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An improved constrained simultaneous iterative reconstruction technique for ionospheric tomography / Yi Bin Yao in GPS solutions, Vol 24 n° 3 (July 2020)  

Public [article]  inGPS solutions > Vol 24 n° 3 (July 2020) Titre : An improved constrained simultaneous iterative reconstruction technique for ionospheric tomography Type de document : Article/Communication Auteurs : Yi Bin Yao, Auteur ; Changzhi Zhai, Auteur ; Jian Kong, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] interpolation [Termes descripteurs IGN] modèle ionosphérique [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] teneur totale en électrons [Termes descripteurs IGN] tomographie [Termes descripteurs IGN] voxel Résumé : (auteur) Global Navigation Satellite System (GNSS) is now widely used for continuous ionospheric observations. Three-dimensional computerized ionospheric tomography (3DCIT) is an important tool for the reconstruction of electron density distributions in the ionosphere through effective use of the GNSS data. More specifically, the 3DCIT technique is able to resolve the three-dimensional electron density distributions over the reconstructed area based on the GNSS slant total electron content (STEC) observations. We present an Improved Constrained Simultaneous Iterative Reconstruction Technique (ICSIRT) algorithm that differs from the traditional ionospheric tomography methods in 3 ways. First, the ICSIRT computes the electron density corrections based on the product of the intercept and electron density within voxels so that the assignment of corrections at different heights becomes more reasonable. Second, an Inverse Distance Weighted (IDW) interpolation is used to restrict the electron density values in the voxels not traversed by GNSS rays, thereby ensuring the smoothness of the reconstructed region. Also, to improve the reconstruction accuracy around the HmF2 (the peak height of the F2 layer) altitude, a multiresolution grid is adopted in the vertical direction, with a 10-km resolution from 200 to 420 km and a 50-km resolution at other altitudes. The new algorithm has been applied to the GNSS data over the European and North American regions in different case studies that involve different seasonal conditions as well as a major storm. In the European region experiment, reconstruction results show that the new ICSIRT algorithm can effectively improve the reconstruction of the GNSS data. The electron density profiles retrieved from ICSIRT are much closer to the ionosonde observations than those from its predecessor, namely, the Constrained Simultaneous Iteration Reconstruction Technique (CSIRT). The reconstruction accuracy is significantly improved. In the North American region experiment, the electron density profiles in ICSIRT results show better agreement with incoherent scatter radar observations than CSIRT, even for the topside profiles. Numéro de notice : A2020-227 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-00981-4 date de publication en ligne : 18/04/2020 En ligne : https://doi.org/10.1007/s10291-020-00981-4 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94958 [article]

Estimation of tropospheric wet refractivity using tomography method and artificial neural networks in Iranian case study / Mir Reza Ghaffari Razin in GPS solutions, Vol 24 n° 3 (July 2020)  

Public [article]  inGPS solutions > Vol 24 n° 3 (July 2020) Titre : Estimation of tropospheric wet refractivity using tomography method and artificial neural networks in Iranian case study Type de document : Article/Communication Auteurs : Mir Reza Ghaffari Razin, Auteur ; Behzad Voosoghi, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] coefficient de corrélation [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] erreur relative [Termes descripteurs IGN] Iran [Termes descripteurs IGN] réfraction atmosphérique [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] retard troposphérique [Termes descripteurs IGN] retard troposphérique zénithal [Termes descripteurs IGN] tomographie par GPS [Termes descripteurs IGN] vapeur d'eau [Termes descripteurs IGN] voxel Résumé : (auteur) Using the observations from local and regional GPS networks, the estimation of slant wet delays (SWDs) is possible for each line of sight between satellite and receiver. The observations of SWD are used to model horizontal and vertical variations of the wet refractivity in the atmosphere above the study area. This work is done using the tomography method. In tomography, the horizontal variations of tropospheric wet refractivity are modeled with the polynomial in degree and rank of 2 with latitude and longitude as variables. Also, altitude variations are modeled in the form of discrete layers with constant heights. The main innovation is to estimate the tropospheric parameters for each line of sight by the artificial neural networks (ANNs). The SWD obtained from GPS observations for the different signals at each station is compared with the SWD generated by the ANNs (SWDGPS–SWDANNs). The square of the difference between these two values is introduced as the cost function in the ANNs. To evaluate, we used observations from October 27 to 31, 2011. The availability of GPS and radiosonde data is the main reason for choosing this timeframe. The correlation coefficient, root mean square error (RMSE), and relative error allow for evaluation of the proposed model. The results were also compared with the results of the voxel-based troposphere tomography method. For a more detailed evaluation, four test stations are selected and ANN zenith wet delays (ZWDANN) are compared with the ZWDGPS. Observations of test stations are not used in the modeling step. The correlation coefficient in the testing step for TomoANN and Tomovoxel is 0.9006 and 0.8863, respectively. The mean RMSE at 5 days for TomoANN and Tomovoxel is calculated as 0.63 and 0.71 mm/km, respectively. Also, the average relative error at the four test stations for TomoANN is 15.37% and for Tomovoxel it is 19.69%. The results demonstrate the better capability of the proposed method in the modeling of the tropospheric wet refractivity in the region of Iran. Numéro de notice : A2020-238 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-00979-y date de publication en ligne : 10/04/2020 En ligne : https://doi.org/10.1007/s10291-020-00979-y Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94986 [article]

Digital terrain, surface, and canopy height models from InSAR backscatter-height histograms / Gustavo H.X. Shiroma in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 6 (June 2020) . - pp 754 - 3777 Titre : Digital terrain, surface, and canopy height models from InSAR backscatter-height histograms Type de document : Article/Communication Auteurs : Gustavo H.X. Shiroma, Auteur ; Marco Lavalle, Auteur Année de publication : 2020 Article en page(s) : pp 754 - 3777 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] bande L [Termes descripteurs IGN] décomposition de Gauss [Termes descripteurs IGN] Gabon [Termes descripteurs IGN] histogramme [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] modèle numérique de surface de la canopée [Termes descripteurs IGN] modèle numérique de terrain [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] polarimétrie radar [Termes descripteurs IGN] rétrodiffusion [Termes descripteurs IGN] structure de la végétation Résumé : (auteur) This article demonstrates how 3-D vegetation structure can be approximated by interferometric synthetic aperture radar (InSAR) backscatter-height histograms. Single-look backscatter measurements are plotted against the InSAR phase height and are aggregated spatially over a forest patch to form a 3-D histogram, referred to as InSAR backscatter-height histogram or simply InSAR histogram. InSAR histograms resemble LiDAR waveforms, suggesting that existing algorithms used to retrieve canopy height and ground topography from radar tomograms or LiDAR waveforms can be applied to InSAR histograms. Three algorithms are evaluated to generate maps of digital terrain, surface, and canopy height models: Gaussian decomposition, quantile, and backscatter threshold. Full-polarimetric L-band uninhabited aerial vehicle synthetic aperture radar (UAVSAR) data collected over the Gabonese Lopé National Park during the 2016 AfriSAR campaign are used to illustrate and compare the performance of the algorithms for the HH, HV, VV, HH+VV, and HH−VV polarimetric channels. Results show that radar-derived maps using the InSAR histograms differ by 4 m (top-canopy), 5 m (terrain), and 6 m (forest height) in terms of average root-mean-square errors (RMSEs) from standard maps derived from full-waveform laser, vegetation, and ice sensor (LVIS) LiDAR measurements. Numéro de notice : A2020-279 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2956989 date de publication en ligne : 16/01/2020 En ligne : https://doi.org/10.1109/TGRS.2019.2956989 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95099 [article]

Using multi-scale and hierarchical deep convolutional features for 3D semantic classification of TLS point clouds / Zhou Guo in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 4 (April 2020) . - pp 661 - 680 Titre : Using multi-scale and hierarchical deep convolutional features for 3D semantic classification of TLS point clouds Type de document : Article/Communication Auteurs : Zhou Guo, Auteur ; Chen-Chieh Feng, Auteur Année de publication : 2020 Article en page(s) : pp 661 - 680 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse multiéchelle [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] approche hiérarchique [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] Oakland (Californie) [Termes descripteurs IGN] régression [Termes descripteurs IGN] semis de points Résumé : (auteur) Point cloud classification, which provides meaningful semantic labels to the points in a point cloud, is essential for generating three-dimensional (3D) models. Its automation, however, remains challenging due to varying point densities and irregular point distributions. Adapting existing deep-learning approaches for two-dimensional (2D) image classification to point cloud classification is inefficient and results in the loss of information valuable for point cloud classification. In this article, a new approach that classifies point cloud directly in 3D is proposed. The approach uses multi-scale features generated by deep learning. It comprises three steps: (1) extract single-scale deep features using 3D convolutional neural network (CNN); (2) subsample the input point cloud at multiple scales, with the point cloud at each scale being an input to the 3D CNN, and combine deep features at multiple scales to form multi-scale and hierarchical features; and (3) retrieve the probabilities that each point belongs to the intended semantic category using a softmax regression classifier. The proposed approach was tested against two publicly available point cloud datasets to demonstrate its performance and compared to the results produced by other existing approaches. The experiment results achieved 96.89% overall accuracy on the Oakland dataset and 91.89% overall accuracy on the Europe dataset, which are the highest among the considered methods. Numéro de notice : A2020-109 Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1552790 date de publication en ligne : 10/12/2018 En ligne : https://doi.org/10.1080/13658816.2018.1552790 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94711 [article]

Comparison and analysis of results of 3D modelling of complex cultural and historical objects using different types of terrestrial laser scanner / Admir Mulahusic in Survey review, vol 52 n° 371 (March 2020)  

Public [article]  inSurvey review > vol 52 n° 371 (March 2020) . - pp 107-114 Titre : Comparison and analysis of results of 3D modelling of complex cultural and historical objects using different types of terrestrial laser scanner Type de document : Article/Communication Auteurs : Admir Mulahusic, Auteur ; Nedim Tuno, Auteur ; Dubravko Gajski, Auteur ; Jusuf Topoljak, Auteur Année de publication : 2020 Article en page(s) : pp 107-114 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] balayage laser [Termes descripteurs IGN] Croatie [Termes descripteurs IGN] impulsion laser [Termes descripteurs IGN] logiciel de reconstruction 3D [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] monument historique [Termes descripteurs IGN] patrimoine culturel [Termes descripteurs IGN] précision géométrique (imagerie) [Termes descripteurs IGN] télémétrie laser terrestre [Termes descripteurs IGN] traitement de données Résumé : (auteur) Laser scanning does not provide unlimited geometrical accuracy and integrity when scanning complex objects. Scanning systems have a minimum and maximum range in which they operate, depending on the technical characteristics. Scanning below or above these limits results in gross errors and registering of incorrect data. Laser scanners can have difficulties with certain materials such as marble and reflective surfaces. This paper presents the results of laser scanning of a complex monument of cultural and historical heritage using two different types of terrestrial laser scanners. Afterwards, the comparison and analysis of the results are shown. The scanners used were terrestrial laser scanners Faro Focus 3D (phase mode distance measurements) and STONEX X300 (pulse mode distance measurements). Numéro de notice : A2020-073 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1528758 date de publication en ligne : 09/10/2018 En ligne : https://doi.org/10.1080/00396265.2018.1528758 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94638 [article]

A proposal for modeling indoor–outdoor spaces through indoorGML, open location code and OpenStreetMap / Ruben Cantarero Navarro in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)  

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Automated extraction of lane markings from mobile LiDAR point clouds based on fuzzy inference / Heidar Rastiveis in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

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Comparative usability of an augmented reality sandtable and 3D GIS for education / Antoni B. Moore in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)  

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Tree annotations in LiDAR data using point densities and convolutional neural networks / Ananya Gupta in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)  

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Cattle detection and counting in UAV images based on convolutional neural networks / Wen Shao in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)  

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An indoor navigation model and its network extraction / Filippo Mortari in Applied geomatics, Vol 11 n° 4 (December 2019)  

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Application of photogrammetry to generate quantitative geobody data in ephemeral fluvial systems / Charlotte L. Priddy in Photogrammetric record, vol 34 n° 168 (December 2019)  

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Combining thermal imaging with photogrammetry of an active volcano using UAV: an example from Stromboli, Italy / Zoë E. Wakeford in Photogrammetric record, vol 34 n° 168 (December 2019)  

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Innovative techniques of photogrammetry for 3D modeling / Vicenzo Barrile in Applied geomatics, Vol 11 n° 4 (December 2019)  

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A learning approach to evaluate the quality of 3D city models / Oussama Ennafii in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 12 (December 2019)  

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