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Assessment of ArcGIS based extraction of geoidal undulation compared to National Geospatial Intelligence Agency (NGA) model – A case study / Sher Muhammad in Journal of applied geodesy, vol 14 n° 1 (January 2020)  

Public [article]  inJournal of applied geodesy > vol 14 n° 1 (January 2020) . - pp 77 - 81 Titre : Assessment of ArcGIS based extraction of geoidal undulation compared to National Geospatial Intelligence Agency (NGA) model – A case study Type de document : Article/Communication Auteurs : Sher Muhammad, Auteur ; Lide Tian, Auteur Année de publication : 2020 Article en page(s) : pp 77 - 81 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes descripteurs IGN] altitude orthométrique [Termes descripteurs IGN] détection d'erreur [Termes descripteurs IGN] Earth Gravity Model 1996 [Termes descripteurs IGN] ellipsoïde (géodésie) [Termes descripteurs IGN] géoïde altimétrique [Termes descripteurs IGN] Himalaya [Termes descripteurs IGN] interpolation [Termes descripteurs IGN] Matlab [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] niveau moyen des mers [Termes descripteurs IGN] Tibet Résumé : (auteur) Global Navigation Satellite System (GNSS) and remote sensing Digital Elevation Models (DEMs) represent earth’s surface elevation with reference to ellipsoid and orthometric heights. Proper estimation of the geoid (difference of ellipsoid and orthometric heights) is necessary before comparing data referenced to the different vertical datum. In this paper, an error in estimating EGM96 orthometric height is highlighted, verified by NGA/NASA developed model and MATLAB®. A significant error was found in the ArcGIS derived EGM96 orthometric heights range between ±6.9 meters. In addition, interpolation of low-resolution geoid data also produces significant biases depending on geographic location and the number of the interpolation data point. The bias was maximum negative in the central part of Tibetan Plateau and Himalaya. Therefore, estimation of orthometric height similar to NGA/NASA model precision is necessary for comparison of DEMs for natural resources management, 3D modelling and glaciers mass balance mainly in the mountainous regions. Numéro de notice : A2020-041 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0030 En ligne : https://doi.org/10.1515/jag-2019-0030 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94512 [article]

Inside the ice shelf: using augmented reality to visualise 3D lidar and radar data of Antarctica / Alexandra L. Boghosian in Photogrammetric record, vol 34 n° 168 (December 2019)  

Public [article]  inPhotogrammetric record > vol 34 n° 168 (December 2019) . - pp 346 - 364 Titre : Inside the ice shelf: using augmented reality to visualise 3D lidar and radar data of Antarctica Type de document : Article/Communication Auteurs : Alexandra L. Boghosian, Auteur ; Martin J. Pratt, Auteur ; Maya A. Becker, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 346 - 364 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] Antarctique [Termes descripteurs IGN] banquise [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] glace de mer [Termes descripteurs IGN] GNSS-INS [Termes descripteurs IGN] image radar [Termes descripteurs IGN] Matlab [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] pas d'échantillonnage au sol [Termes descripteurs IGN] réalité augmentée [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] travail coopératif [Termes descripteurs IGN] VRML Résumé : (auteur) From 2015 to 2017, the ROSETTA‐Ice project comprehensively mapped Antarctica's Ross Ice Shelf using IcePod, a newly developed aerogeophysical platform. The campaign imaged the ice‐shelf surface with lidar and its internal structure with ice‐penetrating radar. The ROSETTA‐Ice data was combined with pre‐existing ice surface and bed topography digital elevation models to create the first augmented reality (AR) visualisation of the Antarctic Ice Sheet, using the Microsoft HoloLens. The ROSETTA‐Ice datasets support cross‐disciplinary science that aims to understand 4D processes, namely the change of 3D ice‐shelf structures over time. The work presented here uses AR to visualise this dataset in 3D and highlights how AR can be simultaneously a useful research tool for interdisciplinary geoscience as well as an effective device for science communication education. Numéro de notice : A2019-575 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12298 date de publication en ligne : 23/12/2019 En ligne : https://doi.org/10.1111/phor.12298 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94455 [article]

sUAS-based remote rensing of river discharge using thermal particle image velocimetry and bathymetric lidar / Paul J. Kinzel in Remote sensing, vol 11 n° 19 (October 2019)  

Public [article]  inRemote sensing > vol 11 n° 19 (October 2019) . - 19 p. Titre : sUAS-based remote rensing of river discharge using thermal particle image velocimetry and bathymetric lidar Type de document : Article/Communication Auteurs : Paul J. Kinzel, Auteur ; Carl J. Legleiter, Auteur Année de publication : 2019 Article en page(s) : 19 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] bathymétrie laser [Termes descripteurs IGN] Colorado (Etats-Unis) [Termes descripteurs IGN] débit [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] image captée par drone [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] lidar bathymétrique [Termes descripteurs IGN] Matlab [Termes descripteurs IGN] rivière [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] surveillance hydrologique [Termes descripteurs IGN] vitesse Résumé : (auteur) This paper describes a non-contact methodology for computing river discharge based on data collected from small Unmanned Aerial Systems (sUAS). The approach is complete in that both surface velocity and channel geometry are measured directly under field conditions. The technique does not require introducing artificial tracer particles for computing surface velocity, nor does it rely upon the presence of naturally occurring floating material. Moreover, no prior knowledge of river bathymetry is necessary. Due to the weight of the sensors and limited payload capacities of the commercially available sUAS used in the study, two sUAS were required. The first sUAS included mid-wave thermal infrared and visible cameras. For the field evaluation described herein, a thermal image time series was acquired and a particle image velocimetry (PIV) algorithm used to track the motion of structures expressed at the water surface as small differences in temperature. The ability to detect these thermal features was significant because the water surface lacked floating material (e.g., foam, debris) that could have been detected with a visible camera and used to perform conventional Large-Scale Particle Image Velocimetry (LSPIV). The second sUAS was devoted to measuring bathymetry with a novel scanning polarizing lidar. We collected field measurements along two channel transects to assess the accuracy of the remotely sensed velocities, depths, and discharges. Thermal PIV provided velocities that agreed closely ( R2 = 0.82 and 0.64) with in situ velocity measurements from an acoustic Doppler current profiler (ADCP). Depths inferred from the lidar closely matched those surveyed by wading in the shallower of the two cross sections ( R2 = 0.95), but the agreement was not as strong for the transect with greater depths ( R2 = 0.61). Incremental discharges computed with the remotely sensed velocities and depths were greater than corresponding ADCP measurements by 22% at the first cross section and Numéro de notice : A2019-554 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs11192317 date de publication en ligne : 05/10/2019 En ligne : https://doi.org/10.3390/rs11192317 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94207 [article]

Evaluation of global geopotential models: a case study for India / Ropesh Goyal in Survey review, vol 51 n° 368 (September 2019)  

Public [article]  inSurvey review > vol 51 n° 368 (September 2019) . - pp 402 - 412 Titre : Evaluation of global geopotential models: a case study for India Type de document : Article/Communication Auteurs : Ropesh Goyal, Auteur ; Onkar Dikshit, Auteur ; Nagarajan Balasubramania, Auteur Année de publication : 2019 Article en page(s) : pp 402 - 412 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes descripteurs IGN] analyse multicritère [Termes descripteurs IGN] Inde [Termes descripteurs IGN] Matlab [Termes descripteurs IGN] modèle de géopotentiel [Termes descripteurs IGN] modèle de géopotentiel local [Termes descripteurs IGN] réseau altimétrique national Résumé : (Auteur) This paper aims to identify most suitable global geopotential model (GGM) for India, by comparing 15 GGMs developed through 1996 to 2017. The GGM derived geoid undulation values are compared with the geometrical undulation values obtained from GNSS/levelling data on Indian vertical datum. A correction term is added to the computed GGM derived geoid undulation value after fitting three-, four-, five- and seven-parameter models to account for bias and tilt between local geometric Indian vertical datum and global gravimetric vertical datum. The results indicate that EGM2008 model is the best GGM available for India with root-mean-square error (RMSE) of 0.28 m, without model fitting. However, after considering the systematic errors in the two datums with seven-parameter model, GECO GGM has shown significantly better results with RMSE of 0.19 m for India. Numéro de notice : A2019-366 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1468537 date de publication en ligne : 11/05/2018 En ligne : https://doi.org/10.1080/00396265.2018.1468537 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93472 [article]

Shadow detection and correction using a combined 3D GIS and image processing approach / Safa Ridene in Revue internationale de géomatique, vol 29, n° 3 - 4 (juillet - décembre 2019)  

Public [article]  inRevue internationale de géomatique > vol 29, n° 3 - 4 (juillet - décembre 2019) . - pp 241 - 253 Titre : Shadow detection and correction using a combined 3D GIS and image processing approach Type de document : Article/Communication Auteurs : Safa Ridene, Auteur ; Reda Yaagoubi, Auteur ; Imane Sebari, Auteur ; Audrey Alajouanine, Auteur Année de publication : 2019 Article en page(s) : pp 241 - 253 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] détection d'ombre [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] Matlab [Termes descripteurs IGN] ModelBuilder [Termes descripteurs IGN] orthophotographie [Termes descripteurs IGN] SIG 3D [Termes descripteurs IGN] Toulouse Résumé : (Auteur) While shadow can give useful information about size and shape of objects, it can pose problems in feature detection and object detection, thereby, it represents one of the major perturbator phenomenons frequently occurring on images and unfortunately, it is inevitable. “Shadows may lead to the failure of image analysis processes and also cause a poor quality of information which in turn leads to problems in implementation of algorithms.” (Mahajan and Bajpayee, 2015). It also affects multiple image analysis applications, whereby shadow cast by buildings deteriorate the spectral values of the surfaces. Therefore, its presence causes a deterioration in the visual image's quality and limits the information that the former could give. Ignoring the existence of shadows in images may cause serious problems in various visual processing applications such as false objects detection. In this context, many researches have been conducted through years. However, it is still a challenge for analysts all over the world to find a fully automated and efficient method for shadow removal from images. Numéro de notice : A2019-640 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3166/rig.2019.00091 date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.3166/rig.2019.00091 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95649 [article]

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