Descripteur
Termes IGN > géomatique > données localisées
données localiséesSynonyme(s)spatial data ;données géospatiales ;données géographiques données à référence spatialeVoir aussi |
Documents disponibles dans cette catégorie (3735)
![](./images/expand_all.gif)
![](./images/collapse_all.gif)
Etendre la recherche sur niveau(x) vers le bas
Pedestrian network generation based on crowdsourced tracking data / Xue Yang in International journal of geographical information science IJGIS, vol 34 n° 5 (May 2020)
![]()
[article]
Titre : Pedestrian network generation based on crowdsourced tracking data Type de document : Article/Communication Auteurs : Xue Yang, Auteur ; Luliang Tang, Auteur ; Chang Ren, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1051 - 1074 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] approche participative
[Termes IGN] base de données multi-représentation
[Termes IGN] correction géométrique
[Termes IGN] correction topographique
[Termes IGN] dimension fractale
[Termes IGN] données localisées des bénévoles
[Termes IGN] estimation par noyau
[Termes IGN] mobilité urbaine
[Termes IGN] navigation pédestre
[Termes IGN] regroupement de pointsRésumé : (auteur) Pedestrian networks play an important role in various applications, such as pedestrian navigation services and mobility modeling. This paper presents a novel method to extract pedestrian networks from crowdsourced tracking data based on a two-layer framework. This framework includes a walking pattern classification layer and a pedestrian network generation layer. In the first layer, we propose a multi-scale fractal dimension (MFD) algorithm in order to recognize the two different types of walking patterns: walking with a clear destination (WCD) or walking without a clear destination (WOCD). In the second layer, we generate the pedestrian network by combining the pedestrian regions and pedestrian paths. The pedestrian regions are extracted based on a modified connected component analysis (CCA) algorithm from the WOCD traces. We generate the pedestrian paths using a kernel density estimation (KDE)-based point clustering algorithm from the WCD traces. The pedestrian network generation results using two actual crowdsourced datasets show that the proposed method has good performance in both geometrical correctness and topological correctness. Numéro de notice : A2020-207 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1702197 Date de publication en ligne : 09/12/2019 En ligne : https://doi.org/10.1080/13658816.2019.1702197 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94888
in International journal of geographical information science IJGIS > vol 34 n° 5 (May 2020) . - pp 1051 - 1074[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2020051 RAB Revue Centre de documentation En réserve L003 Disponible Toward a standardized encoding of remote sensing geo-positioning sensor models / Meng Jin in Remote sensing, vol 12 n° 9 (May 2020)
![]()
[article]
Titre : Toward a standardized encoding of remote sensing geo-positioning sensor models Type de document : Article/Communication Auteurs : Meng Jin, Auteur ; Yuqi Bai, Auteur ; Emmanuel Devys , Auteur ; Liping Di, Auteur
Année de publication : 2020 Projets : 3-projet - voir note / Article en page(s) : n° 1530 Note générale : bibliographie
M.J. and Y.B. were funded by the National Key Research and Development Program of China (No. 2016YFF0202705, PI: Jiankun Guo). L.D. was funded by USGS/FGDC (No. G15AC00508, PI: Liping Di).Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] données localisées
[Termes IGN] interopérabilité
[Termes IGN] Sensor Web Enablement
[Termes IGN] SensorML
[Termes IGN] standard OGCRésumé : (auteur) Geolocation information is an important feature of remote sensing image data that is captured through a variety of passive or active observation sensors, such as push-broom electro-optical sensor, synthetic aperture radar (SAR), light detection and ranging (LIDAR) and sound navigation and ranging (SONAR). As a fundamental processing step to locate an image, geo-positioning is used to determine the ground coordinates of an object from image coordinates. A variety of sensor models have been created to describe geo-positioning process. In particular, Open Geospatial Consortium (OGC) has defined the Sensor Model Language (SensorML) specification in its Sensor Web Enablement (SWE) initiative to describe sensors including the geo-positioning process. It has been realized using syntax from the extensible markup language (XML). Besides, two standards defined by the International Organization for Standardization (ISO), ISO 19130-1 and ISO 19130-2, introduced a physical sensor model, a true replacement model, and a correspondence model for the geo-positioning process. However, a standardized encoding for geo-positioning sensor models is still missing for the remote sensing community. Thus, the interoperability of remote sensing data between application systems cannot be ensured. In this paper, a standardized encoding of remote sensing geo-positioning sensor models is introduced. It is semantically based on ISO 19130-1 and ISO 19130-2, and syntactically based on OGC SensorML. It defines a cross mapping of the sensor models defined in ISO 19130-1 and ISO 19130-2 to the SensorML, and then proposes a detailed encoding method to finalize the XML schema (an XML schema here is the structure to define an XML document), which will become a profile of OGC SensorML. It seamlessly unifies the sensor models defined in ISO 19130-1, ISO 19130-2, and OGC SensorML. By enabling a standardized description of sensor models used to produce remote sensing data, this standard is very promising in promoting data interoperability, mobility, and integration in the remote sensing domain. Numéro de notice : A2020-333 Affiliation des auteurs : IGN+Ext (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs12091530 Date de publication en ligne : 11/05/2020 En ligne : https://doi.org/10.3390/rs12091530 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96867
in Remote sensing > vol 12 n° 9 (May 2020) . - n° 1530[article]La télédétection aéroportée pour la gestion des territoires forestiers de montagne / Jean-Matthieu Monnet in Sciences, eaux & territoires, n° 33 (avril 2020)
![]()
[article]
Titre : La télédétection aéroportée pour la gestion des territoires forestiers de montagne Type de document : Article/Communication Auteurs : Jean-Matthieu Monnet, Auteur ; Pierre Paccard, Auteur ; Catherine Riond, Auteur Année de publication : 2020 Article en page(s) : pp 64 - 69 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] abattage (sylviculture)
[Termes IGN] acquisition de données
[Termes IGN] diffusion de données
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt alpestre
[Termes IGN] France (végétation)
[Termes IGN] gestion forestière
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) Le Programme national de la forêt et du bois 2016-2026 affiche comme objectif « d’augmenter les prélèvements de bois en France tout en assurant le renouvellement de la forêt ». Les forêts de montagne qui représentent environ un quart de la surface forestière pourraient contribuer de manière significative à cet objectif. Les contraintes d’accès et de topographie rendent cependant difficile la gestion de ces forêts. En s’appuyant sur la technologie Lidar aéroporté, il est désormais possible de cartographier à haute résolution, sur des territoires de la taille d’un parc naturel régional, les caractéristiques forestières (ressource, accessibilité) intéressant les gestionnaires. La généralisation de l’outil pose cependant des questions de coût d’acquisition des données et de droit de leur diffusion auprès des acteurs de la filière. Numéro de notice : A2020-182 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.14758/SET-REVUE.2020.3.12 Date de publication en ligne : 10/04/2020 En ligne : https://doi.org/10.14758/SET-REVUE.2020.3.12 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94956
in Sciences, eaux & territoires > n° 33 (avril 2020) . - pp 64 - 69[article]Accounting for spatiotemporal correlations of GNSS coordinate time series to estimate station velocities / Clément Benoist in Journal of geodynamics, vol 135 (April 2020)
![]()
[article]
Titre : Accounting for spatiotemporal correlations of GNSS coordinate time series to estimate station velocities Type de document : Article/Communication Auteurs : Clément Benoist , Auteur ; Xavier Collilieux
, Auteur ; Paul Rebischung
, Auteur ; Zuheir Altamimi
, Auteur ; Olivier Jamet
, Auteur ; Laurent Métivier
, Auteur ; Kristel Chanard
, Auteur ; Liliane Bel, Auteur
Année de publication : 2020 Projets : GEODESIE / Coulot, David, Université de Paris / Clerici, Christine Article en page(s) : n° 101693 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] corrélation
[Termes IGN] covariance
[Termes IGN] données spatiotemporelles
[Termes IGN] repère de référence terrestre conventionnel
[Termes IGN] série temporelle
[Termes IGN] vitesseRésumé : (auteur) It is well known that GNSS permanent station coordinate time series exhibit time-correlated noise. Spatial correlations between coordinate time series of nearby stations are also long-established and generally handled by means of spatial filtering techniques. Accounting for both the temporal and spatial correlations of the noise via a spatiotemporal covariance model is however not yet a common practice. We demonstrate in this paper the interest of using such a spatiotemporal covariance model of the stochastic variations in GNSS time series in order to estimate long-term station coordinates and especially velocities.
We provide a methodology to rigorously assess the covariances between horizontal coordinate variations and use it to derive a simple exponential spatiotemporal covariance model for the stochastic variations in the IGS repro2 station coordinate time series. We then use this model to estimate station velocities for two selected datasets of 10 time series in Europe and 11 time series in the USA. We show that coordinate prediction as well as velocity determination from short time series are improved when using this spatiotemporal model, as compared with the case where spatiotemporal correlations are ignored.Numéro de notice : A2020-460 Affiliation des auteurs : Géodésie+Ext (mi2018-2019) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jog.2020.101693 Date de publication en ligne : 13/01/2020 En ligne : https://doi.org/10.1016/j.jog.2020.101693 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95385
in Journal of geodynamics > vol 135 (April 2020) . - n° 101693[article]A citSci approach for rapid earthquake intensity mapping: a case study from Istanbul (Turkey) / Ilyas Yalcin in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)
![]()
[article]
Titre : A citSci approach for rapid earthquake intensity mapping: a case study from Istanbul (Turkey) Type de document : Article/Communication Auteurs : Ilyas Yalcin, Auteur ; Sultan Aksakal Kocaman, Auteur ; Candan Gokceoglu, Auteur Année de publication : 2020 Article en page(s) : 15 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] carte sismologique
[Termes IGN] données localisées des bénévoles
[Termes IGN] gestion des risques
[Termes IGN] Istanbul (Turquie)
[Termes IGN] krigeage
[Termes IGN] risque naturel
[Termes IGN] science citoyenneRésumé : (auteur) Nowadays several scientific disciplines utilize Citizen Science (CitSci) as a research approach. Natural hazard research and disaster management also benefit from CitSci since people can provide geodata and the relevant attributes using their mobile devices easily and rapidly during or after an event. An earthquake, depending on its intensity, is among the highly destructive natural hazards. Coordination efforts after a severe earthquake event are vital to minimize its harmful effects and timely in-situ data are crucial for this purpose. The aim of this study is to perform a CitSci pilot study to demonstrate the usability of data obtained by volunteers (citizens) for creating earthquake iso-intensity maps in a short time. The data were collected after a 5.8 Mw Istanbul earthquake which occurred on 26 September 2019. Through the mobile app “I felt the quake”, citizen observations regarding the earthquake intensity were collected from various locations. The intensity values in the app represent a revised form of the Mercalli intensity scale. The iso-intensity map was generated using a spatial kriging algorithm and compared with the one produced by The Disaster and Emergency Management Presidency (AFAD), Turkey, empirically. The results show that collecting the intensity information via trained users is a plausible method for producing such maps. Numéro de notice : A2020-264 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040266 Date de publication en ligne : 20/04/2020 En ligne : https://doi.org/10.3390/ijgi9040266 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95027
in ISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 15 p.[article]Crowdsource mapping of target buildings in hazard: the utilization of smartphone technologies and geographic services / Mohammad H. Vahidnia in Applied geomatics, vol 12 n° 1 (April 2020)
PermalinkDirectionally constrained fully convolutional neural network for airborne LiDAR point cloud classification / Congcong Wen in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)
PermalinkPermalinkMonitoring 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)
PermalinkOnline flu epidemiological deep modeling on disease contact network / Liang Zhao in Geoinformatica, vol 24 n° 2 (April 2020)
PermalinkRecognizing linear building patterns in topographic data by using two new indices based on Delaunay triangulation / Xianjin He in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)
PermalinkSpatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China / Mingyue Wang in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)
PermalinkTechniques for efficient detection of rapid weather changes and analysis of their impacts on a highway network / Adil Alim in Geoinformatica, vol 24 n° 2 (April 2020)
PermalinkThe direct geodesic problem and an approximate analytical solution in Cartesian coordinates on a triaxial ellipsoid / Georgios Panou in Journal of applied geodesy, vol 14 n° 2 (April 2020)
Permalink