scholarly journals Reconstruction of 3D Building Model Using Point of Interest Technique at Different Altitude and Range

2021 ◽  
Vol 767 (1) ◽  
pp. 012010
Author(s):  
A A Ab Aziz ◽  
M Muhammad ◽  
S A Sulaiman ◽  
K N Tahar
Keyword(s):  
Building Model ◽  
Point Of Interest ◽  
3D Building Model

scholarly journals POST-EARTHQUAKE 3D BUILDING MODEL (LOD2) GENERATION FROM UAS IMAGERY: THE CASE OF VRISA TRADITIONAL SETTLEMENT, LESVOS, GREECE

2020 ◽  
Vol XLIV-4/W3-2020 ◽  
pp. 165-172
Author(s):  
K. Chaidas ◽  
G. Tataris ◽  
N. Soulakellis
Keyword(s):  
Laser Scanner ◽  
Building Model ◽  
Levels Of Detail ◽  
Building Models ◽  
Digital Elevation ◽  
3D Building Model ◽  
Modelling Techniques ◽  
Camera Position ◽  
Elevation Model ◽  
Comparison Of The Results

Abstract. In recent years 3D building modelling techniques are commonly used in various domains such as navigation, urban planning and disaster management, mostly confined to visualization purposes. The 3D building models are produced at various Levels of Detail (LOD) in the CityGML standard, that not only visualize complex urban environment but also allows queries and analysis. The aim of this paper is to present the methodology and the results of the comparison among two scenarios of LOD2 building models, which have been generated by the derivate UAS data acquired from two flight campaigns in different altitudes. The study was applied in Vrisa traditional settlement, Lesvos island, Greece, which was affected by a devastating earthquake of Mw = 6.3 on 12th June 2017. Specifically, the two scenarios were created by the results that were derived from two different flight campaigns which were: i) on 12th January 2020 with a flying altitude of 100 m and ii) on 4th February 2020 with a flying altitude of 40 m, both with a nadir camera position. The LOD2 buildings were generated in a part of Vrisa settlement consisted of 80 buildings using the footprints of the buildings, Digital Surface Models (DSMs), a Digital Elevation Model (DEM) and orthophoto maps of the area. Afterwards, a comparison was implemented between the LOD2 buildings of the two different scenarios, with their volumes and their heights. Subsequently, the heights of the LOD2 buildings were compared with the heights of the respective terrestrial laser scanner (TLS) models. Additionally, the roofs of the LOD2 buildings were evaluated through visual inspections. The results showed that the 65 of 80 LOD2 buildings were generated accurately in terms of their heights and roof types for the first scenario and 64 for the second respectively. Finally, the comparison of the results proved that the generation of post-earthquake LOD2 buildings can be achieved with the appropriate UAS data acquired at a flying altitude of 100 m and they are not affected significantly by a lower one altitude.

scholarly journals Pemetaan Bangunan Tiga Dimensi Untuk Pemodelan Jalur Evakuasi Darurat

2017 ◽  
Author(s):  
debby nurliza ulhaq ◽  
Budhy Soeksmantono ◽  
Ketut Wikantika
Keyword(s):  
Shortest Paths ◽  
Three Dimensional ◽  
Emergency Evacuation ◽  
Dijkstra’S Algorithm ◽  
Related Data ◽  
Building Model ◽  
Dijkstra's Algorithm ◽  
3D Building Model ◽  
Road Data ◽  
Evacuation Route

AbstrakMitigasi bencana merupakan salah satu hal penting yang harus dipertimbangkan terutama dalam konstruksi bangunan karena hal tersebut cukup rumit terlebih apabila dikaitkan dengan fakta tidak adanya informasi yang dapat digunakan untuk orang-orang menyelamatkan diri mereka sendiri. Maka dari itu, makalah ilmiah ini memperkenalkan mengenai network analysist untuk rute evakuasi darurat yang bertujuan untuk mencari rute terbaik menuju tempat aman seperti titik berkumpul tergantung pada situasi terkini. Pembuatan keputusan berdasarkan rute yang tepat akan dipilih berdasarkan kategori usia korban dan kondisi saat bencana terjadi, sehingga dapat mengurangi dampak buruk yang akan muncul. Algoritma Dijkstra menunjukan suatu algoritma perncarian rute terpendek antara gedung dan titik berkumpul dengan menghubungkan keduanya melalui data jalan. Model rute evakuasi ini dibentuk dengan menggunakan kombinasi antara model bangunan tiga dimensi yang dibangun dari data LiDAR, orthophoto, dan data lainnya yang berkaitan dengan pemodelan. Bangunan tiga dimensi dapat digunakan dalam manajemen bencana dan respon darurat karena dapat menyediakan informasi penting seperti lokasi bangunan. Evaluasi dari model yang diajukan meningkatkan kemampuan penyelamatan diri sendiri yang mengarah pada berkurangnya dampak buruk yang akan terjadi.Kata kunci: Evakuasi Darurat, Algoritma Dijkstra, LiDAR, pemodelan bangunan 3D AbstractMitigation is an important thing to be considered especially in building construction because it is quite complicated due to the fact that much of the information is unavailable for people to rescue themselves. Hence, this paper introduces about network analysis for evacuation emergency route which aims at finding the best route to the secured place such as the closest assembly point depends on the situation. Thus, decision making regarding the proper route to be chosen depends of the victim age category and current condition to minimize impact that can be generated. Dijkstra’s Algorithm is presented an algorithm for finding the shortest paths between building and assembly point by linking them through road data. This emergency evacuation route model is constructed by combining with three dimensional building model which constructed by using LiDAR data, orthophoto, and the other related data. Three dimensional geo data can be used in disaster management and emergency response because they may provide valuable information such as location of the building. The evaluation of the proposed model for a case study building improve self-sustaining which lead to chances of less adverse effects can appear.Keywords: Emergency Evacuation, Dijkstra’s Algorithm, LiDAR, 3D building model

scholarly journals AN INSPIRE-KONFORM 3D BUILDING MODEL OF BAVARIA USING CADASTRE INFORMATION, LIDAR AND IMAGE MATCHING

2016 ◽  
Vol XLI-B4 ◽  
pp. 747-754 ◽  
Author(s):  
R. Roschlaub ◽  
J. Batscheider
Keyword(s):  
Image Matching ◽  
High Speed ◽  
State Agency ◽  
Test Plan ◽  
Research Project ◽  
Data Set ◽  
Building Model ◽  
Building Models ◽  
Joint Research Project ◽  
3D Building Model

The federal governments of Germany endeavour to create a harmonized 3D building data set based on a common application schema (the AdV-CityGML-Profile). The Bavarian Agency for Digitisation, High-Speed Internet and Surveying has launched a statewide 3D Building Model with standardized roof shapes for all 8.1 million buildings in Bavaria. For the acquisition of the 3D Building Model LiDAR-data or data from Image Matching are used as basis in addition with the building ground plans of the official cadastral map. The data management of the 3D Building Model is carried out by a central database with the usage of a nationwide standardized CityGML-Profile of the AdV. The update of the 3D Building Model for new buildings is done by terrestrial building measurements within the maintenance process of the cadaster and from image matching. In a joint research project, the Bavarian State Agency for Surveying and Geoinformation and the TUM, Chair of Geoinformatics, transformed an AdV-CityGML-Profilebased test data set of Bavarian LoD2 building models into an INSPIRE-compliant schema. For the purpose of a transformation of such kind, the AdV provides a data specification, a test plan for 3D Building Models and a mapping table. The research project examined whether the transformation rules defined in the mapping table, were unambiguous and sufficient for implementing a transformation of LoD2 data based on the AdV-CityGML-Profile into the INSPIRE schema. The proof of concept was carried out by transforming production data of the Bavarian 3D Building Model in LoD2 into the INSPIRE BU schema. In order to assure the quality of the data to be transformed, the test specifications according to the test plan for 3D Building Models of the AdV were carried out. The AdV mapping table was checked for completeness and correctness and amendments were made accordingly.

Collaborative 3D Modeling

2016 ◽  
Vol 5 (3) ◽  
pp. 47-67 ◽  
Author(s):  
Rafika Hajji ◽  
Roland Billen
Keyword(s):  
3D Modeling ◽  
Building Model ◽  
3D Data ◽  
3D Building Model ◽  
Promising Solution ◽  
New Vision ◽  
Definition Of ◽  
2D Data ◽  
City Models

The need of 3D city models increases day by day. However, 3D modeling still faces some impediments to be generalized. Therefore, new solutions such as collaboration should be investigated. The paper presents a new vision of collaboration applied on 3D modeling through the definition of the concept of a 3D collaborative model. The paper highlights basic questions to be considered for the definition and the development of that model then argues the importance of reuse of 2D data as a promising solution to reconstruct 3D data and to upgrade to integrated 3D solutions in the future. This idea is supported by a case study, to demonstrate how 2D/2.5D data collected from different providers in Walloon region in Belgium can be integrated and reengineered to match the specifications of a 3D building model compatible with the CityGML standard.

Use of topographic LiDAR point clouds for building reconstruction

2021 ◽  
Author(s):  
Yipeng Yuan
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Point Clouds ◽  
Building Roof ◽  
Building Model ◽  
Building Models ◽  
Urban Models ◽  
Elevation Data ◽  
3D Building Model ◽  
Building Reconstruction

Demand for three-dimensional (3D) urban models keeps growing in various civil and military applications. Topographic LiDAR systems are capable of acquiring elevation data directly over terrain features. However, the task of creating a large-scale virtual environment still remains a time-consuming and manual work. In this thesis a method for 3D building reconstruction, consisting of building roof detection, roof outline extraction and regularization, and 3D building model generation, directly from LiDAR point clouds is developed. In the proposed approach, a new algorithm called Gaussian Markov Random Field (GMRF) and Markov Chain Monte Carlo (MCMC) is used to segment point clouds for building roof detection. The modified convex hull (MCH) algorithm is used for the extraction of roof outlines followed by the regularization of the extracted outlines using the modified hierarchical regularization algorithm. Finally, 3D building models are generated in an ArcGIS environment. The results obtained demonstrate the effectiveness and satisfactory accuracy of the developed method.

Sign in / Sign up

Export Citation Format

Share Document