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Auteur Norman Kerle |
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Affiner la recherche Interroger des sources externesAccuracy assessment of real-time kinematics (RTK) measurements on unmanned aerial vehicles (UAV) for direct geo-referencing / Desta Ekaso in Geo-spatial Information Science, vol 23 n° 2 (June 2020)
Titre : Accuracy assessment of real-time kinematics (RTK) measurements on unmanned aerial vehicles (UAV) for direct geo-referencing Type de document : Article/Communication Auteurs : Desta Ekaso, Auteur ; Francesco Nex, Auteur ; Norman Kerle, Auteur Année de publication : 2020 Article en page(s) : pp 165 - 181 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] aérotriangulation
[Termes IGN] centrale inertielle
[Termes IGN] géoréférencement direct
[Termes IGN] image captée par drone
[Termes IGN] instrument embarqué
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] précision du positionnement
[Termes IGN] récepteur GNSSRésumé : (auteur) Geospatial information acquired with Unmanned Aerial Vehicles (UAV) provides valuable decision-making support in many different domains, and technological advances coincide with a demand for ever more sophisticated data products. One consequence is a research and development focus on more accurately referenced images and derivatives, which has long been a weakness especially of low to medium cost UAV systems equipped with relatively inexpensive inertial measurement unit (IMU) and Global Navigation Satellite System (GNSS) receivers. This research evaluates the positional accuracy of the real-time kinematics (RTK) GNSS on the DJI Matrice 600 Pro, one of the first available and widely used UAVs with potentially surveying-grade performance. Although a very high positional accuracy of the drone itself of 2 to 3 cm is claimed by DJI, the actual accuracy of the drone RTK for positioning the images and for using it for mapping purposes without additional ground control is not known. To begin with, the actual GNSS RTK position of reference center (the physical point on the antenna) on the drone is not indicated, and uncertainty regarding this also exists among the professional user community. In this study the reference center was determined through a set of experiments using the dual frequency static Leica GNSS with RTK capability. The RTK positioning data from the drone were then used for direct georeferencing, and its results were evaluated. Test flights were carried out over a 70 x 70 m area with an altitude of 40 m above the ground, with a ground sampling distance of 1.3 cm. Evaluated against ground control points, the planimetric accuracy of direct georeferencing for the photogrammetric product ranged between 30 and 60 cm. Analysis of direct georeferencing results showed a time delay of up to 0.28 seconds between the drone GNSS RTK and camera image acquisition affecting direct georeferencing results. Numéro de notice : A2020-319 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/10095020.2019.1710437 Date de publication en ligne : 23/01/2020 En ligne : https://doi.org/10.1080/10095020.2019.1710437 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95184
in Geo-spatial Information Science > vol 23 n° 2 (June 2020) . - pp 165 - 181[article]Mapping and the citizen sensor, ch 6. Considerations of privacy, ethics and legal issues in volunteered geographic information / Peter Mooney (2017)
Titre de série : Mapping and the citizen sensor, ch 6 Titre : Considerations of privacy, ethics and legal issues in volunteered geographic information Type de document : Chapitre/Contribution Auteurs : Peter Mooney, Auteur ; Ana-Maria Olteanu-Raimond Editeur : Londres : Ubiquity press Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] données localisées des bénévoles
[Termes IGN] droit
[Termes IGN] éthique
[Termes IGN] protection de la vie privéeRésumé : (auteur) Today almost any kind of User Generated Content (UGC) can be situated within a geographic context. Volunteered Geographic Information (VGI) can include many types of UGC, such as georeferenced photographs, social media and text, geographic data themselves, etc. There are legal, privacy and ethical issues raised by VGI, and at present these are not very well studied or understood despite the rise in popularity of VGI. This chapter will discuss, investigate and define some of the most prominent issues related to the legal, privacy and ethics topic within VGI. The chapter argues that these issues are not well understood by all of the actors in VGI, and in particular by the producers of this information as well as the users or consumers of this new data source. Creating a better understanding of these issues will be very important in the future development and evolution of VGI in society. Numéro de notice : H2017-019 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Chapître / contribution nature-HAL : ChOuvrScient DOI : 10.5334/bbf.f Date de publication en ligne : 11/09/2017 En ligne : https://doi.org/10.5334/bbf.f Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89339 
Titre : Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information Type de document : Article/Communication Auteurs : Linda M. See, Auteur ; Peter Mooney, Auteur ; Giles M. Foody, Auteur ; Lucy Bastin, Auteur ; Alexis Comber, Auteur ; Jacinto Estima, Auteur ; Steffen Fritz, Auteur ; Norman Kerle, Auteur ; Bin Jiang, Auteur ; Mari Laakso, Auteur ; Hai-Ying Liu, Auteur ; Grega Milčinski, Auteur ; Matej Nikšič, Auteur ; Marco Painho, Auteur ; Andrea Pődör, Auteur ; Ana-Maria Olteanu-Raimond Année de publication : 2016 Article en page(s) : pp 1 - 23 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse du discours
[Termes IGN] cartographie collaborative
[Termes IGN] citoyen
[Termes IGN] données localisées des bénévoles
[Termes IGN] état de l'art
[Termes IGN] participation du public
[Termes IGN] production participative
[Termes IGN] science citoyenne
[Termes IGN] terminologieRésumé : (Auteur) Citizens are increasingly becoming an important source of geographic information, sometimes entering domains that had until recently been the exclusive realm of authoritative agencies. This activity has a very diverse character as it can, amongst other things, be active or passive, involve spatial or aspatial data and the data provided can be variable in terms of key attributes such as format, description and quality. Unsurprisingly, therefore, there are a variety of terms used to describe data arising from citizens. In this article, the expressions used to describe citizen sensing of geographic information are reviewed and their use over time explored, prior to categorizing them and highlighting key issues in the current state of the subject. The latter involved a review of ~100 Internet sites with particular focus on their thematic topic, the nature of the data and issues such as incentives for contributors. This review suggests that most sites involve active rather than passive contribution, with citizens typically motivated by the desire to aid a worthy cause, often receiving little training. As such, this article provides a snapshot of the role of citizens in crowdsourcing geographic information and a guide to the current status of this rapidly emerging and evolving subject. Numéro de notice : A2016--119 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi5050055 En ligne : http://dx.doi.org/10.3390/ijgi5050055 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84782
in ISPRS International journal of geo-information > vol 5 n° 5 (May 2016) . - pp 1 - 23[article]Documents numériques
en open access
Crowdsourcing, Citizen Science or VGI ... - pdf éditeurAdobe Acrobat PDF
Titre : VGI quality control Type de document : Article/Communication Auteurs : Cidália Costa Fonte, Auteur ; Lucy Bastin, Auteur ; Giles M. Foody, Auteur ; Tobias Kellenberger, Auteur ; Norman Kerle, Auteur ; Peter Mooney, Auteur ; Ana-Maria Olteanu-Raimond Année de publication : 2015 Conférence : ISPRS 2015, Geospatial Week : Laserscanning, ISSDQ, CMRT, ISA, GeoVIS, GeoBigData 28/09/2015 03/10/2015 La Grande Motte France ISPRS OA Annals Article en page(s) : pp 317 - 324 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] acquisition de données
[Termes IGN] contrôle qualité
[Termes IGN] données localisées des bénévoles
[Termes IGN] participation du public
[Termes IGN] qualité des donnéesMots-clés libres : Volunteered Geographic Information (VGI), Data Quality, National Mapping Agency (NMA), Crowd-sourcing, Citizen Science Résumé : (auteur) This paper presents a framework for considering quality control of volunteered geographic information (VGI). Different issues need to be considered during the conception, acquisition and post-acquisition phases of VGI creation. This includes items such as collecting metadata on the volunteer, providing suitable training, giving corrective feedback during the mapping process and use of control data, among others. Two examples of VGI data collection are then considered with respect to this quality control framework, i.e. VGI data collection by National Mapping Agencies and by the most recent Geo-Wiki tool, a game called Cropland Capture. Although good practices are beginning to emerge, there is still the need for the development and sharing of best practice, especially if VGI is to be integrated with authoritative map products or used for calibration and/or validation of land cover in the future. Numéro de notice : A2015--055 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W5-317-2015 Date de publication en ligne : 20/08/2015 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W5-317-2015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83455
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 W5 (October 2015) . - pp 317 - 324[article]Documents numériques
en open access
VGI quality controlAdobe Acrobat PDF
Titre : Active learning in the spatial domain for remote sensing image classification Type de document : Article/Communication Auteurs : André Stumpf, Auteur ; Nicolas Lachiche, Auteur ; Jean-Philippe Malet, Auteur ; Norman Kerle, Auteur ; Anne Puissant, Auteur Année de publication : 2014 Article en page(s) : pp 2492 - 2507 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] algorithme d'apprentissage
[Termes IGN] analyse de sensibilité
[Termes IGN] classification par arbre de décision
[Termes IGN] incertitude des données
[Termes IGN] inventaire
[Termes IGN] méthode heuristique
[Termes IGN] penteRésumé : (Auteur) Active learning (AL) algorithms have been proven useful in reducing the number of required training samples for remote sensing applications; however, most methods query samples pointwise without considering spatial constraints on their distribution. This may often lead to a spatially dispersed distribution of training points unfavorable for visual image interpretation or field surveys. The aim of this study is to develop region-based AL heuristics to guide user attention toward a limited number of compact spatial batches rather than distributed points. The proposed query functions are based on a tree ensemble classifier and combine criteria of sample uncertainty and diversity to select regions of interest. Class imbalance, which is inherent to many remote sensing applications, is addressed through stratified bootstrap sampling. Empirical tests of the proposed methods are performed with multitemporal and multisensor satellite images capturing, in particular, sites recently affected by large-scale landslide events. The assessment includes an experimental evaluation of the labeling time required by the user and the computational runtime, and a sensitivity analysis of the main algorithm parameters. Region-based heuristics that consider sample uncertainty and diversity are found to outperform pointwise sampling and region-based methods that consider only uncertainty. Reference landslide inventories from five different experts enable a detailed assessment of the spatial distribution of remaining errors and the uncertainty of the reference data. Numéro de notice : A2014-261 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2262052 Date de publication en ligne : 12/07/2013 En ligne : https://doi.org/10.1109/TGRS.2013.2262052 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33164
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 5 tome 1 (May 2014) . - pp 2492 - 2507[article]Exemplaires(1)
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