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GANmapper: geographical data translation / Abraham Noah Wu in International journal of geographical information science IJGIS, vol 36 n° 7 (juillet 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 7 (juillet 2022) . - pp 1394 - 1422 Titre : GANmapper: geographical data translation Type de document : Article/Communication Auteurs : Abraham Noah Wu, Auteur ; Filip Biljecki, Auteur Année de publication : 2022 Article en page(s) : pp 1394 - 1422 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie [Termes IGN] apprentissage automatique [Termes IGN] bâtiment [Termes IGN] distance de Fréchet [Termes IGN] empreinte [Termes IGN] morphologie urbaine [Termes IGN] réseau antagoniste génératif [Termes IGN] réseau routier [Termes IGN] système d'information géographique [Termes IGN] texture d'image Résumé : (auteur) We present a new method to create spatial data using a generative adversarial network (GAN). Our contribution uses coarse and widely available geospatial data to create maps of less available features at the finer scale in the built environment, bypassing their traditional acquisition techniques (e.g. satellite imagery or land surveying). In the work, we employ land use data and road networks as input to generate building footprints and conduct experiments in 9 cities around the world. The method, which we implement in a tool we release openly, enables the translation of one geospatial dataset to another with high fidelity and morphological accuracy. It may be especially useful in locations missing detailed and high-resolution data and those that are mapped with uncertain or heterogeneous quality, such as much of OpenStreetMap. The quality of the results is influenced by the urban form and scale. In most cases, the experiments suggest promising performance as the method tends to truthfully indicate the locations, amount, and shape of buildings. The work has the potential to support several applications, such as energy, climate, and urban morphology studies in areas previously lacking required data or inpainting geospatial data in regions with incomplete data. Numéro de notice : A2022-493 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2041643 Date de publication en ligne : 08/03/2022 En ligne : https://doi.org/10.1080/13658816.2022.2041643 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100975 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2022071	SL	Revue	Centre de documentation	Revues en salle	Disponible

Efficient image dataset classification difficulty estimation for predicting deep-learning accuracy / Florian Scheidegger in The Visual Computer, vol 37 n° 6 (June 2021)  

Public [article]  inThe Visual Computer > vol 37 n° 6 (June 2021) . - pp 1593 - 1610 Titre : Efficient image dataset classification difficulty estimation for predicting deep-learning accuracy Type de document : Article/Communication Auteurs : Florian Scheidegger, Auteur ; Roxana Istrate, Auteur ; Giovanni Mariani, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1593 - 1610 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] architecture de réseau [Termes IGN] classification par nuées dynamiques [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] distance de Fréchet [Termes IGN] extraction de traits caractéristiques [Termes IGN] jeu de données [Termes IGN] précision de la classification [Termes IGN] processeur graphique Résumé : (auteur) In the deep-learning community, new algorithms are published at a very fast pace. Therefore, solving an image classification problem for new datasets becomes a challenging task, as it requires to re-evaluate published algorithms and their different configurations in order to find a close to optimal classifier. To facilitate this process, before biasing our decision toward a class of neural networks or running an expensive search over the network space, we propose to estimate the classification difficulty of the dataset. Our method computes a single number that characterizes the dataset difficulty 97× faster than training state-of-the-art networks. The proposed method can be used in combination with network topology and hyper-parameter search optimizers to efficiently drive the search toward promising neural network configurations. Numéro de notice : A2021-533 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-020-01922-5 Date de publication en ligne : 28/07/2020 En ligne : https://doi.org/10.1007/s00371-020-01922-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97993 [article]

Group diagrams for representing trajectories / Maike Buchin in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 12 (December 2020) . - pp 2401 - 2433 Titre : Group diagrams for representing trajectories Type de document : Article/Communication Auteurs : Maike Buchin, Auteur ; Bernhard Kilgus, Auteur ; Andrea Kölzsch, Auteur Année de publication : 2020 Article en page(s) : pp 2401 - 2433 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] analyse spatio-temporelle [Termes IGN] approximation [Termes IGN] base de données d'objets mobiles [Termes IGN] diagramme [Termes IGN] distance de Fréchet [Termes IGN] données GPS [Termes IGN] géomètrie algorithmique [Termes IGN] itinéraire [Termes IGN] migration animale [Termes IGN] objet mobile Résumé : (auteur) Given the trajectories of one or several moving groups, we propose a new framework, the group diagram (GD) for representing these. Specifically, we seek a minimal GD as a concise representation of the groups maintaining the spatio-temporal structure of the groups’ movement. A GD is specified by three input values, namely a distance threshold, a similarity measure and a minimality criterion. For several variants of the GD, we give a comprehensive analysis of their computational complexity and present efficient approximation algorithms for their computation. Furthermore, we experimentally evaluate our algorithms on GPS data of migrating geese. Applying the proposed methods on these data sets reveals how the GD concisely represents the movement of the groups. This representation can be used for further analysis and for the formulation of new hypotheses for further ecological research, such as differences in movement patterns of groups on different surfaces or the shift of migration routes over several years. We use different similarity measures to summarize the migration routes of (i) a goose family for one migration period and to summarize (ii) the migration routes of one individual for several migration periods or (iii) the migration routes of several independent individuals for one migration period. Numéro de notice : A2020-690 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1684498 Date de publication en ligne : 25/11/2019 En ligne : https://doi.org/10.1080/13658816.2019.1684498 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96227 [article]

Context-aware similarity of GPS trajectories / Radu Mariescu-Istodor in Journal of location-based services, vol 14 n° 4 ([01/11/2020])  

Public [article]  inJournal of location-based services > vol 14 n° 4 [01/11/2020] . - pp 231 - 251 Titre : Context-aware similarity of GPS trajectories Type de document : Article/Communication Auteurs : Radu Mariescu-Istodor, Auteur ; Pasi Fränti, Auteur Année de publication : 2020 Article en page(s) : pp 231 - 251 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] distance de Fréchet [Termes IGN] prise en compte du contexte [Termes IGN] similitude [Termes IGN] trace GPS [Termes IGN] traitement de données localisées [Termes IGN] trajet (mobilité) Résumé : (auteur) Measuring similarity of GPS trajectories has attracted a lot of attention in recent years. As a result, multiple trajectory similarity measures have been developed and are used in a wide set of applications which aim to extract meaningful information from large collections. In this paper, we focus on some of the most popular measures and study how they all can be adapted to use contextual information. We experiment using the buildings in an urban setting as the context and demonstrate how it impacts the similarity values. Experiments show that routes rank differently in terms of similarity in the presence of context which can have serious implications in applications such as trajectory search and clustering similar trajectories. Numéro de notice : A2020-848 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17489725.2020.1842923 Date de publication en ligne : 04/11/2020 En ligne : https://doi.org/10.1080/17489725.2020.1842923 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98654 [article]

Visual analytics of delays and interaction in movement data / Maximilian Konzack in International journal of geographical information science IJGIS, vol 31 n° 1-2 (January - February 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 1-2 (January - February 2017) . - pp 320 - 345 Titre : Visual analytics of delays and interaction in movement data Type de document : Article/Communication Auteurs : Maximilian Konzack, Auteur ; Thomas McKetterick, Auteur ; Tim Ophelder, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 320 - 345 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle [Termes IGN] décomposition spatiale [Termes IGN] distance de Fréchet [Termes IGN] données spatiotemporelles [Termes IGN] navigation [Termes IGN] objet mobile [Vedettes matières IGN] Géovisualisation Résumé : (auteur) The analysis of interaction between movement trajectories is of interest for various domains when movement of multiple objects is concerned. Interaction often includes a delayed response, making it difficult to detect interaction with current methods that compare movement at specific time intervals. We propose analyses and visualizations, on a local and global scale, of delayed movement responses, where an action is followed by a reaction over time, on trajectories recorded simultaneously. We developed a novel approach to compute the global delay in subquadratic time using a fast Fourier transform (FFT). Central to our local analysis of delays is the computation of a matching between the trajectories in a so-called delay space. It encodes the similarities between all pairs of points of the trajectories. In the visualization, the edges of the matching are bundled into patches, such that shape and color of a patch help to encode changes in an interaction pattern. To evaluate our approach experimentally, we have implemented it as a prototype visual analytics tool and have applied the tool on three bidimensional data sets. For this we used various measures to compute the delay space, including the directional distance, a new similarity measure, which captures more complex interactions by combining directional and spatial characteristics. We compare matchings of various methods computing similarity between trajectories. We also compare various procedures to compute the matching in the delay space, specifically the Fréchet distance, dynamic time warping (DTW), and edit distance (ED). Finally, we demonstrate how to validate the consistency of pairwise matchings by computing matchings between more than two trajectories. Numéro de notice : A2017-034 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1199806 En ligne : http://dx.doi.org/10.1080/13658816.2016.1199806 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84027 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2017011	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-2017012	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Trajectory Box Plot: a new pattern to summarize movements / Laurent Etienne in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)  

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Matching networks with different levels of detail / Sébastien Mustière in Geoinformatica, vol 12 n° 4 (December 2008)  

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Comparaison des éléments linéaires de deux bases de données géographiques, version 1.2 / Patrick Marmonier (2002)

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A new merging process for data integration based on the Discrete Fréchet Distance / Thomas Devogele (2002)  

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Qualité géométrique des entités géographiques surfaciques / Atef Bel Hadj Ali (2001)  

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Using distances for linear accuracy measurements / Thomas Devogele (2000)

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