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A filtering-based approach for improving crowdsourced GNSS traces in a data update context / Stefan Ivanovic in ISPRS International journal of geo-information, vol 8 n° 9 (September 2019)
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Titre : A filtering-based approach for improving crowdsourced GNSS traces in a data update context Type de document : Article/Communication Auteurs : Stefan Ivanovic (1988 - 2020) , Auteur ; Ana-Maria Olteanu-Raimond
, Auteur ; Sébastien Mustière
, Auteur ; Thomas Devogele
, Auteur
Année de publication : 2019 Projets : 1-Pas de projet / Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] apprentissage automatique
[Termes IGN] approche participative
[Termes IGN] base de données localisées
[Termes IGN] données localisées des bénévoles
[Termes IGN] filtrage du bruit
[Termes IGN] mise à jour de base de données
[Termes IGN] montagne
[Termes IGN] qualité des données
[Termes IGN] sport
[Termes IGN] système d'information géographique
[Termes IGN] trace GPS
[Termes IGN] valeur aberranteRésumé : (auteur) Traces collected by citizens using GNSS (Global Navigation Satellite System) devices during sports activities such as running, hiking or biking are now widely available through different sport-oriented collaborative websites. The traces are collected by citizens for their own purposes and frequently shared with the sports community on the internet. Our research assumption is that crowdsourced GNSS traces may be a valuable source of information to detect updates in authoritative datasets. Despite their availability, the traces present some issues such as poor metadata, attribute incompleteness and heterogeneous positional accuracy. Moreover, certain parts of the traces (GNSS points composing the traces) are results of the displacements made out of the existing paths. In our context (i.e., update authoritative data) these off path GNSS points are considered as noise and should be filtered. Two types of noise are examined in this research: Points representing secondary activities (e.g., having a lunch break) and points representing errors during the acquisition. The first ones we named secondary human behaviour (SHB), whereas we named the second ones outliers. The goal of this paper is to improve the smoothness of traces by detecting and filtering both SHB and outliers. Two methods are proposed. The first one allows for the detection secondary human behaviour by analysing only traces geometry. The second one is a rule-based machine learning method that detects outliers by taking into account the intrinsic characteristics of points composing the traces, as well as the environmental conditions during traces acquisition. The proposed approaches are tested on crowdsourced GNSS traces collected in mountain areas during sports activities. Numéro de notice : A2019-626 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi8090380 Date de publication en ligne : 30/08/2019 En ligne : https://doi.org/10.3390/ijgi8090380 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95359
in ISPRS International journal of geo-information > vol 8 n° 9 (September 2019) . - 17 p.[article]Free and open-source GIS technologies for the management of woody biomass / Michele Mangiameli in Applied geomatics, vol 11 n° 3 (September 2019)
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Titre : Free and open-source GIS technologies for the management of woody biomass Type de document : Article/Communication Auteurs : Michele Mangiameli, Auteur ; Giuseppe Mussumeci, Auteur ; Paolo Roccaro, Auteur ; Federico G. A. Vagliasindi, Auteur Année de publication : 2019 Article en page(s) : pp 309 - 315 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] base de données localisées
[Termes IGN] bioénergie
[Termes IGN] biomasse forestière
[Termes IGN] carte forestière
[Termes IGN] dioxyde de carbone
[Termes IGN] données cadastrales
[Termes IGN] gestion forestière
[Termes IGN] logiciel libre
[Termes IGN] logiciel SIG
[Termes IGN] problème du voyageur de commerce
[Termes IGN] ressources forestières
[Termes IGN] système de gestion de bases de données relationnellesRésumé : (Auteur) Biomasses are materials of organic origin that can be used for the production of energy. Among the renewable energy sources, a prominent role is played by woody biomass, which can be retrieved from existing forests or plantations governed in short or middle rotation coppice, the so-called Short and Medium Rotation Forestry. The main environmental benefit resulting from the use of wood biomass consists in the fact that the amount of carbon dioxide released during their combustion process is the same as that absorbed during the development phase. Here, we propose a procedure to manage the traceability of short biomass chains and to schedule the activities for mobile forest construction sites using free and open-source GIS technologies. Firstly, we created a spatial DB to manage the areas where the cutting and logging activities are performed. Then, we overlapped the boundaries of areas with the cadastral sheets to ensure the biomass comes from short chain, i.e., within the range of 70 km from the position of the central. To plan the number of working days required and make an estimation of the production, the total area of the lots, the land clearing, and the net area were calculated. Finally, depending on the characteristics of wooded areas, the type of system to be used for the business of cutting and logging was evaluated. This work demonstrates how GIS allows a fast traceability of short biomass chains and an estimation of the production by improving the efficiency and effectiveness of biomass resource assessment. Numéro de notice : A2019-462 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-019-00265-8 Date de publication en ligne : 27/04/2019 En ligne : https://doi.org/10.1007/s12518-019-00265-8 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93602
in Applied geomatics > vol 11 n° 3 (September 2019) . - pp 309 - 315[article]Place and sentiment-based life story analysis: From the Spanish republican army to the French resistance / Catherine Dominguès in Revue française des sciences de l'information et de la communication, vol 17 (2019)
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Titre : Place and sentiment-based life story analysis: From the Spanish republican army to the French resistance Type de document : Article/Communication Auteurs : Catherine Dominguès , Auteur ; Laurence Jolivet
, Auteur ; Carmen Brando
, Auteur ; Marion Cargill, Auteur
Année de publication : 2019 Projets : MATRICIEL / Article en page(s) : n° 7228 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Toponymie
[Termes IGN] appariement de données localisées
[Termes IGN] apprentissage dirigé
[Termes IGN] carte thématique
[Termes IGN] Espagne
[Termes IGN] expression orale
[Termes IGN] France (administrative)
[Termes IGN] guerre
[Termes IGN] histoire
[Termes IGN] linguistique
[Termes IGN] ontologie
[Termes IGN] segmentation sémantique
[Termes IGN] terminologieRésumé : (auteur) In 2008, the Network of Actors for the History and Memory of Immigration (RAHMI) launched an experimental gathering program to collect the forgotten memory of immigrant populations involved in the local community. Various groups of people were targeted by this collection, which made it possible to record life stories, including those of Spanish Republicans who went into exile in France between 1936 and 1939, and participated in the French Resistance. The MATRICIEL project (PEPS CNRS UPE 2016) focused on the migration of these Spanish Republicans in terms of the places mentioned in their stories, and the sentiments associated with these places. The project aimed to mainstream the migrants’ voices in the analysis; the objects of study chosen: the places, designated by a proper name: Barcelona, or a common name: internment camp, and the associated sentiments distinguished by their polarity: positive or negative, contribute to enhancing oral archives for the construction of an immigration memory. In this article, we present the approach implemented for a multidisciplinary analysis of the life story corpus, which combines methods and tools for natural language processing and mapping. The identification of common noun places mentioned in the stories was conducted through a supervised learning model. The identification and subsequent mapping of proper name places highlight the spatial distribution of the witnesses’ life courses, determined by the historical context and personal choices. The semi-automatic sentiment annotation adds polarity to the stories. In perspective, the analysis of common noun place types will make it possible to evaluate the granularity used by witnesses to describe their lived spaces; their location will help to specify the spatiality of the stories. Numéro de notice : A2019-590 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : TOPONYMIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.4000/rfsic.7228 Date de publication en ligne : 01/09/2019 En ligne : https://doi.org/10.4000/rfsic.7228 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94547
in Revue française des sciences de l'information et de la communication > vol 17 (2019) . - n° 7228[article]PPD: Pyramid Patch Descriptor via convolutional neural network / Jie Wan in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 9 (September 2019)
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Titre : PPD: Pyramid Patch Descriptor via convolutional neural network Type de document : Article/Communication Auteurs : Jie Wan, Auteur ; Alper Yilmaz, Auteur ; Lei Yan, Auteur Année de publication : 2019 Article en page(s) : pp 673 - 686 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] appariement d'images
[Termes IGN] benchmark spatial
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données localisées de référence
[Termes IGN] échantillonnage d'image
[Termes IGN] état de l'art
[Termes IGN] extraction de données
[Termes IGN] image aérienne
[Termes IGN] image satellite
[Termes IGN] jeu de données localiséesRésumé : (Auteur) Local features play an important role in remote sensing image matching, and handcrafted features have been excessively used in this area for a long time. This article proposes a pyramid convolutional neural triplet network that extracts a 128-dimensional deep descriptor that significantly improves the matching performance. The proposed approach first extracts deep descriptors of the anchor patches and corresponding positive patches in a batch using the proposed pyramid convolutional neural network. Following this step, the approaches chooses the closest negative patch for each anchor patch and corresponding positive patch pair to form the triplet sample based on the descriptor distances among all other image patches in the batch. These triplets are used to optimize the parameters of the network using a new loss function. We evaluated the proposed deep descriptors on two benchmark data sets (Brown and HPatches) as well as real image data sets. The results reveal that the proposed descriptor achieves the state-of-the-art performance on the Brown data set and a comparatively very high performance on the HPatches data set. The proposed approach finds more correct matches than the classical handcrafted feature descriptors on aerial image pairs and is observed to be robust to variations in the viewpoint and illumination. Numéro de notice : A2019-416 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.9.673 Date de publication en ligne : 01/09/2019 En ligne : https://doi.org/10.14358/PERS.85.9.673 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93543
in Photogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 9 (September 2019) . - pp 673 - 686[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 105-2019091 SL Revue Centre de documentation Revues en salle Disponible Review of mobile laser scanning target‐free registration methods for urban areas using improved error metrics / Hoang Long Nguyen in Photogrammetric record, vol 34 n° 167 (September 2019)
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Titre : Review of mobile laser scanning target‐free registration methods for urban areas using improved error metrics Type de document : Article/Communication Auteurs : Hoang Long Nguyen, Auteur ; David Belton, Auteur ; Petra Helmholz, Auteur Année de publication : 2019 Article en page(s) : pp 282 – 303 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme ICP
[Termes IGN] appariement de points
[Termes IGN] erreur de mesure
[Termes IGN] qualité du processus
[Termes IGN] semis de points
[Termes IGN] traitement de semis de points
[Termes IGN] zone urbaineMots-clés libres : The aim of the registration process is to obtain the transformation parameters to transform captured point clouds to their correct positions. Résumé : (auteur) Registration is one of the most important tasks in mobile laser scanning (MLS) point cloud processing. This paper firstly reviews existing target‐free matching techniques as well as methods to evaluate the quality of the registration. Next, a new error metric is introduced that takes into account the residuals of check planes as well as their orientation. Experiments using real datasets in combination with reference data were performed to evaluate the suitability of these metrics. The proposed error metric proved to be more suitable for evaluating the quality of point cloud registration than state‐of‐the‐art equivalents. The results also indicate that least squares plane fitting is the best technique for MLS point cloud registration. Numéro de notice : A2019-498 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12293 Date de publication en ligne : 10/10/2019 En ligne : https://doi.org/10.1111/phor.12293 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93760
in Photogrammetric record > vol 34 n° 167 (September 2019) . - pp 282 – 303[article]Validating the use of object-based image analysis to map commonly recognized landform features in the United States / Samantha T. Arundel in Cartography and Geographic Information Science, Vol 46 n° 5 (September 2019)
PermalinkQuantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale / Elena Barbierato in European journal of remote sensing, vol 52 n° 4 (2019)
PermalinkAutomatic extraction of accurate 3D tie points for trajectory adjustment of mobile laser scanners using aerial imagery / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
PermalinkImproving public data for building segmentation from Convolutional Neural Networks (CNNs) for fused airborne lidar and image data using active contours / David Griffiths in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
PermalinkLocal climate zone-based urban land cover classification from multi-seasonal Sentinel-2 images with a recurrent residual network / Chunping Qiu in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
Permalink“Mapping-with”: The Politics of (Counter-)classification in OpenStreetMap / Clancy Wilmott in Cartographic perspectives, n° 92 (2019)
PermalinkPyramid scene parsing network in 3D: Improving semantic segmentation of point clouds with multi-scale contextual information / Hao Fang in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
PermalinkAnalysis of collaboration networks in OpenStreetMap through weighted social multigraph mining / Quy Thy Truong in International journal of geographical information science IJGIS, vol 33 n° 7 - 8 (July - August 2019)
PermalinkIs deep learning the new agent for map generalization? / Guillaume Touya in International journal of cartography, vol 5 n° 2-3 (July - November 2019)
PermalinkMultiscale cartographic visualization of harmonized datasets / Peter Kunz in International journal of cartography, vol 5 n° 2-3 (July - November 2019)
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