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Automatic object extraction from airborne laser scanning point clouds for digital base map production / Elyta Widyaningrum (2021)
Titre : Automatic object extraction from airborne laser scanning point clouds for digital base map production Type de document : Thèse/HDR Auteurs : Elyta Widyaningrum, Auteur Editeur : Delft [Pays-Bas] : Delft University of Technology Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] axe médian
[Termes IGN] chaîne de traitement
[Termes IGN] détection d'objet
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction du réseau routier
[Termes IGN] image aérienne
[Termes IGN] orthoimage
[Termes IGN] semis de points
[Termes IGN] squelettisation
[Termes IGN] transformation de Hough
[Termes IGN] vectorisationRésumé : (auteur) A base map provides essential geospatial information for applications such as urban planning, intelligent transportation systems, and disaster management. Buildings and roads are the main ingredients of a base map and are represented by polygons. Unfortunately, manually delineating their boundaries from remote sensing data is time consuming and labour intensive. Airborne laser scanning (ALS) point clouds provide dense and accurate 3D positional information. Automatic extraction of buildings and roads from 3D point clouds is challenging because of their irregular shapes, occlusions in the data, and irregularity of ALS point clouds. This study focuses on two particular objectives: (i) accurate classification of a large volume of ALS 3D point clouds; and (ii) smooth and accurate building and road outline extraction. To achieve the classification objective, we perform point-wise deep learning to classify an ALS point cloud of a complex urban scene in Surabaya, Indonesia. The point cloud is colored by airborne orthophotos. Training data is obtained from an existing 2D topographic base map by a semi-automatic method proposed in this research. A dynamic-graph convolutional neural network is used to classify the point cloud into four classes: bare land, trees, buildings, and roads. We investigate effective input feature combinations for outdoor point cloud classification. A highly acceptable classification result of 91.8% overall accuracy is achieved when using the full combination of RGB color and LiDAR features. To address the objective of outline extraction, we propose building and road outline extraction methods that run directly on ALS point cloud data. For accurate and smooth building outline extraction, we propose two different methods. First, we develop the ordered Hough transform (OHT), which is an extension of the traditional Hough transform, by explicitly incorporating the sequence of points to form the outline. Second, we propose a new method based on Medial Axis Transform (MAT) skeletons which takes advantage of the skeleton points to detect building corners. The OHT method is resistant to noise but it requires prior knowledge on a building’s main directions. On the contrary, the MAT-based method does not require such orientation initialization but is more sensitive to noise on building edges. We compare the results of our building outline extraction methods to an existing RANSAC-based method, in terms of geometric accuracy, completeness of building corners, and computation time, and demonstrate that the MAT-based approach has the highest geometric accuracy, results in more complete building corners, and is slightly faster than other methods. For road network extraction, we develop a method based on skeletonization, which results in complete and continuous road centerlines and boundaries. In our study area, several roads are disrupted and disconnected due to trees. We design a tree-constrained approach to fill road gaps and integrate road width estimated from a medial axis algorithm. Comparison to reference data shows that the proposed method is able to extract almost all existing roads in the study area, and even detects roads that were not present in the reference due to human errors. We conclude that our object extraction methods enable a complete automatic procedure, extracting more accurate building and road outlines from ALS point cloud data. This contributes to a higher automation readiness level for a faster and cheaper base map production. Numéro de notice : 17664 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Thèse étrangère Note de thèse : PhD thesis : Sciences : TU Delft: 2021 Date de publication en ligne : 10/03/2021 En ligne : https://doi.org/10.4233/uuid:8900fac8-a76c-482a-b280-e1758783b5b3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97984 Consolidation of crowd-sourced geo-ragged data for parameterized travel recommendations / Ago Luberg (2021)
Titre : Consolidation of crowd-sourced geo-ragged data for parameterized travel recommendations Type de document : Thèse/HDR Auteurs : Ago Luberg, Auteur ; Tanel Tammet, Directeur de thèse Editeur : Tallinn [Estonia] : Tallinn University of Technology Année de publication : 2021 Importance : 159 p. Format : 21 x 30 cm Note générale : bibliographie
Dissertation accepted for the defence of the degree of Doctor of Philosophy in Computer ScienceLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] apprentissage automatique
[Termes IGN] base de données
[Termes IGN] conception orientée utilisateur
[Termes IGN] données localisées des bénévoles
[Termes IGN] extraction de données
[Termes IGN] géoréférencement
[Termes IGN] point d'intérêt
[Termes IGN] Riga
[Termes IGN] site wiki
[Termes IGN] système de recommandation
[Termes IGN] Tallinn
[Termes IGN] taxinomie
[Termes IGN] tourismeRésumé : (auteur) The research covered in this thesis is focused on different aspects of the task of creating automated recommendations for tourism, focusing mostly on places of interest like beautiful views, architectural landmarks, charming areas etc. A significant amount of work has been spent on designing and developing actual recommender systems - Sightsplanner, Sightsmap and the automated recommender of Visit Estonia - and their data harvesting methods in order to create a platform for showing the feasibility of the new methods designed and experimented with. The main results of our research are split between three subfields:
• Knowledge engineering: we have shown how to formalize fuzzy and uncertain POI categories along with suitable ontologies and reasoner-based algorithms for object matching and score calculation in a real-life context of actual POI-s, available data and easily expressable user preferences.
• Machine learning: we have designed a learnable detection system for detecting duplicate POIs from different databases, usable for cross- category, cross-language and cross-city datasets.
• We show that learning on Tallinn eateries improved the algorithm parameters to such a degree that on Riga data containing also museums and galleries it gave us 98% accuracy versus 85% accuracy achieved by tuning the algorithm parameters manually.
• Knowledge extraction: we have designed an algorithm for high-quality keyword extraction from short crowd-sourced POI descriptions in different languages, able to find a suitable name and to add suitable types to the POI. Our clusterization algorithm is able to merge the POIs based on the extracted data: on the Panoramio and Wikipedia data about U.K. and French locations it was able to find 56% of Wikipedia objects from the textual titles/annotations of Panoramio pictures in the area.Note de contenu : 1- Introduction
2- Related work
3- Involvement in recommender projects
4- Data acquisition and information extraction
5- Data deduplication (using machine learning)
6- Location category and name detection
7- Data storage and object score calculation
8- Conclusions
9- Future workNuméro de notice : 28600 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse étrangère Note de thèse : PhD Thesis : Computer Science : Tallinn University of Technology : 2021 DOI : 10.23658/taltech.23/2021 En ligne : https://doi.org/10.23658/taltech.23/2021 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99407
Titre : Content-based image retrieval for map georeferencing Type de document : Article/Communication Auteurs : Jonas Luft, Auteur ; Jochen Schiewe, Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2021 Collection : Proceedings of the ICA num. 4 Conférence : ICC 2021, 30th ICA international cartographic conference 14/12/2021 18/12/2021 Florence Italie Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] appariement d'images
[Termes IGN] carte ancienne
[Termes IGN] carte numérisée
[Termes IGN] carte topographique
[Termes IGN] données localisées des bénévoles
[Termes IGN] géoréférencement indirect
[Termes IGN] mesure de similitude
[Termes IGN] recherche d'image basée sur le contenuRésumé : (auteur) In recent years, libraries have made great progress in digitising troves of historical maps with high-resolution scanners. Providing user-friendly information access for cultural heritage through spatial search and webGIS requires georeferencing of the hundreds of thousands of digitised maps. Georeferencing is usually done manually by finding “ground control points”, locations in the digital map image, whose identity is unambiguous and can easily be found in modern-day reference geodata/mapping data. To decide whether two symbols from different maps describe the same object, their semantic and spatial relations need to be matched. Automating this process is the only feasible way to georeference the immense quantities of maps in conceivable time. However, automated solutions for spatial matching quickly fail when faced with incomplete data – which is the greatest challenge when comparing maps of different ages or scales. These problems can be overcome by computing map similarity in the image domain. Treating maps as a special case of image processing allows efficient and robust matching and thus identification of geographical regions without the need to explicitly model semantics. We propose a method to encode worldwide reference VGI mapping data as image features, allowing the construction of an efficient lookup index. With this index, content-based image retrieval can be used for both geolocating a given map for georeferencing with high accuracy. We demonstrate our approach on hundreds of map sheets of different historical topographical survey map series, successfully georeferencing most of them within mere seconds. Numéro de notice : C2021-073 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Communication DOI : 10.5194/ica-proc-4-69-2021 Date de publication en ligne : 03/12/2021 En ligne : https://doi.org/10.5194/ica-proc-4-69-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100007
Titre : Deep learning for feature based image matching Type de document : Thèse/HDR Auteurs : Lin Chen, Auteur ; Christian Heipke, Directeur de thèse Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 2021 Collection : DGK - C, ISSN 0065-5325 num. 867 Importance : 159 p. Format : 21 x 30 cm Note générale : bibliographie
Diese Arbeit ist gleichzeitig veröffentlicht in: Wissenschaftliche Arbeiten der Fachrichtung Geodäsie und Geoinformatik der Leibniz UniversitätHannoverISSN 0174-1454, Nr. 369, Hannover 2021Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] appariement d'images
[Termes IGN] chaîne de traitement
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] descripteur
[Termes IGN] image aérienne oblique
[Termes IGN] orientation d'image
[Termes IGN] orthoimageRésumé : (auteur) Feature based image matching aims at finding matched features between two or more images. It is one of the most fundamental research topics in photogrammetry and computer vision. The matching features area prerequisite for applications such as image orientation, Simultaneous Localization and Mapping (SLAM) and robot vision. A typical feature based matching algorithm is composed of five steps: feature detection, affine shape estimation, orientation, description and descriptor matching. Today, the employment of deep neural network has framed those different steps as machine learning problems and the matching performance has been improved significantly. One of the main reasons why feature based image matching may still prove difficult is the complex change between different images, including geometric and radiometric transformations. If the change between images exceeds a certain level, it will also exceed the tolerance of those aforementioned separate steps and, in turn, cause feature based image matching to fail.
This thesis focuses on improving feature based image matching against large viewpoint and viewing direction change between images. In order to improve the feature based image matching performance under these circumstances, affine shape estimation, orientation and description are solved with deep learning architectures. In particular, Convolutional Neural Networks (CNN) are used. For the affine shape and orientation learning, the main contribution of this thesis is two fold. First, instead of a Siamese CNN, only one branch is needed and the loss is built based on the geometric measures calculated from the mean gradient or second moment matrix. Therefore, for each of the input patches, a global minimum, namely the canonical feature, exists. Second, both the affine shape and orientation are solved simultaneously within one network by combining the loss used for affine shape and orientation learning. To the best of the author’s knowledge, this is the first time these two modules are reported to have been successfully trained simultaneously. For the descriptor learning part, a new weak match is defined. For any input feature patch, a slightly transformed patch that lies far from the input feature patch in descriptor space is defined as a weak match feature. A weak match finder network is proposed to actively find these weak match features. In a following step, the found weak matches are used in the standard descriptor learning framework. In this way, the intra-variance of the appearance of matched feature patch pairs is explored in depth and, accordingly, the invariance of feature descriptors against viewpoint and viewing direction change is improved. The proposed feature based image matching method is evaluated on standard benchmarks and is used to solve for the parameters of image orientation. For the image orientation task, aerial oblique images are taken into account. Through analysis of the experiments conducted for small image blocks, it is shown that deep learning feature based image matching leads to more registered images, more reconstructed 3D points and a more stable block connection.Note de contenu : 1- Introduction
2- Basics
3- Related work
4- Deep learning feature representation
5- Experiments and results
6- Discussion
7- Conclusion and outlookNuméro de notice : 17673 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD dissertation : Fachrichtung Geodäsie und Geoinformatik : Hanovre : 2021 En ligne : https://dgk.badw.de/fileadmin/user_upload/Files/DGK/docs/c-867.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97999 Développement d’outils d’exploitation des archives photographiques aériennes de l’IGN pour caractériser l’évolution pluridécennale du littoral sur l’île de la Réunion / Adinane Oladjidé Ayichemi (2021)
Titre : Développement d’outils d’exploitation des archives photographiques aériennes de l’IGN pour caractériser l’évolution pluridécennale du littoral sur l’île de la Réunion Type de document : Mémoire Auteurs : Adinane Oladjidé Ayichemi, Auteur Editeur : Le Mans : Ecole Supérieure des Géomètres et Topographes ESGT Année de publication : 2021 Importance : 87 p. Format : 21 x 30 cm Note générale : Bibliographie
Mémoire présenté en vue d'obtenir le diplome d'Ingénieur CNAM Spécialité Géomètre et TopographeLangues : Français (fre) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] catastrophe naturelle
[Termes IGN] détection de changement
[Termes IGN] géomorphologie locale
[Termes IGN] géoréférencement
[Termes IGN] image ancienne
[Termes IGN] modèle numérique de surface
[Termes IGN] orthoimage
[Termes IGN] photographie aérienne
[Termes IGN] prévention des risques
[Termes IGN] Réunion, île de la
[Termes IGN] risque naturel
[Termes IGN] superposition d'imagesIndex. décimale : ESGT Mémoires d'ingénieurs de l'ESGT Résumé : (auteur) Pour anticiper l’ampleur des futures catastrophes naturelles, il est courant de revisiter les changements morphologiques liés aux événements passés enregistrés. La Réunion est une île très exposée aux risques naturels majeurs, notamment les cyclones et les mouvements de terrain, qui perturbent sa vie sociale et économique. Les photographies aériennes historiques offrent aujourd’hui une opportunité pour suivre et décrire l’évolution du paysage grâce à la photogrammétrique moderne. Nous exploitons les archives disponibles pour créer et analyser des modèles numériques de surface en vue de quantifier les effets cycloniques dans la rivière des Galets à la Réunion. Dans ce processus de chasse aux changements locaux, un enregistrement robuste des séquences de campagne et un géoréférencement précis sont des facteurs limitatifs clés. Le co-alignement des photographiques issues de deux différentes missions encadrant un cyclone est effectué afin de limiter les erreurs liées à la distorsion des modèles générés lorsqu’ils seront comparés. À l’aide de la carte des zones stéréo-optimales des missions, que nous avons créée, les régions les plus prioritaires ont été repérées pour identifiés des détails topographiques persistants. Ces détails sont relevés par GNSS pour géoréférencer nos modèles. Une évaluation de la qualité des modèles créés est effectuée afin de garantir dans quelle mesure ils sont exploitables pour détecter des changements morphologiques dans la zone d’intérêt. Note de contenu : 1- Contexte scientifique
2- Rapatriement des données brutes
3- Préparation des données nécessaires pour le calcul photogrammétrique
4- Création des MNS et orthophtos
ConclusionNuméro de notice : 28696 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Mémoire ingénieur ESGT Organisme de stage : Bureau de recherches géologiques et minières BRGM En ligne : https://dumas.ccsd.cnrs.fr/MEMOIRES-CNAM/dumas-03526338v1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100467 Dynamics of inundation events in the rivers-estuaries-ocean continuum in Bengal delta : synergy between hydrodynamic modelling and spaceborne remote sensing / Md Jamal Uddin Kahn (2021)PermalinkElevation models for reproducible evaluation of terrain representation / Patrick Kennelly in Cartography and Geographic Information Science, vol 48 n° 1 (January 2021)PermalinkPermalinkPermalinkGeomorphic analysis of Xiadian buried fault zone in Eastern Beijing plain based on SPOT image and unmanned aerial vehicle (UAV) data / Yanping Wang in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)PermalinkGeoreferencing with self-calibration for airborne full-waveform Lidar data using digital elevation model / Qinghua Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 1 (January 2021)PermalinkPermalinkImproving GEDI footprint geolocation using a high resolution digital terrain model / Anouk Schleich (2021)PermalinkPermalinkModélisation et raisonnement spatial flou pour l’aide à la localisation de victimes en montagne / Mattia Bunel (2021)PermalinkOptimisation et développement des solutions photogrammétriques pour la réalisation des relevés de façade au sein du cabinet ELLIPSE Géomètres-Experts / Guillaume Jeannin (2021)PermalinkOptimisation des protocoles de numérisation 3D multi-capteurs et de fusion de données hétérogènes au sein de l'entreprise Premier plan / Elisa Gautron (2021)PermalinkProduction et mise à jour d’un produit BD Forêt V3 par apprentissage profond / Sébastien Giordano (2021)PermalinkQualification des données LiDAR GEDI pour le suivi de l’impact climatique sur la forêt de Südharz / Iris Jeuffrard (2021)PermalinkRemote sensing and GIS / Basudeb Bhatta (2021)PermalinkRendu basé image d'images historiques / Maria Scarlleth Gomes de Castro (2021)PermalinkPermalinkPermalinkStructure-from-motion-derived digital surface models from historical aerial photographs: A new 3D application for coastal dune monitoring / Edoardo Grottoli in Remote sensing, vol 13 n° 1 (January-1 2021)PermalinkSuivi des vignes par télédétection de proximité : le deep learning au service de l’agriculture de précision / Sami Beniaouf (2021)PermalinkThe potential of LiDAR and UAV-photogrammetric data analysis to interpret archaeological sites: A case study of Chun Castle in South-West England / Israa Kadhim in ISPRS International journal of geo-information, vol 10 n° 1 (January 2021)PermalinkPermalinkAdjusting the regular network of squares resolution to the digital terrain model surface shape / Dariusz Gościewski in ISPRS International journal of geo-information, vol 9 n° 12 (December 2020)PermalinkApplication of various strategies and methodologies for landslide susceptibility maps on a basin scale: the case study of Val Tartano, Italy / Vasil Yordanov in Applied geomatics, vol 12 n° 4 (December 2020)PermalinkAutomatic building footprint extraction from UAV images using neural networks / Zoran Kokeza in Geodetski vestnik, vol 64 n° 4 (December 2020 - February 2021)PermalinkDu drone LiDAR à un nuage de points précis et exact : une chaîne de traitement LiDAR adaptée et quasi automatique / Maxime Lafleur in XYZ, n° 165 (décembre 2020)PermalinkForest cover mapping based on a combination of aerial images and Sentinel-2 satellite data compared to National Forest Inventory data / Selina Ganz in Forests, vol 11 n° 12 (December 2020)PermalinkMapping of land cover with open-source software and ultra-high-resolution imagery acquired with unmanned aerial vehicles / Ned Horning in Remote sensing in ecology and conservation, vol 6 n° 4 (December 2020)PermalinkQuality assessment of photogrammetric methods - A workflow for reproducible UAS orthomosaics / Marvin Ludwig in Remote sensing, vol 12 n° 22 (December-1 2020)PermalinkRemote sensing in urban planning: Contributions towards ecologically sound policies? / Thilo Wellmann in Landscape and Urban Planning, vol 204 (December 2020)PermalinkBuilding change detection using a shape context similarity model for LiDAR data / Xuzhe Lyu in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)PermalinkCombination of Landsat 8 OLI and Sentinel-1 SAR time-series data for mapping paddy fields in parts of West and Central Java provinces, Indonesia / Sanjiwana Arjasakusuma in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)PermalinkA deep learning framework for matching of SAR and optical imagery / Lloyd Haydn Hughes in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)PermalinkMacrozonation of seismic transient and permanent ground deformation of Iran / Saeideh Farahani in Natural Hazards and Earth System Sciences, vol 20 n° 11 (November 2020)PermalinkStreets of London: Using Flickr and OpenStreetMap to build an interactive image of the city / Azam Raha Bahrehdar in Computers, Environment and Urban Systems, vol 84 (November 2020)PermalinkTopographic connection method for automated mapping of landslide inventories, study case: semi urban sub-basin from Monterrey, Northeast of México / Nelly L. Ramirez Serrato in Geocarto international, vol 35 n° 15 ([01/11/2020])PermalinkUrban tree species identification and carbon stock mapping for urban green planning and management / MD Abdul Choudhury in Forests, vol 11 n°11 (November 2020)PermalinkComparing features of single and multi-photon lidar in boreal forests / Xiaowei Yu in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)PermalinkGEBCO Gridded Bathymetric Datasets for mapping Japan Trench geomorphology by means of GMT scripting toolset / Polina Lemenkova in Geodesy and cartography, vol 46 n° 3 (October 2020)PermalinkA preliminary exploration of the cooling effect of tree shade in urban landscapes / Qiuyan Yu in International journal of applied Earth observation and geoinformation, vol 92 (October 2020)PermalinkAn overview of clustering methods for geo-referenced time series: from one-way clustering to co- and tri-clustering / Xiaojing Wu in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)PermalinkApplication of 30-meter global digital elevation models for compensating rational polynomial coefficients biases / Amin Alizadeh Naeini in Geocarto international, vol 35 n° 12 ([01/09/2020])PermalinkAssessment of landslide susceptibility at a local spatial scale applying the multi-criteria analysis and GIS: a case study from Slovakia / Jana Vojteková in Geomatics, Natural Hazards and Risk, vol 11 n° 1 (2020)PermalinkComparison of two methods for multiresolution terrain modelling in GIS / Turkay Gokgoz in Geocarto international, vol 35 n° 12 ([01/09/2020])PermalinkHomogeneous tree height derivation from tree crown delineation using Seeded Region Growing (SRG) segmentation / Muhamad Farid Ramli in Geo-spatial Information Science, vol 23 n° 3 (September 2020)PermalinkImproving drainage conditions of forest roads using the GIS and forest road simulator / Mehran Nasiri in Journal of forest science, vol 66 n° 9 (September 2020)PermalinkPost‐filtering with surface orientation constraints for stereo dense image matching / Xu Huang in Photogrammetric record, vol 35 n° 171 (September 2020)PermalinkPrecise extraction of citrus fruit trees from a Digital Surface Model using a unified strategy: detection, delineation, and clustering / Ali Ozgun Ok in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 9 (September 2020)PermalinkThermal and spatial data integration for recreating rebuilding stages of wooden and masonry buildings / Paulina Lewińska in Photogrammetric record, vol 35 n° 171 (September 2020)PermalinkVehicle detection of multi-source remote sensing data using active fine-tuning network / Xin Wu in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)PermalinkCNN semantic segmentation to retrieve past land cover out of historical orthoimages and DSM: first experiments / Arnaud Le Bris in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkConjugate ruptures and seismotectonic implications of the 2019 Mindanao earthquake sequence inferred from Sentinel-1 InSAR data / Bingquan Li in International journal of applied Earth observation and geoinformation, vol 90 (August 2020)PermalinkGuided feature matching for multi-epoch historical image blocks pose estimation / Lulin Zhang in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkStructure from motion for complex image sets / Mario Michelini in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)PermalinkTowards structureless bundle adjustment with two- and three-view structure approximation / Ewelina Rupnik in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkAssessment of USGS DEMs for modelling pothole inundation in the prairie pothole region of Iowa / Priyadarshi Upadhyay in Geocarto international, vol 35 n° 9 ([01/07/2020])PermalinkEffect of spatial correlation on the performances of modernized GPS and Galileo in relative positioning / Noureddine Kheloufi in Geodesy and cartography, vol 46 n° 2 (July 2020)PermalinkA simple distributed water balance model for an urbanized river basin using remote sensing and GIS techniques / Olutoyin Adeola Fashae in Geocarto international, vol 35 n° 9 ([01/07/2020])PermalinkAqueous alteration mapping in Rishabdev ultramafic complex using imaging spectroscopy / Hrishikesh Kumar in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)PermalinkEstimating and interpreting fine-scale gridded population using random forest regression and multisource data / Yun Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkMountain summit detection with Deep Learning: evaluation and comparison with heuristic methods / Rocio Nahime Torres in Applied geomatics, vol 12 n° 2 (June 2020)PermalinkUnsupervised change detection between SAR images based on hypergraphs / Jun Wang in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkAbove-ground biomass estimation of arable crops using UAV-based SfM photogrammetry / Maria Luz Gil-Docampo in Geocarto international, vol 35 n° 7 ([15/05/2020])PermalinkAutomated conflation of digital elevation model with reference hydrographic lines / Timofey Samsonov in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)PermalinkFootprint determination of a spectroradiometer mounted on an unmanned aircraft system / Deepak Gautam in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkGeomorphic Change Detection Using Cost-Effective Structure-from-Motion Photogrammetry: Evaluation of Direct Georeferencing from Consumer-Grade UAS at Orewa Beach (New Zealand) / Stéphane Bertin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 5 (May 2020)PermalinkIntertidal topography mapping using the waterline method from Sentinel-1 & -2 images: The examples of Arcachon and Veys Bays in France / Edward Salameh in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)PermalinkModeling strawberry biomass and leaf area using object-based analysis of high-resolution images / Zhen Guan in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)PermalinkA point cloud feature regularization method by fusing judge criterion of field force / Xijiang Chen in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkRefractive two-view reconstruction for underwater 3D vision / François Chadebecq in International journal of computer vision, vol 128 n° 5 (May 2020)PermalinkMonitoring of landslide activity at the Sirobagarh landslide, Uttarakhand, India, using LiDAR, SAR interferometry and geodetic surveys / Ashutosh Tiwari in Geocarto international, vol 35 n° 5 ([01/04/2020])PermalinkMultitemporal analysis of gully erosion in olive groves by means of digital elevation models obtained with aerial photogrammetric and LIDAR data / Tomás Fernández in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)PermalinkAssessment of dense image matchers for digital surface model generation using airborne and spaceborne images – an update / Yilong Han in Photogrammetric record, vol 35 n° 169 (March 2020)PermalinkClassification and segmentation of mining area objects in large-scale spares Lidar point cloud using a novel rotated density network / Yueguan Yan in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)PermalinkDeep learning for geometric and semantic tasks in photogrammetry and remote sensing / Christian Helpke in Geo-spatial Information Science, vol 23 n° 1 (March 2020)PermalinkEfficient match pair selection for oblique UAV images based on adaptive vocabulary tree / San Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)PermalinkEstimation of variance and spatial correlation width for fine-scale measurement error in digital elevation model / Mikhail L. Uss in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)PermalinkIntegrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images / Wen Dai in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)PermalinkIntegration of remote sensing and GIS to extract plantation rows from a drone-based image point cloud digital surface model / Nadeem Fareed in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)PermalinkA novel method of spatiotemporal dynamic geo-visualization of criminal data, applied to command and control centers for public safety / Mayra Salcedo-Gonzalez in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)PermalinkVariable DEM generalization using local entropy for terrain representation through scale / Paulo Raposo in International journal of cartography, Vol 6 n° 1 (March 2020)PermalinkA LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams / Benjamin Swan in Transactions in GIS, Vol 24 n° 1 (February 2020)PermalinkSome thoughts on measuring earthquake deformation using optical imagery / Min Huang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkStatistical assessment of cartographic product from photogrammetry and fixed-wing UAV acquisition / Ademir Marques Junior in European journal of remote sensing, vol 53 n° 1 (2020)PermalinkThe "Incense Road" from Petra to Gaza: an analysis using GIS and Cost functions / Motti Zohar in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)PermalinkThree-dimensional photogrammetric mapping of cotton bolls in situ based on point cloud segmentation and clustering / Shangpeng Sun in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)PermalinkCombining GF-2 and RapidEye satellite data for mapping mangrove species using ensemble machine-learning methods / Liheng Peng in International Journal of Remote Sensing IJRS, vol 41 n° 3 (15 - 22 janvier 2020)PermalinkModelling the orthoimage accuracy using DEM accuracy and off-nadir angle / Altan Yilmaz in Geocarto international, Vol 35 n° 1 ([02/01/2020])PermalinkSpatial visualization of quantitative landscape changes in an industrial region between 1827 and 1883. Case study Katowice, southern Poland / Paweł Cybulski in Journal of maps, vol 16 n° 1 ([02/01/2020])PermalinkPermalink3D iterative spatiotemporal filtering for classification of multitemporal satellite data sets / Hessah Albanwan in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 1 (January 2020)PermalinkAnalyse, structuration et sémantisation des images aériennes [diaporama] / Valérie Gouet-Brunet (2020)PermalinkPermalinkAssessment 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)PermalinkAutomatic scale estimation of structure from motion based 3D models using laser scalers in underwater scenarios / Klemen Istenič in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)PermalinkCamera orientation, calibration and inverse perspective with uncertainties: a Bayesian method applied to area estimation from diverse photographs / Grégoire Guillet in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)PermalinkPermalinkFusion d'approches photométriques et géométriques pour la création de modèles 3D / Jean Mélou (2020)PermalinkGénération de cartes tactiles photoréalistes pour personnes déficientes visuelles par apprentissage profond / Gauthier Fillières-Riveau in Revue internationale de géomatique, vol 30 n° 1-2 (janvier - juin 2020)PermalinkPermalinkGlobal iterative geometric calibration of a linear optical satellite based on sparse GCPs / Yingdong Pi in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)PermalinkDe l’image optique "multi-stéréo" à la topographie très haute résolution et la cartographie automatique des failles par apprentissage profond / Lionel Matteo (2020)PermalinkMise en place d'un système d’auscultation par photogrammétrie aérienne et comparaison avec un scanner laser 3D / Benoît Brizard (2020)PermalinkNew quantitative indices from 3D modeling by photogrammetry to monitor coral reef environments / Isabel Urbina-Barreto (2020)PermalinkPast and future evolution of French Alpine glaciers in a changing climate: a deep learning glacio-hydrological modelling approach / Jordi Bolibar Navarro (2020)PermalinkPrecise local quasigeoid modelling using GNSS/levelling height anomalies and gravity data / Marek Trojanowicz in Survey review, Vol 52 n°370 (January 2020)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkStreambank topography: an accuracy assessment of UAV-based and traditional 3D reconstructions / Benjamin U. Meinen in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)PermalinkLe temps dans la géolocalisation par satellites / Sébastien Trilles (2020)PermalinkTest du potentiel de l’imagerie satellite haute résolution pour le suivi des mouvements gravitaires des falaises crayeuses de Seine-Maritime / Zoé Stroebele (2020)PermalinkThree-dimensional reconstruction of fluvial surface sedimentology and topography using personal mobile laser scanning / Richard David Williams in Earth surface processes and landforms, vol 45 n° 1 (January 2020)PermalinkVery high resolution land cover mapping of urban areas at global scale with convolutional neural network / Thomas Tilak (2020)PermalinkPermalinkPermalinkApplication of photogrammetry to generate quantitative geobody data in ephemeral fluvial systems / Charlotte L. Priddy in Photogrammetric record, vol 34 n° 168 (December 2019)PermalinkCombining 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)PermalinkDeep learning for conifer/deciduous classification of airborne LiDAR 3D point clouds representing individual trees / Hamid Hamraz in ISPRS Journal of photogrammetry and remote sensing, Vol 158 (December 2019)PermalinkInnovative techniques of photogrammetry for 3D modeling / Vicenzo Barrile in Applied geomatics, Vol 11 n° 4 (December 2019)PermalinkInside 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)PermalinkA learning approach to evaluate the quality of 3D city models / Oussama Ennafii in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 12 (December 2019)PermalinkA 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)PermalinkUn modèle de transcription pour identifier et analyser les objets de référence et les relations spatiales utilisées pour se localiser en montagne / Mattia Bunel in Cartes & Géomatique, n° 241-242 (décembre 2019)PermalinkNouvelle donne aérienne / Marielle Mayo in Géomètre, n° 2175 (décembre 2019)PermalinkPré-localisation des données pour la modélisation 3D de tunnels : développements et évaluations / Christophe Heinkelé in Revue Française de Photogrammétrie et de Télédétection, n° 221 (novembre 2019)PermalinkLa Terre en 4D : apport des séries temporelles de modèles numériques d'élévation par photogrammétrie spatiale pour l'étude de la surface terrestre / César Deschamps-Berger in Revue Française de Photogrammétrie et de Télédétection, n° 221 (novembre 2019)PermalinkSegmenting mangrove ecosystems drone images using SLIC superpixels / Edward Zimudzi in Geocarto international, vol 34 n° 14 ([30/10/2019])PermalinkA CNN-based subpixel level DSM generation approach via single image super-resolution / Yongjun Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 10 (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)PermalinkMultiple-view geospatial comparison using web-based virtual globes / Liangfeng Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 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)PermalinkMapping of forest tree distribution and estimation of forest biodiversity using Sentinel-2 imagery in the University Research Forest Taxiarchis in Chalkidiki, Greece / Maria Kampouri in Geocarto international, vol 34 n° 12 ([15/09/2019])PermalinkComparison of filtering algorithms used for DTM production from airborne lidar data: a case study in Bergama, Turkey / Baris Suleymanoglu in Geodetski vestnik, vol 63 n° 3 (September - November 2019)PermalinkDelineation of vacant building land using orthophoto and lidar data object classification / Dejan Jenko in Geodetski vestnik, vol 63 n° 3 (September - November 2019)PermalinkEnhanced 3D mapping with an RGB-D sensor via integration of depth measurements and image sequences / Bo Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 9 (September 2019)PermalinkGeometric accuracy improvement of WorldView‐2 imagery using freely available DEM data / Mateo Gašparović in Photogrammetric record, vol 34 n° 167 (September 2019)PermalinkModelling discontinuous terrain from DSMs using segment labelling, outlier removal and thin-plate splines / Kassel Hingee in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)PermalinkPpC: a new method to reduce the density of lidar data. Does it affect the DEM accuracy? / Sandra Bujan in Photogrammetric record, vol 34 n° 167 (September 2019)PermalinkTopographie et archéologie, du cordeau au tout numérique : plus de 40 ans d'interactions / Bertrand Chazaly in XYZ, n° 160 (septembre 2019)PermalinkIncreasing precision for French forest inventory estimates using the k-NN technique with optical and photogrammetric data and model-assisted estimators / Dinesh Babu Irulappa-Pillai-Vijayakumar in Remote sensing, vol 11 n° 8 (August 2019)PermalinkTotal Vertical Uncertainty (TVU) modeling for topo-bathymetric LIDAR systems / Firat Eren in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 8 (August 2019)PermalinkAnalysis of free image-based modelling systems applied to support topographic measurements / José Miguel Caldera-Cordero in Survey review, vol 51 n° 367 (July 2019)PermalinkHigh-resolution large-area digital orthophoto map generation using LROC NAC images / Kaichang Di in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)PermalinkMonitoring of extreme land hydrology events in central Poland using GRACE, land surface models and absolute gravity data / Joanna Kuczynska-Siehien in Journal of applied geodesy, vol 13 n° 3 (July 2019)PermalinkUsing direct transformation approach as an alternative technique to fuse global digital elevation models with GPS/levelling measurements in Egypt / Hossam Talaat Elshambaky in Journal of applied geodesy, vol 13 n° 3 (July 2019)PermalinkError propagation for the Molodensky G1 term / Jack C. McCubbine in Journal of geodesy, vol 93 n°6 (June 2019)PermalinkTélédétection radar : de l'image d'intensité initiale au choix du mode de calibration des coefficients de diffusion / Jean-Paul Rudant in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - octobre 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])PermalinkDigital surface model generation from high resolution multi-view stereo satellite imagery / Ke Gong in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 5 (May 2019)PermalinkEstimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery / Yanan Liu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)PermalinkRetrieving soil surface roughness with the Hapke photometric model: Confrontation with the ground truth / Sébastien Labarre in Remote sensing of environment, vol 225 (May 2019)PermalinkRobust structure from motion based on relative rotations and tie points / Xin Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 5 (May 2019)PermalinkBIM-PoseNet: Indoor camera localisation using a 3D indoor model and deep learning from synthetic images / Debaditya Acharya in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)PermalinkJournées de la recherche 2019 / Anonyme in Géomatique expert, n° 127 (avril - mai 2019)PermalinkOrléans monte sa maquette virtuelle / Anonyme in Géomatique expert, n° 127 (avril - mai 2019)PermalinkRobust external calibration of terrestrial laser scanner and digital camera for structural monitoring / Mohammad Omidalizarandi in Journal of applied geodesy, vol 13 n° 2 (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)PermalinkBuilding detection and regularisation using DSM and imagery information / Yousif A. Mousa in Photogrammetric record, vol 34 n° 165 (March 2019)PermalinkLand cover classification in combined elevation and optical images supported by OSM data, mixed-level features, and non-local optimization algorithms / Dimitri Bulatov in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 3 (March 2019)PermalinkMethod for an automatic alignment of imagery and vector data applied to cadastral information in Poland / Juan J. Ruiz-Lendínez in Survey review, vol 51 n° 365 (March 2019)PermalinkNumérisation et modélisation 3D du Jardin d’Hiver du Musée de la Faïence de Sarreguemines / Valentin Girardet in XYZ, n° 158 (mars 2019)PermalinkTemporal and spatial high-resolution climate data from 1961 to 2100 for the German National Forest Inventory (NFI) / Helge Dietrich in Annals of Forest Science, vol 76 n° 1 (March 2019)PermalinkDiffusion and inpainting of reflectance and height LiDAR orthoimages / Pierre Biasutti in Computer Vision and image understanding, vol 179 (February 2019)PermalinkSeamline network generation based on foreground segmentation for orthoimage mosaicking / Li Li in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)PermalinkTanDEM-X digital surface models in boreal forest above-ground biomass change detection / Kirsi Karila in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)PermalinkThe orthographic projection model for pose calibration of long focal images / Laura F. Julià in IPOL Journal, Image Processing On Line, vol 9 (2019)PermalinkPermalinkAnalysis of the usability of mobile laser scanning data in snowy conditions / Mathilde Letard (2019)PermalinkApports des techniques photogrammétriques à l'étude du dynamisme des structures volcaniques du piton de la Fournaise / Allan Derrien (2019)PermalinkArchival aerial photogrammetric surveys, a data source to study land use/cover evolution over the last century : opportunities and issues / Arnaud Le Bris (2019)PermalinkAutomatic determination of stream networks from DEMs by using road network data to locate culverts / Ville Mäkinen in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)PermalinkPermalinkEnrichissement d'orthophotographie par des données OpenStreetMap pour l'apprentissage machine / Gauthier Fillières-Riveau (2019)PermalinkForest inventory sensitivity to UAS-based image processing algorithms / Bonifasius Maturbongs in Annals of forest research, vol 62 n° 1 (January - June 2019)PermalinkFusion de sets de photos provenant de capteurs différents dans le domaine de l’archéologie / Hugo De Paulis (2019)PermalinkHyperparameter optimization of neural network-driven spatial models accelerated using cyber-enabled high-performance computing / Minrui Zheng in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)PermalinkPermalinkIndividual tree detection and crown delineation with 3D information from multi-view satellite Images / Changlin Xiao in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)PermalinkPermalinkPermalinkPermalinkSemantic aware quality evaluation of 3D building models : Modeling and simulation / Oussama Ennafii (2019)PermalinkSimultaneous chain-forming and generalization of road networks / Susanne Wenzel in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)PermalinkSoftware comparison for underwater archaeological photogrammetric applications / Marinos Vlachos (2019)PermalinkSpatial decision support in urban environments using machine learning, 3D geo-visualization and semantic integration of multi-source data / Nikolaos Sideris (2019)PermalinkStructure 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)PermalinkPermalinkPermalink4-dimensional recording and visualization of urban archeological excavations / Gabriele Bitelli in Applied geomatics, vol 10 n° 4 (December 2018)PermalinkDEM refinement by low vegetation removal based on the combination of full waveform data and progressive TIN densification / Hongchao Ma in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)PermalinkDetection of individual trees in urban alignment from airborne data and contextual information: A marked point process approach / Josselin Aval in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)Permalink