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Termes IGN > sciences naturelles > physique > traitement d'image > photogrammétrie > photogrammétrie numérique > modèle numérique de surface
modèle numérique de surfaceSynonyme(s)modèle numérique d'élévation ;modèle numérique d'altitude ;MNE ;MNA ;DEM MNSVoir aussi |
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UAV-borne, LiDAR-based elevation modelling: a method for improving local-scale urban flood risk assessment / Katerina Trepekli in Natural Hazards, vol 113 n° 1 (August 2022)
[article]
Titre : UAV-borne, LiDAR-based elevation modelling: a method for improving local-scale urban flood risk assessment Type de document : Article/Communication Auteurs : Katerina Trepekli, Auteur ; Thomas Balstrøm, Auteur ; Thomas Friborg, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 423 - 451 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] antenne GNSS
[Termes IGN] centrale inertielle
[Termes IGN] faisceau laser
[Termes IGN] Ghana
[Termes IGN] inondation
[Termes IGN] modèle de simulation
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] risque naturel
[Termes IGN] semis de points
[Termes IGN] Triangulated Irregular Network
[Termes IGN] zone urbaineRésumé : (auteur) In this study, we present the first findings of the potential utility of miniaturized light and detection ranging (LiDAR) scanners mounted on unmanned aerial vehicles (UAVs) for improving urban flood modelling and assessments at the local scale. This is done by generating ultra-high spatial resolution digital terrain models (DTMs) featuring buildings and urban microtopographic structures that may affect floodwater pathways (DTMbs). The accuracy and level of detail of the flooded areas, simulated by a hydrologic screening model (Arc-Malstrøm), were vastly improved when DTMbs of 0.3 m resolution representing three urban sites surveyed by a UAV-LiDAR in Accra, Ghana, were used to supplement a 10 m resolution DTM covering the region’s entire catchment area. The generation of DTMbs necessitated the effective classification of UAV-LiDAR point clouds using a morphological and a triangulated irregular network method for hilly and flat landscapes, respectively. The UAV-LiDAR data enabled the identification of archways, boundary walls and bridges that were critical when predicting precise run-off courses that could not be projected using the coarser DTM only. Variations in a stream’s geometry due to a one-year time gap between the satellite-based and UAV-LiDAR data sets were also observed. The application of the coarser DTM produced an overestimate of water flows equal to 15% for sloping terrain and up to 62.5% for flat areas when compared to the respective run-offs simulated from the DTMbs. The application of UAV-LiDAR may enhance the effectiveness of urban planning by projecting precisely the locations, extents and run-offs of flooded areas in dynamic urban settings. Numéro de notice : A2022-704 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article DOI : 10.1007/s11069-022-05308-9 Date de publication en ligne : 22/03/2022 En ligne : https://doi.org/10.1007/s11069-022-05308-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101567
in Natural Hazards > vol 113 n° 1 (August 2022) . - pp 423 - 451[article]Uncertainty interval estimates for computing slope and aspect from a gridded digital elevation model / Carlos López-Vázquez in International journal of geographical information science IJGIS, vol 36 n° 8 (August 2022)
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Titre : Uncertainty interval estimates for computing slope and aspect from a gridded digital elevation model Type de document : Article/Communication Auteurs : Carlos López-Vázquez, Auteur Année de publication : 2022 Article en page(s) : pp 1601 - 1628 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] géomorphométrie
[Termes IGN] incertitude des données
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] penteRésumé : (auteur) The first order derivatives of a Digital Elevation Model (DEM) defined over a regular grid are usually computed without an uncertainty estimate. The standard procedure involves a compact 3 × 3 window. Using a Taylor expansion, an uncertainty interval for each partial derivative as a function of the cell size was devised using two estimates, either of different resolution or of different order. The intervals for slope and aspect can be derived afterwards. We carried out an experiment comparing some different estimates of the slope and aspect over a synthetic surface representative of a real topography and amenable to offer an exact derivative. The partial derivatives were numerically estimated with four different procedures: the Simple procedure defined by Jones over a 2 × 2 window, the Evans–Young procedure using a centered difference over a 3 × 3 window, and using a 5 × 5 window both with an extrapolated Evans–Young procedure and the expression due to Florinsky. The results confirm that intervals for both slope and aspect always included the exact value even after drastically increasing the cell size. Finally, a real case with an integer-valued DEM was considered, illustrating the combined effect of Representation and Truncation error. Numéro de notice : A2022-623 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2063294 Date de publication en ligne : 07/06/2022 En ligne : https://doi.org/10.1080/13658816.2022.2063294 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101367
in International journal of geographical information science IJGIS > vol 36 n° 8 (August 2022) . - pp 1601 - 1628[article]Exploring the vertical dimension of street view image based on deep learning: a case study on lowest floor elevation estimation / Huan Ning in International journal of geographical information science IJGIS, vol 36 n° 7 (juillet 2022)
[article]
Titre : Exploring the vertical dimension of street view image based on deep learning: a case study on lowest floor elevation estimation Type de document : Article/Communication Auteurs : Huan Ning, Auteur ; Zhenlong Li, Auteur ; Xinyue Ye, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1317 - 1342 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] détection d'objet
[Termes IGN] distorsion d'image
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] hauteur du bâti
[Termes IGN] image Streetview
[Termes IGN] lever tachéométrique
[Termes IGN] modèle numérique de surface
[Termes IGN] porteRésumé : (auteur) Street view imagery such as Google Street View is widely used in people’s daily lives. Many studies have been conducted to detect and map objects such as traffic signs and sidewalks for urban built-up environment analysis. While mapping objects in the horizontal dimension is common in those studies, automatic vertical measuring in large areas is underexploited. Vertical information from street view imagery can benefit a variety of studies. One notable application is estimating the lowest floor elevation, which is critical for building flood vulnerability assessment and insurance premium calculation. In this article, we explored the vertical measurement in street view imagery using the principle of tacheometric surveying. In the case study of lowest floor elevation estimation using Google Street View images, we trained a neural network (YOLO-v5) for door detection and used the fixed height of doors to measure doors’ elevation. The results suggest that the average error of estimated elevation is 0.218 m. The depthmaps of Google Street View were utilized to traverse the elevation from the roadway surface to target objects. The proposed pipeline provides a novel approach for automatic elevation estimation from street view imagery and is expected to benefit future terrain-related studies for large areas. Numéro de notice : A2022-465 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1981334 Date de publication en ligne : 06/10/2021 En ligne : https://doi.org/10.1080/13658816.2021.1981334 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100970
in International journal of geographical information science IJGIS > vol 36 n° 7 (juillet 2022) . - pp 1317 - 1342[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2022071 SL Revue Centre de documentation Revues en salle Disponible 3D modeling method for dome structure using digital geological map and DEM / Xian-Yu Liu in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)
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Titre : 3D modeling method for dome structure using digital geological map and DEM Type de document : Article/Communication Auteurs : Xian-Yu Liu, Auteur ; An-Bo Li, Auteur ; Hao Chen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 339 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] carte géologique
[Termes IGN] carte stratigraphique
[Termes IGN] courbe de Bézier
[Termes IGN] modèle géologique
[Termes IGN] modèle numérique de surface
[Termes IGN] modélisation 3D
[Termes IGN] structure géologiqueRésumé : (auteur) Geological maps have wide coverage with low acquisition difficulty. When other geological survey data are scarce, they are a valuable source of geological structure information for geological modeling. However, for structures with large deformation, geological map information has difficulty meeting the requirement of its 3D geological modeling. Therefore, this paper takes the dome structure as an example to explore a 3D modeling method based on geological maps, DEM and related geological knowledge. The method includes: (1) adaptively calculating the attitude of points on the stratigraphic boundaries; (2) inferring and generating the bottom boundary of the model from the attitude data of the boundary points; (3) generating the model interface constrained by Bézier curves based on the bottom boundary; (4) generating the top and bottom surfaces of the stratum; and (5) stitching each surface of the geological body to generate the final dome model. Case studies of the dome in Wulongshan in China and the Richat structure in Mauritania show that this method can build a solid model of the dome based only on geological maps and DEM data, whose morphological features are basically consistent with those embodied in the section view or the model generated by traditional methods. Numéro de notice : A2022-482 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi11060339 Date de publication en ligne : 07/06/2022 En ligne : https://doi.org/10.3390/ijgi11060339 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100895
in ISPRS International journal of geo-information > vol 11 n° 6 (June 2022) . - n° 339[article]Physical modelling of Nanda Devi National Park, a natural world heritage site, from GIS data / Sanat Agrawal in Cartographica, vol 57 n° 2 (Summer 2022)
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Titre : Physical modelling of Nanda Devi National Park, a natural world heritage site, from GIS data Type de document : Article/Communication Auteurs : Sanat Agrawal, Auteur ; Akshay Jain, Auteur Année de publication : 2022 Article en page(s) : pp 179 - 194 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] conservation du patrimoine
[Termes IGN] Himalaya
[Termes IGN] Inde
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle physique
[Termes IGN] patrimoine naturel
[Termes IGN] QGIS
[Termes IGN] site
[Termes IGN] surface du sol
[Termes IGN] système d'information géographiqueRésumé : (auteur) A methodology has been developed to create a physical model of the Nanda Devi National Park (NDNP), a Natural World Heritage Site (NWHS), by additive fabrication, to facilitate effective communication among the stakeholders for conservation management. The GIS data of a terrain give elevation values on the surface of a terrain only and lack 3D definition. The DEM ASCII XYZ file format is converted into a 3D STL file with walls and a base. Gaps and singularities in the data are taken care of. There is ample scope for aiding conservation management and restoration of NWHS sites using additive manufacturing (AM). A physical model of the NDNP was created using the methodology. The model holds very high value for long-term monitoring of the NWHS and the Himalayas. The physical model of the NDNP can serve as an effective medium of communication for conservation management. Physical models of the glacial basins or the Nanda Devi peak will provide further value. The research work can be extended to making models of the NDNP of larger sizes or by focusing on smaller region of the NDNP in consultation with the stakeholders. Numéro de notice : A2022-636 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart-2021-0025 Date de publication en ligne : 25/06/2022 En ligne : https://doi.org/10.3138/cart-2021-0025 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101426
in Cartographica > vol 57 n° 2 (Summer 2022) . - pp 179 - 194[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 031-2022021 RAB Revue Centre de documentation En réserve L003 Disponible True orthophoto generation based on unmanned aerial vehicle images using reconstructed edge points / Mojdeh Ebrahimikia in Photogrammetric record, vol 37 n° 178 (June 2022)PermalinkVegetation cover mapping from RGB webcam time series for land surface emissivity retrieval in high mountain areas / Benedikt Hiebl in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)PermalinkDetection and mapping of snow avalanche debris from Western Himalaya, India using remote sensing satellite images / Kamal Kant Singh in Geocarto international, vol 37 n° 9 ([15/05/2022])PermalinkEfficient convolutional neural architecture search for LiDAR DSM classification / Aili Wang in IEEE Transactions on geoscience and remote sensing, vol 60 n° 5 (May 2022)PermalinkAssessing surface drainage conditions at the street and neighborhood scale: A computer vision and flow direction method applied to lidar data / Cheng-Chun Lee in Computers, Environment and Urban Systems, vol 93 (April 2022)PermalinkCharacterizing stream morphological features important for fish habitat using airborne laser scanning data / Spencer Dakin Kuiper in Remote sensing of environment, vol 272 (April 2022)PermalinkDirect photogrammetry with multispectral imagery for UAV-based snow depth estimation / Kathrin Maier in ISPRS Journal of photogrammetry and remote sensing, vol 186 (April 2022)PermalinkSimulating future LUCC by coupling climate change and human effects based on multi-phase remote sensing data / Zihao Huang in Remote sensing, vol 14 n° 7 (April-1 2022)PermalinkAn approach to extracting digital elevation model for undulating and hilly terrain using de-noised stereo images of Cartosat-1 sensor / Litesh Bopche in Applied geomatics, vol 14 n° 1 (March 2022)PermalinkAutomatic extraction of building geometries based on centroid clustering and contour analysis on oblique images taken by unmanned aerial vehicles / Leilei Zhang in International journal of geographical information science IJGIS, vol 36 n° 3 (March 2022)PermalinkComparaison des images satellite et aériennes dans le domaine de la détection d’obstacles à la navigation aérienne et de leur mise à jour / Olivier de Joinville in XYZ, n° 170 (mars 2022)PermalinkLiDAR-based method for analysing landmark visibility to pedestrians in cities: case study in Kraków, Poland / Krystian Pyka in International journal of geographical information science IJGIS, vol 36 n° 3 (March 2022)PermalinkMonitoring coastal vulnerability by using DEMs based on UAV spatial data / Antonio Minervino Amodio in ISPRS International journal of geo-information, vol 11 n° 3 (March 2022)PermalinkUsing vertices of a triangular irregular network to calculate slope and aspect / Guanghui Hu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)Permalink3D modeling of urban area based on oblique UAS images - An end-to-end pipeline / Valeria-Ersilia Oniga in Remote sensing, vol 14 n° 2 (January-2 2022)PermalinkSoil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS / Sumedh R. Kashiwar in Natural Hazards, vol 110 n° 2 (January 2022)PermalinkPermalinkPermalinkAutomatic algorithm for georeferencing historical-to-nowadays aerial images acquired in natural environments / Daniela Craciun (2022)PermalinkDéveloppement d’outils et de méthodes permettant l’acquisition, le traitement et la diffusion de données issues de levés par drone / Guillaume Feuillatre (2022)Permalink