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Titre : Google Earth Engine applications Type de document : Monographie Auteurs : Lalit Kumar, Éditeur scientifique ; Onisimo Mutanga, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 420 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-3-03897-885-5 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique
[Termes IGN] base de données d'images
[Termes IGN] Google Earth Engine
[Termes IGN] image 3D
[Termes IGN] image aérienne
[Termes IGN] image satellite
[Termes IGN] information géographique numérique
[Termes IGN] informatique en nuage
[Termes IGN] moteur de recherche
[Termes IGN] surveillance écologique
[Termes IGN] système d'information environnementale
[Termes IGN] traitement de données localiséesRésumé : (éditeur) In a rapidly changing world, there is an ever-increasing need to monitor the Earth's resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth's surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales. Note de contenu : 1- Google Earth Engine applications since inception: usage, trends, and potential
2- Global estimation of biophysical variables from Google Earth Engine platform
3- An operational before-after-control-impact (BACI) designed platform for vegetation monitoring at planetary scale
4- Mapping vegetation and land use types in Fanjingshan national nature reserve using Google Earth Engine
5- A dynamic Landsat derived Normalized Difference Vegetation Index (NDVI) product for the conterminous United States
6- High spatial resolution visual band imagery outperforms medium resolution spectral imagery for ecosystem assessment in the semi-arid Brazilian Sert˜ao
7- Assessing the spatial and occupation dynamics of the Brazilian pasturelands based on the automated classification of MODIS images from 2000 to 2016
8- Towards global-scale seagrass mapping and monitoring using Sentinel-2 on Google Earth Engine: The case study of the Aegean and Ionian Seas
9- BULC-U: Sharpening resolution and improving accuracy of land-use/land-cover classifications in Google Earth Engine
10- Monitoring the impact of land cover change on surface urban heat island through Google
Earth Engine: Proposal of a global methodology, first applications and problems
11- Regional crop gross primary productivity and yield estimation using fused Landsat-MODIS data
12- The first wetland inventory map of Newfoundland at a spatial resolution of 10 m using Sentinel-1 and Sentinel-2 data on the Google Earth Engine cloud computing platform
13- A cloud-based multi-temporal ensemble classifier to map smallholder farming systems
14- Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8 data on Google Earth Engine
15- SnowCloudHydro — A new framework for forecasting streamflow in snowy, data-scarce regions
16- Flood prevention and emergency response system powered by Google Earth Engine
17- Leveraging the Google Earth Engine for drought assessment using global soil moisture data
18- Multitemporal cloud masking in the Google Earth Engine
19- Historical and operational monitoring of surface sediments in the lower Mekong basin using Landsat and Google Earth Engine cloud computing
20- Mapping mining areas in the Brazilian Amazon using MSI/Sentinel-2 imagery (2017)
21- Estimating satellite-derived bathymetry (SDB) with the Google Earth Engine and Sentinel-2
22- Mean composite fire severity metrics computed with Google Earth Engine offer improved accuracy and expanded mapping potentialNuméro de notice : 25887 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Monographie DOI : 10.3390/books978-3-03897-885-5 En ligne : https://doi.org/10.3390/books978-3-03897-885-5 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95788
Titre : Impact of oblique UAV imagery on canopy models Type de document : Mémoire Auteurs : Anouk Schleich, Auteur Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Année de publication : 2019 Importance : 104 p. Format : 21 x 30 cm Note générale : Bibliographie
Rapport de projet pluridisciplinaire, cycle ING2Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse comparative
[Termes IGN] angle de visée
[Termes IGN] image aérienne oblique
[Termes IGN] image captée par drone
[Termes IGN] MicMac
[Termes IGN] nadir
[Termes IGN] parcelle agricole
[Termes IGN] Pix4D
[Termes IGN] semis de points
[Termes IGN] structure-from-motion
[Termes IGN] traitement d'imageIndex. décimale : PROJET Mémoires : Rapports de projet - stage des ingénieurs de 2e année Résumé : (Auteur) Les drones sont une solution très abordable dans le monde de la télédétection. Ils sont de plus en plus utilisés dans le domaine de l’agriculture pour aider les agriculteurs à prévoir leur rendement, à détecter le stress des cultures et à surveiller les champs. Les images aériennes peuvent être utilisées pour construire des modèles 3D grâce au processus photogrammétrique de Structure from Motion. Nous étudierons l’impact des images obliques sur les modèles de canopée. Plusieurs vols avec différents angles de caméra ont été effectués sur un champ de maïs. Nous avons comparé les résultats du vol nadir, correspondant à un angle de 90_, au vol de 80_, 70_, 60_ et 50_. Nous présenterons l’acquisition de données, le traitement des images avec MicMac et Pix4D et qualifierons les résultats. L’un des aspects de la recherche consiste à qualifier les nuages de points de drone en utilisant des nuages de points terrestres. Un autre objectif du projet est d’étudier si l’utilisation de l’imagerie oblique peut éviter l’utilisation de points d’appuis et quel angle est le mieux adapté pour limiter l’effet de doming. Nous pouvons constater que les acquisitions à 70_ et 60_ donnent les meilleurs résultats, mais que cela est très difficile de décider quel angle est le mieux adapté, car différentes analyses donnent différents résultats. Note de contenu :
Introduction
1. Creating 3D models for oblique research
1.1 Context
1.2 Acquisition
1.3 Processing
2. Evaluation of the 3D models
2.1 Visually
2.2 Analyze of the processing outputs
2.3 Comparison of point clouds with GRASS
ConclusionNuméro de notice : 26125 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Mémoire de projet pluridisciplinaire Organisme de stage : Center for Geospatial Analytics (North Carolina State University) Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93912 Documents numériques
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Impact of oblique UAV imagery on canopy models - pdf auteurAdobe Acrobat PDF
Titre : More surface detail with one-two-pixel matching Type de document : Rapport Auteurs : Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny , Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2019 Importance : 16 p. Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] appariement d'histogramme
[Termes IGN] appariement de points
[Termes IGN] appariement semi-global
[Termes IGN] corrélation croisée normalisée
[Termes IGN] corrélation par régions de niveaux de gris
[Termes IGN] géosciences
[Termes IGN] image captée par drone
[Termes IGN] image Pléiades
[Termes IGN] image SPOT 7
[Termes IGN] image terrestre
[Termes IGN] MicMac
[Termes IGN] modèle numérique de surfaceRésumé : (Auteur) Photogrammetrically derived Digital Surface Models have been widely adopted in geoscientific applications such as mapping and change detection across volcanic surfaces, glaciers, areas of seismic activity, forests, river landforms etc. Resolution of the reconstructed surface is crucial as more accurate information enables more profound understanding of the phenomena. With this objective in mind, the research presented here proposes a new matching cost function that produces surfaces of enhanced resolution with respect to the gold standard: the window-based semi-global matching technique. We evaluate the algorithm on different image datasets spanning various acquisition geometries, radiometric qualities and ground sample distance sizes. In particular , results on Earth satellites (SPOT-7, Pléiades), extraterres-trial (Chang'E3 moon landing), aerial and terrestrial acquisitions are shown. The implementation of the method is available in MicMac-the free open-source software for photogrammetry. I. INTRODUCTION Digital surface model (DSM or photogrammetric DSM) generation using dense image matching is an accepted technique across the geoscience communities. Next to other competitive techniques such as LiDAR or radar, image-based reconstruction produces denser 3D information, it is cost-effective and richer as it includes photometric observations that allow, for example, 3D change detection or classification. Photogrammetric DSMs in geoscience applications can be generated from terrestrial images, unmanned aerial vehicle (UAV) acquisitions or high-resolution optical satellite imaging. a) Terrestrial and UAV applications: Modelling of surface roughness parameters [1]; mapping volcanic surfaces [2]; and measuring glaciers' microrelief progression [3] are some of many examples of terrestrial applications carried out with consumer grade cameras and little expert knowledge. UAV-based surveys are increasingly presented as an alternative to terrestrial surveys due to their larger reach, their ease of deployment and reduced operational cost. With respect to resolution, UAV surveys are a compromise between high-resolution close-range and moderate-resolution satellite imaging. The success of the UAV technology is reflected in numerous publications which show that UAV-collected imagery can: enable modelling of forest canopy height [4]; determine the rate and extent of landslide movements [5]; quantify coastal erosion [6], [7] and deposition processes [8] in aeolian research; map ultrafine (i.e. centimetric) tectonic faults in tectonic research [9]; or be employed in repeated surveys of the ice-sheet masses in glaciology [10]. b) Earth satellite and extraterrestrial applications: With the available optical satellite data provided by modern (e.g. Pléiades 1A/B, SPOT-satellites, QuickBird, WorldView 2/3/4, CubeSat) or older satellites (e.g. CartoSat, ASTER), we can Numéro de notice : 26221 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Rapport de recherche nature-HAL : RappRech DOI : sans En ligne : https://hal.archives-ouvertes.fr/hal-02371337 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94223 Documents numériques
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More surface detail with One-Two-Pixel Matching - pdf Archives ouvertes HALAdobe Acrobat PDF Sensitivity of urban material classification to spatial and spectral configurations from visible to short-wave infrared / Arnaud Le Bris (2019)
Titre : Sensitivity of urban material classification to spatial and spectral configurations from visible to short-wave infrared Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2019 Projets : HYEP / Weber, Christiane Conférence : JURSE 2019, Joint Urban Remote Sensing Event 22/05/2019 24/05/2019 Vannes France Proceedings IEEE Importance : 4 p. Format : 21 x 30 cm Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse de sensibilité
[Termes IGN] image à haute résolution
[Termes IGN] image à très haute résolution
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] objet géographique urbain
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] signature spectraleRésumé : (Auteur) Urban material maps are useful for several city modeling or monitoring applications and can be retrieved from remote sensing data. This study investigates the impact of spectral and spatial sensor configuration on urban material classification results, comparing several configurations corresponding to existing or envisaged airborne or space sensors. Images corresponding to such sensors were simulated out of an airborne hyperspectral acquisition. At the end, the relevance of an enhanced spectral configuration and especially providing bands from the SWIR domain was proven, as well as the need for a fine spatial resolution to retrieve urban objects. However, the (late) fusion of multispectral imagery at 2 m resolution with hyperspectral data at 8 m resolution was also proven to lead to good results. Numéro de notice : C2019-005 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE/URBANISME Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/JURSE.2019.8809029 Date de publication en ligne : 22/08/2019 En ligne : https://doi.org/10.1109/JURSE.2019.8809029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92587 Documents numériques
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Sensitivity of urban material classification to spatial and spectral configurations... - pdf auteurAdobe Acrobat PDF Structure from motion for ordered and unordered image sets based on random k-d forests and global pose estimation / Xin Wang in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)
[article]
Titre : Structure from motion for ordered and unordered image sets based on random k-d forests and global pose estimation Type de document : Article/Communication Auteurs : Xin Wang, Auteur ; Franz Rottensteiner, Auteur ; Christian Heipke, Auteur Année de publication : 2019 Article en page(s) : pp 19 - 41 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] appariement d'images
[Termes IGN] chaîne de traitement
[Termes IGN] classification barycentrique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] compensation par faisceaux
[Termes IGN] estimation de pose
[Termes IGN] image captée par drone
[Termes IGN] matrice de rotation
[Termes IGN] orientation relative
[Termes IGN] Ransac (algorithme)
[Termes IGN] recouvrement d'images
[Termes IGN] SIFT (algorithme)
[Termes IGN] structure-from-motion
[Termes IGN] vision par ordinateurRésumé : (auteur) In this paper, we present a new fast and robust method for structure from motion (SfM) for data sets potentially comprising thousands of ordered or unordered images. Our work focuses on the two most time-consuming procedures: (a) image matching and (b) pose estimation. For image matching, a new method employing a random k-d forest is proposed to quickly obtain pairs of overlapping images from an unordered set. After that, image matching and the estimation of relative orientation parameters are performed only for pairs found to be very likely to overlap. For pose estimation, we use a two-stage global approach, separating the determination of rotation matrices and translation parameters; the latter are computed simultaneously using a new method. In order to cope with outliers in the relative orientations, which global approaches are particularly sensitive to, we present a new constraint based on triplet loop closure errors of rotation and translation. Finally, a robust bundle adjustment is carried out to refine the image orientation parameters. We demonstrate the potential and limitations of our pipeline using various real-world datasets including ordered image data acquired from UAV (unmanned aerial vehicle) and other platforms as well as unordered data from the internet. The experiments show that our work performs better than comparable state-of-the-art SfM systems in terms of run time, while we achieve a similar accuracy and robustness. Numéro de notice : A2019-033 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.11.009 Date de publication en ligne : 15/11/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.11.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91970
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Kangas in Silva fennica, vol 52 n° 1 ([01/02/2018])PermalinkActive learning-based optimized training library generation for object-oriented image classification / Rajeswari Balasubramaniam in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)PermalinkChaîne de traitement de photogrammétrie en vue de réaliser un MNS à partir de photographies aériennes / Alice Gonnaud (2018)PermalinkPermalinkDétection de changement par imagerie radar sur les zones naturelles et agricoles en milieu tropical / Jérôme Lebreton (2018)PermalinkDéveloppement d'un outil de manipulation optimisée de rasters volumineux / Amaury Zarzelli (2018)PermalinkPermalinkGenerating terrestrial glacier views from historic airphotos for comparison with contemporary ground photographs / Marion Holst (2018)PermalinkPermalinkPermalinkUn inventaire forestier multisource pour la gestion des territoires / Dinesh Babu Irulappa-Pillai-Vijayakumar (2018)PermalinkLocalisation d'objets urbains à partir de sources multiples dont des images aériennes / Lionel Pibre (2018)PermalinkMise en évidence de l’activité récente des failles du bassin de Naryn (Kyrgyzstan) à partir de données photogrammétriques Pléiades et drone : un nouvel apport pour l’aléa sismique / Aurélie Médard (2018)PermalinkPermalinkRéseaux de neurones convolutionnels profonds pour la détection de petits véhicules en imagerie aérienne / Jean Ogier du Terrail (2018)PermalinkSentinel-2 data analysis and comparison with UAV multispectral images for precision viticulture / Frederica Nonni in GI Forum, vol 2018 n° 1 ([01/01/2018])PermalinkPermalinkSuivi des impacts d’un arasement de barrage sur la végétation riveraine par télédétection à très haute résolution spatiale et temporelle / Marianne Laslier (2018)PermalinkPermalinkAbove-bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform – A case study in Wild Duck Lake Wetland, Beijing, China / Ran Jing in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)PermalinkArea-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds / Paweł Hawryło in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)PermalinkEstimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications? / Fabian E. Fassnacht in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)PermalinkHigh-resolution aerial image labeling with convolutional neural networks / Emmanuel Maggiori in IEEE Transactions on geoscience and remote sensing, vol 55 n° 12 (December 2017)PermalinkStand-level wind damage can be assessed using diachronic photogrammetric canopy height models / Jean-Pierre Renaud in Annals of Forest Science, vol 74 n° 4 (December 2017)PermalinkCartographie de la vulnérabilité des bâtiments au risque sismique / Valerio Baiocchi in Géomatique expert, n° 119 (novembre - décembre 2017)PermalinkChangement climatique et risque inondation / William Halbecq in Géomatique expert, n° 119 (novembre - décembre 2017)PermalinkAutomatic shadow detection in aerial and terrestrial images / Vander Luis de Souza Freitas in Boletim de Ciências Geodésicas, vol 23 n° 4 (oct - dec 2017)PermalinkEfficient structure from motion for oblique UAV images based on maximal spanning tree expansion / San Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)PermalinkHyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables / Sakari Tuominen in Silva fennica, vol 51 n° 5 (2017)PermalinkRegistration of images to Lidar and GIS data without establishing explicit correspondences / Gabor Barsai in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 10 (October 2017)PermalinkDocumentation of heritage buildings using close-range UAV images: dense matching issues, comparison and case studies / Arnadi Murtiyoso in Photogrammetric record, vol 32 n° 159 (September 2017)PermalinkEstudio de precision en la aerotriangulacion de bloques de imagenes obtenidas con UAV / Miguel Angel Lopez Gonzalez in Mapping : Teledetección, medio ambiante, cartografía, sistemas de información geográfica, vol 26 n° 185 (septembrie - octubre 2017)PermalinkA higher order conditional random field model for simultaneous classification of land cover and land use / Lena Albert in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)PermalinkImage matching as a data source for forest inventory – Comparison of semi-global matching and next-generation automatic terrain extraction algorithms in a typical managed boreal forest environment / Mari Kukkonen in International journal of applied Earth observation and geoinformation, vol 60 (August 2017)PermalinkImproving Finnish multi-source national forest inventory by 3D aerial imaging / Sakari Tuominen in Silva fennica, vol 51 n° 4 (2017)PermalinkLearning and transferring deep joint spectral–spatial features for hyperspectral classification / Jingxiang Yang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)PermalinkLearning sensor-specific spatial-spectral features of hyperspectral images via convolutional neural networks / Shaohui Mei in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)PermalinkParallax-tolerant aerial image georegistration and efficient camera pose refinement—without piecewise homographies / Hadi AliAkbarpour in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)PermalinkPotential application of remote sensing in monitoring ecosystem services of forests, mangroves and urban areas / Ram Avtar in Geocarto international, vol 32 n° 8 (August 2017)PermalinkImplementation of an IMU aided image stacking algorithm in a digital camera for Unmanned Aerial Vehicles / Ahmad Audi in Sensors, Vol 17 n°7 (july 2017)PermalinkNorthern conifer forest species classification using multispectral data acquired from an unmanned aerial vehicle / Steven E. Franklin in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 7 (July 2017)PermalinkAn accelerated image matching technique for UAV orthoimage registration / Chung-Hsien Tsai in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)PermalinkAutomatic measurement of control points for aerial image orientation / Adilson Berveglieri in Photogrammetric record, vol 32 n° 158 (June - july 2017)PermalinkEnhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency / Changjiang Liu in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)PermalinkLow aerial imagery – an assessment of georeferencing errors and the potential for use in environmental inventory / Maciej Smaczyński in Geodesy and cartography, vol 66 n° 1 (June 2017)PermalinkTélédétection et photogrammétrie pour l'étude de la dynamique de l’occupation du sol dans le bassin versant de l’oued Chiba (Cap-Bon, Tunisie) / Anis Gasmi in Revue Française de Photogrammétrie et de Télédétection, n° 215 (mai - août 2017)PermalinkDetermining tree height and crown diameter from high-resolution UAV imagery / Dimitrios Panagiotidis in International Journal of Remote Sensing IJRS, vol 38 n° 8-10 (April 2017)PermalinkMapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory / Jonas Bohlin in Silva fennica, vol 51 n° 2 (2017)PermalinkSemantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery / Clément Dechesne in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)PermalinkActive interseismic shallow deformation of the Pingting terraces (Longitudinal Valley – Eastern Taiwan) from UAV high-resolution topographic data combined with InSAR time series / Benoit Deffontaines in Geomatics, Natural Hazards and Risk, vol 8 (2017)PermalinkAttribute profiles on derived features for urban land cover classification / Bharath Bhushan Damodaran in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 3 (March 2017)PermalinkMapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory / Jonas Bohlin in Silva fennica, vol 51 n° 2 (2017)PermalinkUsing vector building maps to aid in generating seams for low-attitude aerial orthoimage mosaicking: Advantages in avoiding the crossing of buildings / Dongliang Wang in ISPRS Journal of photogrammetry and remote sensing, vol 125 (March 2017)PermalinkCharacterizing vegetation canopy structure using airborne remote sensing data / Debsunder Dutta in IEEE Transactions on geoscience and remote sensing, vol 55 n° 2 (February 2017)PermalinkEuroSDR contributions to ISPRS Congress XXIII, 12 - 19 July 2016, Special Session 12 – EuroSDR Prague, Czech Republic / European Spatial Data Research EuroSDR (02/2017)PermalinkOn the fusion of lidar and aerial color imagery to detect urban vegetation and buildings / Madhurima Bandyopadhyay in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 2 (February 2017)PermalinkCartographie et interprétation de l'environnement par drone / Martial Sanfourche in Revue Française de Photogrammétrie et de Télédétection, n° 213 - 214 (janvier - avril 2017)PermalinkCentimetric absolute localization using Unmanned Aerial Vehicles with airborne photogrammetry and on-board GPS / Mehdi Daakir (2017)PermalinkEmbedding user-generated content into oblique airborne photogrammetry-based 3D city model / Jianming Liang in International journal of geographical information science IJGIS, vol 31 n° 1-2 (January - February 2017)PermalinkFaucon noir : retour d'expérience sur une étude de la biodiversité par drone / Laurent Beaudoin in Revue Française de Photogrammétrie et de Télédétection, n° 213 - 214 (janvier - avril 2017)PermalinkImplantation dans le matériel de fonctionnalités temps-réel dans une caméra intelligente ultralégère spécialisée pour la prise de vue aérienne / Ahmad Audi (2017)Permalink