for a WEB based interactive 3D model of historic buildings and centres in Dublin City (Virtual Historic Dublin City) paralleling smart city initiates is now under construction and led by the National Monuments at the Office of Public Works in Ireland. The aim is to facilitate the conservation and maintenance of historic infrastructure and fabric and the dissemination of knowledge for education and cultural tourism using an extensive Historic Building Information Model. Remote sensing data is now processed with greater ease to create 3D intelligent models in Historic BIM. While the use of remote sensing, HBIM and game engine platforms are the main applications used at present, 3D GIS has potential to form part of the workflow for developing the Virtual Historic City. 2D GIS is now being replaced by 3D spatial data allowing more complex analysis to be carried out, 3D GIS can define and depict buildings, urban rural centres in relation to their geometry topological, semantic and visualisation properties. The addition of semantic attributes allows complex analysis and 3D spatial queries for modelling city and urban elements. This analysis includes fabric and structural elements of buildings, relief, vegetation, transportation, water bodies, city furniture and land use

3-Dimensional Building Details from Aerial Photography for Internet Maps

This paper introduces the automated characterization of real estate (real property) for Internet mapping. It proposes a processing framework to achieve this task from vertical aerial photography and associated property information. A demonstration of the feasibility of an automated solution builds on test data from the Austrian City of Graz. Information is extracted from vertical aerial photography and various data products derived from that photography in the form of a true orthophoto, a dense digital surface model and digital terrain model, and a classification of land cover. Maps of cadastral property boundaries aid in defining real properties. Our goal is to develop a table for each property with descriptive numbers about the buildings, their dimensions, number of floors, number of windows, roof shapes, impervious surfaces, garages, sheds, vegetation, presence of a basement floor, and other descriptors of interest for each and every property of a city. From aerial sources, at a pixel size of 10 cm, we show that we have obtained positional accuracies in the range of a single pixel, an accuracy of areas in the 10% range, floor counts at an accuracy of 93% and window counts at 86% accuracy. We also introduce 3D point clouds of facades and their creation from vertical aerial photography, and how these point clouds can support the definition of complex facades

FACADE RECONSTRUCTION FOR TEXTURED LOD2 CITYGML MODELS BASED ON DEEP LEARNING AND MIXED INTEGER LINEAR PROGRAMMING

The paper describes a workflow for generating LoD3 CityGML models (i.e. semantic building models with structured facades) based on textured LoD2 CityGML models by adding window and door objects. For each wall texture, bounding boxes of windows and doors are detected using “Faster R-CNN”, a deep neural network. We evaluate results for textures with different resolutions on the ICG Graz50 facade dataset. In general, detected bounding boxes match very well with the rectangular shape of most wall openings. Thus, no further classification of shapes is required. Windows are typically aligned to rows and columns, and only a few different types of windows exist for each facade. However, the neural network proposes rectangles of varying sizes, which are not always aligned perfectly. Thus, we use post-processing to obtain a more realistic appearance of facades. Window and door rectangles get aligned by solving a mixed integer linear optimization problem, which automatically leads to a clustering of these openings into few different classes of window and door types. Furthermore, an a-priori knowledge about the number of clusters is not required

Automatic reconstruction of three-dimensional building models from dense image matching datasets

PhD ThesisThe generation of three-dimensional (3D) building models without roof geometry is currently easily automated using a building footprint and single height value. The automatic reconstruction of roof structures, however, remains challenging because of the complexity and variability in building geometry. Attempts from imagery have utilised high spatial resolution but have only reconstructed simple geometry. This research addresses the complexity of roof geometry reconstruction by developing an approach, which focuses on the extraction of corners to reconstruct 3D buildings as boundary representation models, to try overcome the limitations of planar fitting procedures, which are currently favoured. Roof geometry information was extracted from surface models, true orthophotos and photogrammetric point clouds; reconstructed at the same spatial resolution of the captured aerial imagery, with developments in pixel-to-pixel matching. Edges of roof planes were extracted by the Canny edge detector, and then refined with a workflow based on the principles of scan-line segmentation to remove false positive detection. Line tracing procedures defined the corner positions of the extracted edges. A connectivity ruleset was developed, which searches around the endpoints of unconnected lines, testing for potential connecting corners. All unconnected lines were then removed reconstruct 3D models as a closed network of connecting roof corners. Building models have been reconstructed both as block models and also with roof structures. The methodology was tested on data of Newcastle upon Tyne, United Kingdom, with results showing corner extraction success at 75% and to within a planimetric accuracy of ±0.5 m. The methodology was then tested on data of Vaihingen, Germany, which forms part of the ISPRS 3D reconstruction benchmark. This allowed direct comparisons to be made with other methods. The results from both study areas showed similar planimetric accuracy of extracted corners. However, both sites were not as successful in the reconstruction of roof planes.Ordnance Surve

Building Tomograph – From Remote Sensing Data of Existing Buildings to Building Energy Simulation Input

Existing buildings often have low energy efficiency standards. For the preparation of retrofits, reliable high-quality data about the status quo is required. However, state-of-the-art analysis methods mainly rely on on-site inspections by experts and hence tend to be cost-intensive. In addition, some of the necessary devices need to be installed inside the buildings. As a consequence, owners hesitate to obtain sufficient information about potential refurbishment measures for their houses and underestimate possible savings. Remote sensing measurement technologies have the potential to provide an easy-to-use and automatable way to energetically analyze existing buildings objectively. To prepare an energetic simulation of the status quo and of possible retrofit scenarios, remote sensing data from different data sources have to be merged and combined with additional knowledge about the building. This contribution presents the current state of a project on the development of new and the optimization of conventional data acquisition methods for the energetic analysis of existing buildings solely based on contactless measurements, general information about the building, and data that residents can obtain with little effort. For the example of a single-family house in Morschenich, Germany, geometrical, semantical, and physical information are derived from photogrammetry and quantitative infrared measurements. Both are performed with the help of unmanned aerial vehicles (UAVs) and are compared to conventional methods for energy efficiency analysis regarding accuracy of and necessary effort for input data for building energy simulation. The concept of an object-oriented building model for measurement data processing is presented. Furthermore, an outlook is given on the project involving advanced remote sensing techniques such as ultrasound and microwave radar application for the measurement of additional energetic building parameters

Extractıng Semantıc Buıldıng Models From Aerıal Stereo Images And Conversıon To Cıtygml

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2010Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2010Son yıllarda üç boyutlu (3D) şehir modelleri ve coğrafi bilgi sistemleri (CBS) günden güne önem kazanmaktadır. Üç boyutlu şehir modelleri, şehir detaylarının ve yeryüzünde ki cisimlerin sayısal gosterimleridir. Şehir hakkında gerekli bilgileri belirlemek için birçok kaynaktan veri toplamak mümkündür. Bu veriler LIDAR, lazer tarama, geleneksel ölçme yöntemleri, uydu ve hava fotoğraflarından yararlanılan çeşitli yöntemler yardımı ile elde edilir. Üç boyutlu Cografi Bilgi Sistemleri için toplanan veriler mekansal modelleme, coğrafi analizler, 3D görsellik ve simülasyon uygulamalarında kullanılır. Coğrafi verinin toplanması bir bilgi sisteminin yaratılması için en önemli aşamalardan biridir. Elde edilen verilerin coğrafi, topolojik, mekansal ve görünüş özelliklerini amaca en uygun şekilde,arasında ki ilişkileri ve sınıfları ile birlikte CityGML veri modeli içerisinde tanımlanır. Ana problem fotogrametrik yöntemle elde edilen sanal şehir modellerinin CityGML e dönüştürülmesi hakkında bir boşluk bulunmasıdır. Yapılan tez çalışmasının ana amacı fotogrametrik yöntemler kullanılarak olusturulan model ile City GML veri modeli arasında bulunan bu boşluğu doldurmaktır. Bu yapılan tez çalışması sırasında bu belirtilen boşluk FME programı ile doldurulmustur.In recent years establishing three-dimensional (3D) city models and Geographic Information Systems (GIS) are getting more popular day by day. 3D City Models are digital representations of the Earth’s surface and related objects belonging to urban areas. In order to get information about a city is necessary to collect data from different sources. There are several methods of collecting the data such as LIDAR, laser scanning, surveying measurements, aerial and satellite images… etc. The 3D GIS data collected using with 3D geographic imaging can be used for spatial modeling, GIS analysis, 3D visualization and simulation applications. The collection of geographic data is of primary importance for the creation and maintenance of a GIS. CityGML defines the classes and relations for the most relevant topographic objects in cities and regional models with respect to their geometrical, topological, semantical and topological properties. The main problem, there is a gap between CityGML and traditional photogrammetric measurement methods. The main aim of the thesis study is how to create a link between the photogrammetric methods and CityGML, which is a common information model for the representation of 3D urban objects. In order to fıll the gap FME (The Feature Manipulation Engine) is used during the thesis studyYüksek LisansM.Sc