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Determination of building flood risk maps from LiDAR mobile mapping data / Yu Feng in Computers, Environment and Urban Systems, vol 93 (April 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 93 (April 2022) . - n° 101759 Titre : Determination of building flood risk maps from LiDAR mobile mapping data Type de document : Article/Communication Auteurs : Yu Feng, Auteur ; Qing Xiao, Auteur ; Claus Brenner, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101759 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] apprentissage profond [Termes IGN] bâtiment [Termes IGN] cartographie d'urgence [Termes IGN] cartographie des risques [Termes IGN] classification semi-dirigée [Termes IGN] détection d'objet [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction de traits caractéristiques [Termes IGN] façade [Termes IGN] infiltration [Termes IGN] inondation [Termes IGN] modèle de simulation [Termes IGN] prévention des risques [Termes IGN] risque naturel [Termes IGN] segmentation sémantique Résumé : (auteur) With increasing urbanization, flooding is a major challenge for many cities today. Based on forecast precipitation, topography, and pipe networks, flood simulations can provide early warnings for areas and buildings at risk of flooding. Basement windows, doors, and underground garage entrances are common places where floodwater can flow into a building. Some buildings have been prepared or designed considering the threat of flooding, but others have not. Therefore, knowing the heights of these facade openings helps to identify places that are more susceptible to water ingress. However, such data is not yet readily available in most cities. Traditional surveying of the desired targets may be used, but this is a very time-consuming and laborious process. Instead, mobile mapping using LiDAR (light detection and ranging) is an efficient tool to obtain a large amount of high-density 3D measurement data. To use this method, it is required to extract the desired facade openings from the data in a fully automatic manner. This research presents a new process for the extraction of windows and doors from LiDAR mobile mapping data. Deep learning object detection models are trained to identify these objects. Usually, this requires to provide large amounts of manual annotations. In this paper, we mitigate this problem by leveraging a rule-based method. In a first step, the rule-based method is used to generate pseudo-labels. A semi-supervised learning strategy is then applied with three different levels of supervision. The results show that using only automatically generated pseudo-labels, the learning-based model outperforms the rule-based approach by 14.6% in terms of F1-score. After five hours of human supervision, it is possible to improve the model by another 6.2%. By comparing the detected facade openings' heights with the predicted water levels from a flood simulation model, a map can be produced which assigns per-building flood risk levels. Thus, our research provides a new geographic information layer for fine-grained urban emergency response. This information can be combined with flood forecasting to provide a more targeted disaster prevention guide for the city's infrastructure and residential buildings. To the best of our knowledge, this work is the first attempt to achieve such a large scale, fine-grained building flood risk mapping. Numéro de notice : A2022-196 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101759 Date de publication en ligne : 01/02/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101759 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99964 [article]

Enhancing the resolution of urban digital terrain models using mobile mapping systems / Yu Feng in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-4/W6 (October 2018)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol IV-4/W6 (October 2018) . - pp 11 - 18 Titre : Enhancing the resolution of urban digital terrain models using mobile mapping systems Type de document : Article/Communication Auteurs : Yu Feng, Auteur ; Claus Brenner, Auteur ; Monika Sester, Auteur Année de publication : 2018 Conférence : 3D GeoInfo 2018, ISPRS 13th international conference 01/10/2018 02/10/2018 Delft Pays-Bas ISPRS OA Annals Article en page(s) : pp 11 - 18 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] écoulement des eaux [Termes IGN] Hanovre (Basse-Saxe) [Termes IGN] modèle numérique de terrain [Termes IGN] semis de points [Termes IGN] zone urbaine Résumé : (auteur) Digital Terrain Models (DTMs) are essential surveying products for terrain based analyses, especially for overland flow modelling. Nowadays, many high resolution DTM products are generated by Airborne Laser Scanning (ALS). However, DTMs with even higher resolution are of great interest for a more precise overland flow modelling in urban areas. With the help of mobile mapping techniques, we can obtain much denser measurements of the ground in the vicinity of roads. In this research, a study area in Hannover, Germany was measured by a mobile mapping system. Point clouds from 485 scan strips were aligned and a DTM was extracted. In order to achieve a product with completeness, this mobile mapping produced DTM was then merged and adapted with a DTM product with 0.5 m resolution from a mapping agency. Systematic evaluations have been conducted with respect to the height accuracy of the DTM products. The results show that the final DTM product achieved a higher resolution (0.1 m) near the roads while essentially maintaining its height accuracy. Numéro de notice : A2018-291 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/isprs-annals-IV-4-W6-11-2018 Date de publication en ligne : 12/09/2018 En ligne : https://doi.org/10.5194/isprs-annals-IV-4-W6-11-2018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100955 [article]

Generating a hazard map of dynamic objects using lidar mobile mapping / Alexander Schlichting in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 12 (December 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 12 (December 2016) . - pp 967 - 972 Titre : Generating a hazard map of dynamic objects using lidar mobile mapping Type de document : Article/Communication Auteurs : Alexander Schlichting, Auteur ; Claus Brenner, Auteur Année de publication : 2016 Article en page(s) : pp 967 - 972 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] aléa [Termes IGN] cartographie cadastrale [Termes IGN] cartographie des risques [Termes IGN] détection de piéton [Termes IGN] processus [Termes IGN] semis de points [Termes IGN] système de numérisation mobile [Termes IGN] véhicule sans pilote Résumé : (auteur) One of the hardest problems for future self-driving cars is to predict hazardous situations involving pedestrians and cyclists. Human drivers solve this problem typically by having a deeper understanding of the scene. The technical equivalent of this is to provide a hazard map, which serves as a prior for self-driving cars, enabling them to adjust driving speed and processing thresholds. In this paper, we present a method to derive such a hazard map using lidar mobile mapping. Pedestrians and cyclists are obtained from a sequence of point clouds by segmentation and classification. Their locations are then accumulated in a grid map, which serves as a "heat map" for possible hazardous situations. To demonstrate our approach, we generated a map using lidar mobile mapping, obtained by twelve measurement campaigns in Hanover (Germany). Our results show different outcomes for the city center, residential areas, busy roads, and road junctions. Numéro de notice : A2016-985 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.12.967 En ligne : https://doi.org/10.14358/PERS.82.12.967 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83701 [article]

Generative models for road network reconstruction / Colin Kuntzsch in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 5-6 (May - June 2016) . - pp 1012 - 1039 Titre : Generative models for road network reconstruction Type de document : Article/Communication Auteurs : Colin Kuntzsch, Auteur ; Monika Sester, Auteur ; Claus Brenner, Auteur Année de publication : 2016 Article en page(s) : pp 1012 - 1039 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] appariement de données localisées [Termes IGN] coordonnées GPS [Termes IGN] itinéraire [Termes IGN] méthode de Monte-Carlo par chaînes de Markov [Termes IGN] modèle cartographique [Termes IGN] réalité de terrain [Termes IGN] reconstruction d'itinéraire ou de trajectoire [Termes IGN] relation topologique [Termes IGN] réseau routier [Termes IGN] trafic routier Résumé : (Auteur) This work aims at the inference of traffic networks from GPS trajectories. We perform geometry and topology reconstruction of the network in a multistep process. Our main contributions are the formulation of an explicit intersection model with a score function that accounts for consistency with the raw tracking data, as well as for a topology prior and the search for the best model by maximization of this score function using a Markov chain Monte Carlo sampler. We demonstrate the viability of our model-based approach with experiments on GPS data sets of varying size and data quality, followed by a comparison with results achieved by alternative, heuristic approaches. Numéro de notice : A2016-293 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1092151 En ligne : https://doi.org/10.1080/13658816.2015.1092151 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80872 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2016032	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-2016031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A generative statistical approach to automatic 3D building roof reconstruction from laser scanning data / Hai Huang in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 79 (May 2013) . - pp 29 - 53 Titre : A generative statistical approach to automatic 3D building roof reconstruction from laser scanning data Type de document : Article/Communication Auteurs : Hai Huang, Auteur ; Claus Brenner, Auteur ; Monika Sester, Auteur Année de publication : 2013 Article en page(s) : pp 29 - 53 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] bibliothèque de formes [Termes IGN] chaîne de Markov [Termes IGN] détection du bâti [Termes IGN] données lidar [Termes IGN] primitive géométrique [Termes IGN] reconstruction 3D du bâti [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] toit Résumé : (Auteur) This paper presents a generative statistical approach to automatic 3D building roof reconstruction from airborne laser scanning point clouds. In previous works, bottom-up methods, e.g., points clustering, plane detection, and contour extraction, are widely used. Due to the data artefacts caused by tree clutter, reflection from windows, water features, etc., the bottom-up reconstruction in urban areas may suffer from a number of incomplete or irregular roof parts. Manually given geometric constraints are usually needed to ensure plausible results. In this work we propose an automatic process with emphasis on top-down approaches. The input point cloud is firstly pre-segmented into subzones containing a limited number of buildings to reduce the computational complexity for large urban scenes. For the building extraction and reconstruction in the subzones we propose a pure top-down statistical scheme, in which the bottom-up efforts or additional data like building footprints are no more required. Based on a predefined primitive library we conduct a generative modeling to reconstruct roof models that fit the data. Primitives are assembled into an entire roof with given rules of combination and merging. Overlaps of primitives are allowed in the assembly. The selection of roof primitives, as well as the sampling of their parameters, is driven by a variant of Markov Chain Monte Carlo technique with specified jump mechanism. Experiments are performed on data-sets of different building types (from simple houses, high-rise buildings to combined building groups) and resolutions. The results show robustness despite the data artefacts mentioned above and plausibility in reconstruction. Numéro de notice : A2013-232 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.02.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.02.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32370 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2013051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Aggregation of LoD 1 building models as an optimization problem / R. Guercke in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 2 (March - April 2011)  

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A framework for the generalization of 3D city models / R. Guercke in Bulletin des sciences géographiques, n° 23 (juin 2009)

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Coarse orientation of terrestrial laser scans in urban environments / Claus Brenner in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 1 (January - February 2008)  

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Continuous generalization for fast and smooth visualization on small displays / Monika Sester in GIS Geo-Informations-Systeme, vol 2004 n° 9 (September 2004)

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Dreidimensionale Gebäuderekonstruktion aus digitalen Oberflächenmodellen und Grundrissen / Claus Brenner (2000)  

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Unwrapping of detailed surface models: generation of virtual city models using laser altimetry, 2D GIS and CAD / Norbert Haala in GIM international, vol 13 n° 3 (March 1999)

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A multi-sensor approach to creating accurate virtual environments / Sabry F. El Hakim in ISPRS Journal of photogrammetry and remote sensing, vol 53 n° 6 (November - December 1998)  

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