scholarly journals INTEGRATED USE OF REMOTE SENSED DATA AND NUMERICAL CARTOGRAPHY FOR THE GENERATION OF 3D CITY MODELS

2018 ◽  
Vol XLII-2 ◽  
pp. 97-102 ◽  
Author(s):  
G. Bitelli ◽  
V. A. Girelli ◽  
A. Lambertini
Keyword(s):  
Large Scale ◽  
Point Clouds ◽  
3D Models ◽  
Geospatial Data ◽  
Aerial Images ◽  
Public Authorities ◽  
3D City Models ◽  
3D Point Clouds ◽  
Emilia Romagna Region ◽  
City Models

3D city models are becoming increasingly popular and important, because they constitute the base for all the visualization, planning, management operations regarding the urban infrastructure. These data are however not available in the majority of cities: in this paper, the possibility to use geospatial data of various kinds with the aim to generate 3D models in urban environment is investigated.<br> In 3D modelling works, the starting data are frequently the 3D point clouds, which are nowadays possible to collect by different sensors mounted on different platforms: LiDAR, imagery from satellite, airborne or unmanned aerial vehicles, mobile mapping systems that integrate several sensors. The processing of the acquired data and consequently the obtainability of models able to provide geometric accuracy and a good visual impact is limited by time, costs and logistic constraints.<br> Nowadays more and more innovative hardware and software solutions can offer to the municipalities and the public authorities the possibility to use available geospatial data, acquired for diverse aims, for the generation of 3D models of buildings and cities, characterized by different level of detail.<br> In the paper two cases of study are presented, both regarding surveys carried out in Emilia Romagna region, Italy, where 2D or 2.5D numerical maps are available. The first one is about the use of oblique aerial images realized by the Municipality for a systematic documentation of the built environment, the second concerns the use of LiDAR data acquired for other purposes; in the two tests, these data were used in conjunction with large scale numerical maps to produce 3D city models.

scholarly journals ANALYSIS OF 3D BUILDING MODELS ACCURACY BASED ON THE AIRBORNE LASER SCANNING POINT CLOUDS

2018 ◽  
Vol XLII-2 ◽  
pp. 797-804 ◽  
Author(s):  
W. Ostrowski ◽  
M. Pilarska ◽  
J. Charyton ◽  
K. Bakuła
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Large Scale ◽  
Point Clouds ◽  
3D Models ◽  
Airborne Laser Scanning ◽  
Aerial Images ◽  
Statistical Parameters ◽  
Airborne Laser ◽  
Building Models

Creating 3D building models in large scale is becoming more popular and finds many applications. Nowadays, a wide term “3D building models” can be applied to several types of products: well-known CityGML solid models (available on few Levels of Detail), which are mainly generated from Airborne Laser Scanning (ALS) data, as well as 3D mesh models that can be created from both nadir and oblique aerial images. City authorities and national mapping agencies are interested in obtaining the 3D building models. Apart from the completeness of the models, the accuracy aspect is also important. Final accuracy of a building model depends on various factors (accuracy of the source data, complexity of the roof shapes, etc.). In this paper the methodology of inspection of dataset containing 3D models is presented. The proposed approach check all building in dataset with comparison to ALS point clouds testing both: accuracy and level of details. Using analysis of statistical parameters for normal heights for reference point cloud and tested planes and segmentation of point cloud provides the tool that can indicate which building and which roof plane in do not fulfill requirement of model accuracy and detail correctness. Proposed method was tested on two datasets: solid and mesh model.

scholarly journals Semi-Automatic 3D City Model Generation from Large-Format Aerial Images

2018 ◽  
Vol 7 (9) ◽  
pp. 339 ◽  
Author(s):  
Mehmet Buyukdemircioglu ◽  
Sultan Kocaman ◽  
Umit Isikdag
Keyword(s):  
Large Scale ◽  
3D Visualization ◽  
Aerial Images ◽  
Model Generation ◽  
City Management ◽  
Large Format ◽  
3D City Models ◽  
3D City Model ◽  
City Model ◽  
City Models

3D city models have become crucial for better city management, and can be used for various purposes such as disaster management, navigation, solar potential computation and planning simulations. 3D city models are not only visual models, and they can also be used for thematic queries and analyzes with the help of semantic data. The models can be produced using different data sources and methods. In this study, vector basemaps and large-format aerial images, which are regularly produced in accordance with the large scale map production regulations in Turkey, have been used to develop a workflow for semi-automatic 3D city model generation. The aim of this study is to propose a procedure for the production of 3D city models from existing aerial photogrammetric datasets without additional data acquisition efforts and/or costly manual editing. To prove the methodology, a 3D city model has been generated with semi-automatic methods at LoD2 (Level of Detail 2) of CityGML (City Geographic Markup Language) using the data of the study area over Cesme Town of Izmir Province, Turkey. The generated model is automatically textured and additional developments have been performed for 3D visualization of the model on the web. The problems encountered throughout the study and approaches to solve them are presented here. Consequently, the approach introduced in this study yields promising results for low-cost 3D city model production with the data at hand.

scholarly journals PLASTIC SURGERY FOR 3D CITY MODELS: A PIPELINE FOR AUTOMATIC GEOMETRY REFINEMENT AND SEMANTIC ENRICHMENT

2021 ◽  
Vol V-4-2021 ◽  
pp. 17-24
Author(s):  
O. Wysocki ◽  
B. Schwab ◽  
L. Hoegner ◽  
T. H. Kolbe ◽  
U. Stilla
Keyword(s):  
Point Clouds ◽  
3D Models ◽  
Data Types ◽  
Automated Driving ◽  
3D City Models ◽  
Semantic Enrichment ◽  
Simulation Engine ◽  
Global Accuracy ◽  
Model Database ◽  
City Models

Abstract. Nowadays, the number of connected devices providing unstructured data is rapidly rising. These devices acquire data with a temporal and spatial resolution at an unprecedented level creating an influx of geoinformation which, however, lacks semantic information. Simultaneously, structured datasets like semantic 3D city models are widely available and assure rich semantics and high global accuracy but are represented by rather coarse geometries. While the mentioned downsides curb the usability of these data types for nowadays’ applications, the fusion of both shall maximize their potential. Since testing and developing automated driving functions stands at the forefront of the challenges, we propose a pipeline fusing structured (CityGML and HD Map datasets) and unstructured datasets (MLS point clouds) to maximize their advantages in the automatic 3D road space models reconstruction domain. The pipeline is a parameterized end-to-end solution that integrates segmentation, reconstruction, and modeling tasks while ensuring geometric and semantic validity of models. Firstly, the segmentation of point clouds is supported by the transfer of semantics from a structured to an unstructured dataset. The distinction between horizontal- and vertical-like point cloud subsets enforces a further segmentation or an immediate refinement while only adequately depicted models by point clouds are allowed. Then, based on the classified and filtered point clouds the input 3D model geometries are refined. Building upon the refinement, the semantic enrichment of the 3D models is presented. The deployment of a simulation engine for automated driving research and a city model database tool underlines the versatility of possible application areas.

scholarly journals GROUND AND AERIAL DIGITAL DOCUMENTATION OF CULTURAL HERITAGE: PROVIDING TOOLS FOR 3D EXPLOITATION OF ARCHAEOLOGICAL DATA

2017 ◽  
Vol XLII-2/W3 ◽  
pp. 141-145 ◽  
Author(s):  
G. Cantoro
Keyword(s):  
Laser Scanning ◽  
Large Scale ◽  
Point Clouds ◽  
3D Models ◽  
Aerial Photographs ◽  
Scientific Methods ◽  
Archaeological Data ◽  
3D Point Clouds ◽  
Digital Documentation ◽  
Time Changes

Archaeology is by its nature strictly connected with the physical landscape and as such it explores the inter-relations of individuals with places in which they leave and the nature that surrounds them. Since its earliest stages, archaeology demonstrated its permeability to scientific methods and innovative techniques or technologies. Archaeologists were indeed between the first to adopt GIS platforms (since already almost three decades) on large scale and are now between the most demanding customers for emerging technologies such as digital photogrammetry and drone-aided aerial photography. <br><br> This paper aims at presenting case studies where the “3D approach” can be critically analysed and compared with more traditional means of documentation. Spot-light is directed towards the benefits of a specifically designed platform for user to access the 3D point-clouds and explore their characteristics. Beside simple measuring and editing tools, models are presented in their actual context and location, with historical and archaeological information provided on the side. As final step of a parallel project on geo-referencing and making available a large archive of aerial photographs, 3D models derived from photogrammetric processing of images have been uploaded and linked to photo-footprints polygons. Of great importance in such context is the possibility to interchange the point-cloud colours with satellite imagery from OpenLayers. This approach makes it possible to explore different landscape configurations due to time-changes with simple clicks. <br><br> In these cases, photogrammetry or 3D laser scanning replaced, sided or integrated legacy documentation, creating at once a new set of information for forthcoming research and ideally new discoveries.

scholarly journals INTEGRATION OF 3D POINT CLOUDS WITH SEMANTIC 3D CITY MODELS – PROVIDING SEMANTIC INFORMATION BEYOND CLASSIFICATION

2021 ◽  
Vol VIII-4/W2-2021 ◽  
pp. 105-112
Author(s):  
C. Beil ◽  
T. Kutzner ◽  
B. Schwab ◽  
B. Willenborg ◽  
A. Gawronski ◽  
...  
Keyword(s):  
Point Cloud ◽  
Semantic Information ◽  
Spatial Information ◽  
Point Clouds ◽  
Semantic Knowledge ◽  
Point Cloud Data ◽  
Cloud Data ◽  
3D City Models ◽  
3D Point Clouds ◽  
City Models

Abstract. A range of different and increasingly accessible acquisition methods, the possibility for frequent data updates of large areas, and a simple data structure are some of the reasons for the popularity of three-dimensional (3D) point cloud data. While there are multiple techniques for segmenting and classifying point clouds, capabilities of common data formats such as LAS for providing semantic information are mostly limited to assigning points to a certain category (classification). However, several fields of application, such as digital urban twins used for simulations and analyses, require more detailed semantic knowledge. This can be provided by semantic 3D city models containing hierarchically structured semantic and spatial information. Although semantic models are often reconstructed from point clouds, they are usually geometrically less accurate due to generalization processes. First, point cloud data structures / formats are discussed with respect to their semantic capabilities. Then, a new approach for integrating point clouds with semantic 3D city models is presented, consequently combining respective advantages of both data types. In addition to elaborate (and established) semantic concepts for several thematic areas, the new version 3.0 of the international Open Geospatial Consortium (OGC) standard CityGML also provides a PointCloud module. In this paper a scheme is shown, how CityGML 3.0 can be used to provide semantic structures for point clouds (directly or stored in a separate LAS file). Methods and metrics to automatically assign points to corresponding Level of Detail (LoD)2 or LoD3 models are presented. Subsequently, dataset examples implementing these concepts are provided for download.

scholarly journals INTEGRATION OF 3D OBJECTS AND TERRAIN FOR 3D MODELLING SUPPORTING THE DIGITAL TWIN

2019 ◽  
Vol IV-4/W8 ◽  
pp. 147-154 ◽  
Author(s):  
J. Yan ◽  
S. Zlatanova ◽  
M. Aleksandrov ◽  
A. A. Diakite ◽  
C. Pettit
Keyword(s):  
Point Clouds ◽  
Critical Issue ◽  
3D Modelling ◽  
Data Sets ◽  
Military Operations ◽  
3D City Models ◽  
Digital Twin ◽  
3D Objects ◽  
3D Point Clouds ◽  
City Models

<p><strong>Abstract.</strong> 3D modelling of precincts and cities has significantly advanced in the last decades, as we move towards the concept of the Digital Twin. Many 3D city models have been created but a large portion of them neglect representing terrain and buildings accurately. Very often the surface is either considered planar or is not represented. On the other hand, many Digital Terrain Models (DTM) have been created as 2.5D triangular irregular networks (TIN) or grids for different applications such as water management, sign of view or shadow computation, tourism, land planning, telecommunication, military operations and communications. 3D city models need to represent both the 3D objects and terrain in one consistent model, but still many challenges remain. A critical issue when integrating 3D objects and terrain is the identification of the valid intersection between 2.5D terrain and 3D objects. Commonly, 3D objects may partially float over or sink into the terrain; the depth of the underground parts might not be known; or the accuracy of data sets might be different. This paper discusses some of these issues and presents an approach for a consistent 3D reconstruction of LOD1 models on the basis of 3D point clouds, DTM, and 2D footprints of buildings. Such models are largely used for urban planning, city analytics or environmental analysis. The proposed method can be easily extended for higher LODs or BIM models.</p>

scholarly journals Automated Visual Recognizability Evaluation of Traffic Sign Based on 3D LiDAR Point Clouds

2019 ◽  
Vol 11 (12) ◽  
pp. 1453 ◽  
Author(s):  
Shanxin Zhang ◽  
Cheng Wang ◽  
Lili Lin ◽  
Chenglu Wen ◽  
Chenhui Yang ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Laser Scanning ◽  
Large Scale ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Point Clouds ◽  
Traffic Sign ◽  
Traffic Signs ◽  
3D Point Clouds ◽  
Traffic Environment

Maintaining the high visual recognizability of traffic signs for traffic safety is a key matter for road network management. Mobile Laser Scanning (MLS) systems provide efficient way of 3D measurement over large-scale traffic environment. This paper presents a quantitative visual recognizability evaluation method for traffic signs in large-scale traffic environment based on traffic recognition theory and MLS 3D point clouds. We first propose the Visibility Evaluation Model (VEM) to quantitatively describe the visibility of traffic sign from any given viewpoint, then we proposed the concept of visual recognizability field and Traffic Sign Visual Recognizability Evaluation Model (TSVREM) to measure the visual recognizability of a traffic sign. Finally, we present an automatic TSVREM calculation algorithm for MLS 3D point clouds. Experimental results on real MLS 3D point clouds show that the proposed method is feasible and efficient.

scholarly journals INVESTIGATING INTEROPERABILITY CAPABILITIES BETWEEN IFC AND CITYGML LOD 4 – RETAINING SEMANTIC INFORMATION

2018 ◽  
Vol XLII-4/W10 ◽  
pp. 33-40 ◽  
Author(s):  
G. S. Floros ◽  
C. Ellul ◽  
E. Dimopoulou
Keyword(s):  
Semantic Information ◽  
Open Data ◽  
3D Models ◽  
Solar Panels ◽  
3D City Models ◽  
Information Models ◽  
Building Information ◽  
Consistent Manner ◽  
3D Information ◽  
City Models

<p><strong>Abstract.</strong> Applications of 3D City Models range from assessing the potential output of solar panels across a city to determining the best location for 5G mobile phone masts. While in the past these models were not readily available, the rapid increase of available data from sources such as Open Data (e.g. OpenStreetMap), National Mapping and Cadastral Agencies and increasingly Building Information Models facilitates the implementation of increasingly detailed 3D Models. However, these sources also generate integration challenges relating to heterogeneity, storage and efficient management and visualization. CityGML and IFC (Industry Foundation Classes) are two standards that serve different application domains (GIS and BIM) and are commonly used to store and share 3D information. The ability to convert data from IFC to CityGML in a consistent manner could generate 3D City Models able to represent an entire city, but that also include detailed geometric and semantic information regarding its elements. However, CityGML and IFC present major differences in their schemas, rendering interoperability a challenging task, particularly when details of a building’s internal structure are considered (Level of Detail 4 in CityGML). The aim of this paper is to investigate interoperability options between the aforementioned standards, by converting IFC models to CityGML LoD 4 Models. The CityGML Models are then semantically enriched and the proposed methodology is assessed in terms of model’s geometric validity and capability to preserve semantics.</p>

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