TY - JOUR A1 - Chizhova, Maria A1 - Brunn, Ansgar A1 - Stilla, Uwe T1 - Probabilistic feasibility of the HE reconstruction process of russian-orthodox churches JF - The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences N2 - The cultural human heritage is important for the identity of following generations and has to be preserved in a suitable manner. In the course of time a lot of information about former cultural constructions has been lost because some objects were strongly damaged by natural erosion or on account of human work or were even destroyed. It is important to capture still available building parts of former buildings, mostly ruins. This data could be the basis for a virtual reconstruction. Laserscanning offers in principle the possibility to take up extensively surfaces of buildings in its actual status. In this paper we assume a priori given 3d-laserscanner data, 3d point cloud for the partly destroyed church. There are many well known algorithms, that describe different methods of extraction and detection of geometric primitives, which are recognized separately in 3d points clouds. In our work we put them in a common probabilistic framework, which guides the complete reconstruction process of complex buildings, in our case russian-orthodox churches. Churches are modeled with their functional volumetric components, enriched with a priori known probabilities, which are deduced from a database of russian-orthodox churches. Each set of components represents a complete church. The power of the new method is shown for a simulated dataset of 100 russian-orthodox churches. KW - Building reconstruction KW - laserscanning data KW - 3d-point cloud KW - russian-orthodox churches KW - probability Y1 - 2016 U6 - https://doi.org/https://doi.org/10.5194/isprs-archives-XLI-B5-221-2016 VL - XLI-B5 SP - 221 EP - 227 ER - TY - JOUR A1 - Davidovic, Marina A1 - Kuzmic, Tatjana A1 - Vasic, Dejan A1 - Wich, Valentin A1 - Brunn, Ansgar A1 - Bulatovic, Vladimir T1 - Methodology for Road Defect Detection and Administration based on Mobile Mapping Data JF - Computer Modeling in Engineering & Sciences N2 - A detailed inspection of roads requires highly detailed spatial data with sufficient precision to deliver an accurate geometry and to describe road defects visually. This paper presents a novel method for the detection of road defects. The input data for road defect detection included point clouds and orthomosaics gathered by mobile mapping technology. The defects were categorized in three major groups with the following geometric primitives: points, lines and polygons. The method suggests the detection of point objects from matched point clouds, panoramic images and ortho photos. Defects were mapped as point, line or polygon geometries, directly derived from orthomosaics and panoramic images. Besides the geometric position of road defects, all objects were assigned to a variety of attributes: defect type, surface material, center-of-gravity, area, length, corresponding image of the defect and degree of damage. A spatial dataset comprising defect values with a matching data type was created to perform the attribute analysis quickly and correctly. The final product is a spatial vector data set, consisting of points, lines and polygons, which contains attributes with further information and geometry. This paper demonstrates that mobile mapping suits a large-scale feature extraction of road infrastructure defects. By its simplicity and flexibility, the presented methodology allows it to be easily adapted to extract further feature types with their attributes. This makes the proposed approach a vital tool for data extraction settings with multiple mobile mapping data analysts, e.g., offline crowdsourcing. KW - Deformation detection KW - engineering KW - visual inspection KW - data analyses KW - mobile mapping KW - GIS Y1 - 2021 U6 - https://doi.org/https://doi.org/10.32604/cmes.2021.016071 VL - 129 IS - 1 SP - 207 EP - 226 ER - TY - JOUR A1 - Selenski, Jürgen A1 - Reuß, Oliver A1 - Roth, Jonas A1 - Händler, Verena A1 - Badecki, Tomasz A1 - Schirmer, Uwe A1 - Bogner, Markus A1 - Wagner, Andreas A1 - Brunn, Ansgar ED - Kersten, Thomas P. ED - Tilly, Nora T1 - Integration von 3D-Laserscanning in die Rohstoffgewinnung im Untertagebau JF - DGPF-Jahrestagung 2023 Y1 - 2023 UR - https://www.dgpf.de/src/tagung/jt2023/start.html SP - 251 EP - 262 CY - München ER - TY - CHAP A1 - Händler, Verena A1 - Reuß, Oliver A1 - Roth, Jonas A1 - Selenski, Jürgen A1 - Brunn, Ansgar T1 - Punktwolkenbasierte 3D-Vermessung für KMU in Handwerk und Bauwesen T2 - Publikationen der Deutschen Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation e.V. N2 - Hochschulen für angewandte Wissenschaften entwickeln beständig die Lehre nicht nur für die eigenen Studierenden, sondern auch die Methoden für den Wissenstransfer in die Unternehmen weiter. Neue didaktische Konzepte werden für anstehende Fachthemen ausprobiert. Im Rahmen des Projekts „Frühe Digitalisierung technischer Planungsprozesse im Bauwesen und Handwerk für kleine und mittlere Unternehmen“ (DiTeP4KMU) sollen daher aktuelle Methoden der Wissensvermittlung (Online Lehrangebote, Blended Learning sowie hybride Lehrveranstaltungsformen) in die berufsbegleitende Weiterbildung übertragen und realisiert werden. Das Projekt ist eine Fortsetzung und Erweiterung der bereits an der Hochschule für angewandte Wissenschaften Würzburg-Schweinfurt umgesetzten Projekte „Digitale Photogrammetrie und Bildverarbeitung für kleine und mittlere Unternehmen (DiPhoBi4KMU)“ und „Mobile 3D Vermessung für kleine und mittlere Unternehmen“ (MV-3D4KMU). Ziel des aktuellen Projekts ist die Prozessoptimierung in KMU durch mobile 3D-Vermessung anhand hybrider Wissensvermittlung in Form von E-Learning Angeboten sowie Präsenzveranstaltungen in Form von Netzwerktreffen und Aktionen. Der fachliche Fokus liegt dabei auf der stärkeren Verbreitung der 3D-Daten für alltägliche Aufgaben - insbesondere der schnell zu generierenden 3D-Punktwolken durch moderne Messsysteme - in die Arbeitsprozesse im Bauwesen und Handwerk, in Zusammenarbeit mit den beteiligten Unternehmen. Die Erfahrungen in dem Projekt zeigen bereits nach ca. sechs Monaten ein großes Interesse und bestätigen die Konzeption des Projektentwurfs. Y1 - 2022 UR - https://www.dgpf.de/src/tagung/jt2022/proceedings/proceedings/paper/06_DLT2022_Haendler_et_al.pdf VL - 30 ER - TY - CHAP A1 - Meyer, Theresa A1 - Brunn, Ansgar T1 - 3D Point Clouds in PostgreSQL/PostGIS for Applications in GIS and Geodesy T2 - Proceedings of the 5th International Conference on Geographical Information Systems Theory, Applications and Management N2 - Besides the common approach of an exclusively file based management of 3D point clouds, meanwhile it is possible to store and process this special type of massive geodata within spatial database systems. Users benefit from the general advantages of database solutions and especially from the potentials of a combined analysis of original 3D point clouds, 2D rasters, 3D voxel stacks and 2D and 3D vector data in order to gain valuable geo- information. This paper describes the integration of 3D point clouds into an open source PostgreSQL/PostGIS database using the Pointcloud extension and functions of the Point Data Abstraction Library (PDAL). The focus is on performing three-dimensional spatial queries and the evaluation of different tiling methods for the organization of 3D point clouds into table rows, regarding memory space, performance of spatial queries and effects on interactions between point clouds and other GIS features within the database. A new approach for an optimized point cloud tiling, considering the individual geometric characteristic of a 3D point cloud, is presented. The results show that an individually selected storage structure for a point cloud is crucial for low memory consumption and high-performance 3D queries in PostGIS applications, taking account of its three-dimensional spatial extent and point density. KW - 3D Point Clouds KW - Point Cloud Tiling KW - Geodatabase KW - GIS KW - 3D Applications Y1 - 2019 UR - https://pdfs.semanticscholar.org/7cb5/fe8840189bc7b04bbdf2d324cca64892559a.pdf SN - 978-989-758-371-1 U6 - https://doi.org/10.5220/0007840901540163 SP - 154 EP - 163 PB - SCITEPRESS – Science and Technology Publications ER - TY - JOUR A1 - Chizhova, Maria A1 - Gurianov, Andrey A1 - Hess, Mona A1 - Luhmann, Thomas A1 - Brunn, Ansgar A1 - Stilla, Uwe T1 - Semantic segmentation of building elements using point cloud hashing JF - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences N2 - For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud elements are determined using probabilistic networks and scene databases. The proposed semantic segmentation method is based on the psychological human interpretation of geometric objects, especially on fundamental rules of primary comprehension. Starting from these rules the buildings could be quite well and simply classified by a human operator (e.g. architect) into different building types and structural elements (dome, nave, transept etc.), including particular building parts which are visually detected. The key part of the procedure is a novel method based on hashing where point cloud projections are transformed into binary pixel representations. A segmentation approach released on the example of classical Orthodox churches is suitable for other buildings and objects characterized through a particular typology in its construction (e.g. industrial objects in standardized enviroments with strict component design allowing clear semantic modelling). KW - semantic segmentation KW - hashing KW - Orthodox church KW - point clouds Y1 - 1018 U6 - https://doi.org/https://doi.org/10.5194/isprs-archives-XLII-2-241-2018 VL - VLII-2 SP - 241 EP - 250 ER - TY - JOUR A1 - Chizhova, Maria A1 - Korovin, Dmitriyi A1 - Gurianov, Andrey A1 - Brodovskii, Maxim A1 - Brunn, Ansgar A1 - Stilla, Uwe A1 - Luhmann, Thomas T1 - Probabilistic Reconstruction of orthodox Churches from precision Point Clouds using Bayesian Networks and Cellular Automata JF - The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences N2 - The point cloud interpretation and reconstruction of 3d-buildings from point clouds has already been treated for a few decades. There are many articles which consider the different methods and workows of the automatic detection and reconstruction of geometrical objects from point clouds. Each method is suitable for the special geometry type of object or sensor. General approaches are rare. In our work we present an algorithm which develops the optimal process sequence of the automatic search, detection and reconstruction of buildings and building components from a point cloud. It can be used for the detection of the set of geometric objects to be reconstructed, independent of its destruction. In a simulated example we reconstruct a complete Russian-orthodox church starting from the set of detected structural components and reconstruct missing components with high probability. KW - reconstruction from point cloud KW - cellular automaton KW - Bayesian network KW - orthodox churches Y1 - 2017 UR - https://www.pf.bgu.tum.de/pub/2017/chizhova_co_stilla_3dvrvca_pap.pdf U6 - https://doi.org/doi:10.5194/isprs-archives-XLII-2-W3-187-2017 VL - VLII-2/W3 SP - 187 EP - 194 ER - TY - JOUR A1 - Dizbadi, Mehran A1 - Safarzadeh, Daniyal A1 - Arastoo, Behrooz A1 - Brunn, Ansgar T1 - Predicting the Areal Development of the City of Mashhad with the Automaton Fuzzy Cell Method JF - World Academy of Science, Engineering and Technology, International Journal of Civil and Architectural Engineering N2 - Rapid and uncontrolled expansion of cities has led to unplanned aerial development. In this way, modeling and predicting the urban growth of a city helps decision-makers. In this study, the aspect of sustainable urban development has been studied for the city of Mashhad. In general, the prediction of urban aerial development is one of the most important topics of modern town management. In this research, using the Cellular Automaton (CA) model and perceptron neural network method with satellite data developed for geo data of Geographic Information Systems (GIS) and presenting a simple and powerful model, a simulation of complex urban processes has been done. In finally our accuracy has been better compared to other researches that have been done in this field and we have slightly improved and optimize the final results approximately %92.1. KW - Urban Modeling KW - sustainable development KW - Fuzzy Cellular Automaton KW - Geo-Information System KW - Perceptron neural network KW - Landsat Y1 - 2022 UR - https://www.researchgate.net/publication/363484716_Predicting_the_areal_development_of_the_city_of_Mashhad_with_the_automaton_fuzzy_cell_method/stats VL - 16 IS - 6 ER - TY - CHAP A1 - Meyer, Theresa A1 - Brunn, Ansgar A1 - Stilla, Uwe T1 - Genauigkeitsbetrachtung voxelbasierter Änderungsdetektion im Gebäudeinnenbereich zur automatisierten Baufortschrittsüberwachung T2 - Publikationen der Deutschen Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation e.V. N2 - Dieser Beitrag handelt von einer Methode zur Änderungsdetektion im Gebäudeinneren, die auf der Diskretisierung des Objektraums durch Voxel basiert. Die Belegung des Voxelraums wird anhand von Punktwolken aus terrestrischem Laserscanning zu verschiedenen Bauphasen ermittelt. Durch die Aufdeckung von Belegungskonflikten zwischen zwei Messepochen wird ermittelt, ob Änderungen an einer bestimmten Stelle aufgetreten sind. Es wird gezeigt, wie sich der Diskretisierungsfehler als Resultat der Voxelisierung auf die noch erreichbare räumliche Auflösung einer Änderungsaussage auswirkt. Am Beispiel von Abbrucharbeiten bei einem Innenumbauprojekt werden die wechselseitigen Auswirkungen von Aufnahmegeometrie, Scanauflösung und Voxelgröße diskutiert. Die Ergebnisse zeigen, dass die Auflösung von 3D-Punktwolken unter Beachtung einiger Anforderungen an die Aufnahmegeometrie bei Innenraum-Messungen ausreicht, um bei gängigen Genauigkeitsanforderungen auf Voxelebene automatisiert strukturelle Änderungen zu beschreiben. Y1 - 2022 UR - https://www.dgpf.de/src/tagung/jt2022/proceedings/proceedings/paper/16_DLT2022_Meyer_et_al.pdf U6 - https://doi.org/10.24407/KXP:1796028584 VL - 30 ER - TY - CHAP A1 - Baetz, Christiane A1 - Uhl, Anna A1 - Brunn, Ansgar T1 - Satellite based Change Detection of the Volyn Region T2 - Proceeding of the Conference on "Socio-geographical factors of the regions development" N2 - Land use in the Volyn region (Ukraine) has changed a lot in the last decade. Change detection basing on satellite images is an appropriate method to show the migration of land use. In this article, a classification of the land use on free satellite is implemented. The procedure should be as automatic as possible. For the optimum accuracy different band combinations and the NDVI are tested. Different methods were compared due to the achieved accuracy and the status of automation. KW - classification KW - change detection KW - Volyn region KW - Sentinel KW - Landsat Y1 - 2018 UR - https://konfgeolutsk.wordpress.com/2018/04/18/satellite-based-change-detection-of-the-volyn-region/ CY - Lutzk ER - TY - JOUR A1 - Dizbadi, Mehran A1 - Arastoo, Behrooz A1 - Toth, Charles A1 - Brunn, Ansgar T1 - Automatic Extraction of Buildings Boundaries Using Satellite Imagery with High Spatial Resolution and Deep Learning Methods JF - FIG-Congress 2023 Y1 - 2023 CY - Orlando (USA) ER - TY - JOUR A1 - Okyere, Franz A1 - Minnich, Thea A1 - Brunn, Ansgar T1 - Implementation of a low-cost Ambulance Management System JF - FIG-Congress 2023 Y1 - 2023 CY - Orlando (USA) ER -