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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)
[article]
Titre : Combining thermal imaging with photogrammetry of an active volcano using UAV: an example from Stromboli, Italy Type de document : Article/Communication Auteurs : Zoë E. Wakeford, Auteur ; Magda Chmielewska, Auteur ; Malcolm J. Hole, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 445 - 466 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] données GNSS
[Termes IGN] image captée par drone
[Termes IGN] image RVB
[Termes IGN] image thermique
[Termes IGN] modélisation 3D
[Termes IGN] photogrammétrie numérique
[Termes IGN] point d'appui
[Termes IGN] risque naturel
[Termes IGN] spectre électromagnétique
[Termes IGN] Stromboli (volcan)
[Termes IGN] surveillance géologiqueRésumé : (auteur) Volcanoes are a potential hazard to over 750 million people worldwide. Accessing them to install monitoring equipment can be logistically challenging and dangerous. Traditional monitoring equipment is expensive and not available to many local communities. A new, low‐cost method is proposed to address these challenges using a unique 3D thermal photogrammetric modelling workflow. The data acquisition and processing part of this workflow has been tested on Stromboli, a volcano in the Aeolian Islands of Italy. Unmanned aerial vehicles (UAVs) were deployed at the volcano to acquire both visible and thermal infrared imagery. Both datasets were then digitally processed to produce 3D virtual outcrop models. Finally, the two datasets and models were integrated to produce the first 3D thermal photogrammetric model of an active volcano. The result is an easy‐to‐use workflow applicable to any volcano. This low‐cost monitoring system could be deployed in developing countries and remote areas otherwise hindered by limited budgets and poor access. Numéro de notice : A2019-578 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12301 Date de publication en ligne : 23/12/2019 En ligne : https://doi.org/10.1111/phor.12301 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94464
in Photogrammetric record > vol 34 n° 168 (December 2019) . - pp 445 - 466[article]Half a percent of labels is enough: efficient animal detection in UAV imagery using deep CNNs and active learning / Benjamin Kellenberger in IEEE Transactions on geoscience and remote sensing, vol 57 n° 12 (December 2019)
[article]
Titre : Half a percent of labels is enough: efficient animal detection in UAV imagery using deep CNNs and active learning Type de document : Article/Communication Auteurs : Benjamin Kellenberger, Auteur ; Diego Marcos, Auteur ; Sylvain Lobry, Auteur ; Devis Tuia, Auteur Année de publication : 2019 Article en page(s) : pp 9524 - 9533 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] apprentissage profond
[Termes IGN] classification orientée objet
[Termes IGN] classification par réseau neuronal
[Termes IGN] détection d'objet
[Termes IGN] données localisées
[Termes IGN] échantillonnage de données
[Termes IGN] faune locale
[Termes IGN] image captée par drone
[Termes IGN] Namibie
[Termes IGN] objet mobile
[Termes IGN] réalité de terrain
[Termes IGN] recensementRésumé : (auteur) We present an Active Learning (AL) strategy for reusing a deep Convolutional Neural Network (CNN)-based object detector on a new data set. This is of particular interest for wildlife conservation: given a set of images acquired with an Unmanned Aerial Vehicle (UAV) and manually labeled ground truth, our goal is to train an animal detector that can be reused for repeated acquisitions, e.g., in follow-up years. Domain shifts between data sets typically prevent such a direct model application. We thus propose to bridge this gap using AL and introduce a new criterion called Transfer Sampling (TS). TS uses Optimal Transport (OT) to find corresponding regions between the source and the target data sets in the space of CNN activations. The CNN scores in the source data set are used to rank the samples according to their likelihood of being animals, and this ranking is transferred to the target data set. Unlike conventional AL criteria that exploit model uncertainty, TS focuses on very confident samples, thus allowing quick retrieval of true positives in the target data set, where positives are typically extremely rare and difficult to find by visual inspection. We extend TS with a new window cropping strategy that further accelerates sample retrieval. Our experiments show that with both strategies combined, less than half a percent of oracle-provided labels are enough to find almost 80% of the animals in challenging sets of UAV images, beating all baselines by a margin. Numéro de notice : A2019-598 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2927393 Date de publication en ligne : 20/08/2019 En ligne : http://doi.org/10.1109/TGRS.2019.2927393 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94592
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 12 (December 2019) . - pp 9524 - 9533[article]A low‐cost open‐source workflow to generate georeferenced 3D SfM photogrammetric models of rocky outcrops / Laurent Froideval in Photogrammetric record, vol 34 n° 168 (December 2019)
[article]
Titre : A low‐cost open‐source workflow to generate georeferenced 3D SfM photogrammetric models of rocky outcrops Type de document : Article/Communication Auteurs : Laurent Froideval, Auteur ; Kevin Pedoja, Auteur ; Franck Garestier, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 365 - 384 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] falaise
[Termes IGN] front rocheux
[Termes IGN] géoréférencement
[Termes IGN] GNSS en mode différentiel
[Termes IGN] image captée par drone
[Termes IGN] logiciel libre
[Termes IGN] modélisation 3D
[Termes IGN] Normandie (région 2016)
[Termes IGN] Open MVG
[Termes IGN] point d'appui
[Termes IGN] structure-from-motionRésumé : (auteur) Structure‐from‐Motion (SfM) software and unmanned aerial vehicles (UAVs) have been increasingly adopted in the geosciences. The current mainstream generation of 3D models is still expensive as it relies on UAVs, Differential Global Navigation Satellite System (DGNSS) ground control points and commercial software. This paper proposes an end‐to‐end reproducible SfM workflow with minimal legal, financial or field issues. The procedure avoids both UAVs and DGNSS and relies on open‐source software. Interlocked models of a rocky shore in Normandy, France were generated at different scales and point densities, being georeferenced using free spatial data. A spherical target was used for scaling and assessing the relative accuracy, which was better than 1 cm. Numéro de notice : A2019-576 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12297 Date de publication en ligne : 27/11/2019 En ligne : https://doi.org/10.1111/phor.12297 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94459
in Photogrammetric record > vol 34 n° 168 (December 2019) . - pp 365 - 384[article]Numérisation, restitution et visualisation en 3D de sites patrimoniaux / Jonathan Chemla in XYZ, n° 161 (décembre 2019)
[article]
Titre : Numérisation, restitution et visualisation en 3D de sites patrimoniaux Type de document : Article/Communication Auteurs : Jonathan Chemla, Auteur Année de publication : 2019 Article en page(s) : pp 16 - 19 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image captée par drone
[Termes IGN] patrimoine archéologique
[Termes IGN] photogrammétrie architecturale
[Termes IGN] site archéologique
[Termes IGN] visualisation 3DRésumé : (Auteur) Iconem agit dans les zones où le patrimoine est menacé afin de réaliser rapidement un modèle numérique photoréaliste d'un monument ou d'un site archéologique, en couplant l'utilisation des drones, de la photogrammétrie et des scanners laser. Ce modèle 3D sert d'archive pour la diffusion et l'étude, mais aussi de base à un certain nombre de traitements utiles pour les architectes, les restaurateurs du patrimoine et les scientifiques. Après avoir opéré au Proche-Orient - sur la vieille ville de Mossoul ou le Crac des Chevaliers pour Unesco - ses missions récentes ont couvert des sites en France comme le Mont-Saint-Michel, en Europe, en Afrique du Nord ou encore en Asie du Sud-Est. Numéro de notice : A2019-581 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94469
in XYZ > n° 161 (décembre 2019) . - pp 16 - 19[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 112-2019041 RAB Revue Centre de documentation En réserve L003 Disponible Soil and vegetation scattering contributions in L-Band and P-Band polarimetric SAR observations / S. Hamed Alemohammad in IEEE Transactions on geoscience and remote sensing, vol 57 n° 11 (November 2019)
[article]
Titre : Soil and vegetation scattering contributions in L-Band and P-Band polarimetric SAR observations Type de document : Article/Communication Auteurs : S. Hamed Alemohammad, Auteur ; Thomas Jagdhuber, Auteur ; Mahta Moghaddam, Auteur ; Dara Entekhabi, Auteur Année de publication : 2019 Article en page(s) : pp 8417 - 8429 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] bande P
[Termes IGN] canopée
[Termes IGN] constante diélectrique
[Termes IGN] couvert végétal
[Termes IGN] données polarimétriques
[Termes IGN] humidité du sol
[Termes IGN] image captée par drone
[Termes IGN] image radar moirée
[Termes IGN] micro-onde
[Termes IGN] rugosité du sol
[Termes IGN] teneur en eau de la végétationRésumé : (auteur) Active microwave-based retrieval of soil moisture in vegetated areas has uncertainties due to the sensitivity of the signal to both soil (dielectric constant and roughness) and vegetation (dielectric constant and structure) properties. A multi-frequency acquisition system would increase the number of observations that may constrain soil and/or vegetation parameter retrievals. In order to realize this constraint, an understanding of microwaves interaction with the surface and vegetation across frequencies is necessary. Different microwave frequencies have varied interactions with the soil-vegetation medium and increasing penetration into the soil and canopy with the decreasing frequency. In this study, we examine the contributions of different scattering mechanisms to coincident observations from two microwave frequencies (L and P) of airborne synthetic aperture radar instruments. We quantify contributions of surface, vegetation volume, and double-bounce scattering components. Results are analyzed and discussed to guide future multi-frequency retrieval algorithm designs. Numéro de notice : A2019-594 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2920995 Date de publication en ligne : 27/06/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2920995 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94586
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 11 (November 2019) . - pp 8417 - 8429[article]Télédétection des habitats insulaires ligériens par drone : Retour d’expérience sur les îles de Mareau-aux-Prés (Loiret) / Hilaire Martin in Revue forestière française, vol 71 n° 6 (2019)PermalinkSegmenting mangrove ecosystems drone images using SLIC superpixels / Edward Zimudzi in Geocarto international, vol 34 n° 14 ([30/10/2019])PermalinkEstimating pasture biomass and canopy height in brazilian savanna using UAV photogrammetry / Juliana Batistoti in Remote sensing, Vol 11 n° 20 (October-2 2019)PermalinkAutomated fusion of forest airborne and terrestrial point clouds through canopy density analysis / Wenxia Dai in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)PermalinkA machine learning approach to detect crude oil contamination in a real scenario using hyperspectral remote sensing / Ran Pelta in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)PermalinkMapping dead forest cover using a deep convolutional neural network and digital aerial photography / Jean-Daniel Sylvain in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)PermalinkOptimal segmentation of high spatial resolution images for the classification of buildings using random forests / James Bialas in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)PermalinkPostprocessing synchronization of a laser scanning system aboard a UAV / Marcela do Valle Machado in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 10 (October 2019)PermalinkScene context-driven vehicle detection in high-resolution aerial images / Chao Tao in IEEE Transactions on geoscience and remote sensing, Vol 57 n° 10 (October 2019)PermalinksUAS-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-1 2019)PermalinkUnmanned aerial vehicles (UAVs) for monitoring macroalgal biodiversity: comparison of RGB and multispectral imaging sensors for biodiversity assessments / Leigh Tait in Remote sensing, vol 11 n° 19 (October-1 2019)PermalinkDevelopment and evaluation of a deep learning model for real-time ground vehicle semantic segmentation from UAV-based thermal infrared imagery / Mehdi Khoshboresh Masouleh in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)PermalinkEvolution des techniques topographiques à EDF depuis les 40 dernières années / Rémy Boudon in XYZ, n° 160 (septembre 2019)PermalinkPPD: Pyramid Patch Descriptor via convolutional neural network / Jie Wan in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 9 (September 2019)PermalinkTopographie et archéologie, du cordeau au tout numérique : plus de 40 ans d'interactions / Bertrand Chazaly in XYZ, n° 160 (septembre 2019)PermalinkUnmanned aerial system multispectral mapping for low and variable solar irradiance conditions: Potential of tensor decomposition / Sheng Wang in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)PermalinkAutomatic extraction of accurate 3D tie points for trajectory adjustment of mobile laser scanners using aerial imagery / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)PermalinkMapping the wavelength position of mineral features in hyperspectral thermal infrared data / Christoph Hecker in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)PermalinkMonitoring the structure of forest restoration plantations with a drone-lidar system / D.R.A. Almeida in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)PermalinkCNN-based dense image matching for aerial remote sensing images / Shunping Ji in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 6 (June 2019)PermalinkCo‐registration of panoramic mobile mapping images and oblique aerial images / Phillipp Jende in Photogrammetric record, vol 34 n° 166 (June 2019)PermalinkSemantic façade segmentation from airborne oblique images / Yaping Lin in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 6 (June 2019)PermalinkSimulation and analysis of photogrammetric UAV image blocks: influence of camera calibration error / Yilin Zhou in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2/W5 (May 2019)PermalinkOn the positional accuracy and maximum allowable scale of UAV-derived photogrammetric products for archaeological site documentation / Juan Antonio Pérez in Geocarto international, vol 34 n° 6 ([15/05/2019])PermalinkEconomic losses caused by tree species proportions and site type errors in forest management planning / Arto Haara in Silva fennica, vol 53 n° 2 (2019)PermalinkAutomatic sensor orientation using horizontal and vertical line feature constraints / Yanbiao Sun in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)PermalinkVehicle detection in aerial images / Michael Ying Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 4 (avril 2019)PermalinkAn evaluation of reflectance calibration methods for UAV spectral imagery / Jarrod Edwards in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 3 (March 2019)PermalinkComparaison de MNT à haute résolution issus de techniques laser et photogrammétriques / Michel Kasser in XYZ, n° 158 (mars 2019)PermalinkMise en place de procédures automatisées pour les reports topographiques en milieu ferroviaire à partir de données photogrammétriques et LiDAR acquises par drones / Marion Hinaux in XYZ, n° 158 (mars 2019)PermalinkModelling the effects of fundamental UAV flight parameters on LiDAR point clouds to facilitate objectives-based planning / Jeremy J. Sofonia in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)PermalinkDeveloping an optimized texture mapping for photorealistic 3D buildings / Jungil Lee in Transactions in GIS, vol 23 n° 1 (February 2019)PermalinkImprovement of photogrammetric accuracy by modeling and correcting the thermal effect on camera calibration / Mehdi Daakir in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)PermalinkNear real-time deforestation detection in Malaysia and Indonesia using change vector analysis with three sensors / Pauline Perbet in International Journal of Remote Sensing IJRS, vol 40 n°19 (February 2019)Permalink100% automatic metrology with UAV photogrammetry and embedded GPS, and its application in dike monitoring / Yilin Zhou (2019)PermalinkAdvanced Remote Sensing Technology for Synthetic Aperture Radar Applications, Tsunami Disasters, and Infrastructure / Maged Marghany (2019)PermalinkApports des techniques photogrammétriques à l'étude du dynamisme des structures volcaniques du piton de la Fournaise / Allan Derrien (2019)PermalinkPermalinkBridging the gap: toward a French MS-NFI for territories / Jean-Pierre Renaud (2019)PermalinkPermalinkPermalinkEarth observation, remote sensing and geoscientific ground investigations for archaeological and heritage research / Deodato Tapete (2019)PermalinkEvaluating the capability of the Sentinel 2 data for soil organic carbon prediction in croplands / Fabio Castaldi in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)PermalinkExploitation of hyperspectral data for assessing vegetation health under exposure to petroleum hydrocarbons / Guillaume Lassalle (2019)PermalinkForest inventory sensitivity to UAS-based image processing algorithms / Bonifasius Maturbongs in Annals of forest research, vol 62 n° 1 (January - June 2019)Permalink