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Potential of crowdsourced traces for detecting updates in authoritative geographic data / Stefan Ivanovic (2020)
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Titre : Potential of crowdsourced traces for detecting updates in authoritative geographic data Type de document : Article/Communication Auteurs : Stefan Ivanovic , Auteur ; Ana-Maria Olteanu-Raimond
, Auteur ; Sébastien Mustière
, Auteur ; Thomas Devogele, Auteur
Congrès : AGILE 2019, 22nd conference on Geo-information science (17 - 20 juin 2019; Limassol, Chypre) , Commanditaire
Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2020 Collection : Lecture notes in Geoinformation and Cartography, ISSN 1863-2246 Importance : pp 205 - 221 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes descripteurs IGN] aide à la décision
[Termes descripteurs IGN] appariement de données localisées
[Termes descripteurs IGN] BD Topo
[Termes descripteurs IGN] chemin rural
[Termes descripteurs IGN] contenu généré par les utilisateurs
[Termes descripteurs IGN] données localisées de référence
[Termes descripteurs IGN] mise à jour de base de données
[Termes descripteurs IGN] montagne
[Termes descripteurs IGN] route
[Termes descripteurs IGN] trace GPSRésumé : (auteur) Crowdsourced traces collected by GPS devices during sports activities are now widely available on different websites. The goal of this paper is to study the potential of crowdsourced traces coming from GPS devices to highlight updates in authoritative geographic data. To reach this goal, an approach based on two steps is proposed. First, a data matching method is applied to match authoritative data and crowdsourced traces. Second, for the non-matched crowdsourced segments composing a trace, different criteria are defined to decide if whether or not, non-matched segments should be considered as an alert for update in authoritative data. The proposed approach is tested on crowdsourced traces and on BDTOPO® authoritative road and path network in mountain area. The results are promising: 727, 1 km of missing paths were found in the test area, which corresponds to 7.7% of the total length of used traces. The discovered missing paths also represent a contribution of 2.4% of the total length of BDTopo® road and path network in the test area. Numéro de notice : C2019-008 Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-030-14745-7_12 date de publication en ligne : 16/04/2019 En ligne : http://dx.doi.org/10.1007/978-3-030-14745-7_12 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92911 A thematic mapping method to assess and analyze potential urban hazards and risks caused by flooding / Mohammad Khalid Hossain in Computers, Environment and Urban Systems, vol 79 (January 2020)
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[article]
Titre : A thematic mapping method to assess and analyze potential urban hazards and risks caused by flooding Type de document : Article/Communication Auteurs : Mohammad Khalid Hossain, Auteur ; Qingmin Meng, Auteur Année de publication : 2020 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes descripteurs IGN] Alabama (Etats-Unis)
[Termes descripteurs IGN] aléa
[Termes descripteurs IGN] approche hiérarchique
[Termes descripteurs IGN] cartographie des risques
[Termes descripteurs IGN] catastrophe naturelle
[Termes descripteurs IGN] données socio-économiques
[Termes descripteurs IGN] ethnographie
[Termes descripteurs IGN] inondation
[Termes descripteurs IGN] risque naturel
[Termes descripteurs IGN] système d'information géographique
[Termes descripteurs IGN] vulnérabilité
[Termes descripteurs IGN] zone inondable
[Termes descripteurs IGN] zone urbaineRésumé : (Auteur) About 30% of the total global economic loss inflicted by natural hazards is caused by flooding. Among them, the most serious situation is urban flooding. Urban impervious surface enhances storm runoff and overwhelms the drainage capacity of the storm sewer system, while the urban socioeconomic characteristics most often exacerbate them even more vulnerable to urban flooding impacts. Currently, there is still a significant knowledge gap of comparable assessment and understanding of minority's and non-minority's vulnerability. Therefore, this study designs a quantitative thematic mapping method–location quotient (LQ), using Birmingham, Alabama, USA as the study area. Urban residents' vulnerability to flooding is then analyzed demographically using LQ with census data. Comparing with the widely used social vulnerability index (SVI), LQ is more robust, which not only provides more detailed measurements of both the minority's and the White's vulnerability, but also shows a direct comparison for all populations with finer information about their potential spatial risk assessment. Although SVI showed the Shades Creek is the most vulnerable area with a SVI value above 0.75, only 228 Hispanic people and 2290 African-American live there that is not a significant aggregation of minorities in Birmingham; however, a total White population 12,872 is identified by LQ with a significant aggregation in the Shades Creek. Overall, LQ suggests that the White populations are highly and significantly concentrated in the flood areas, while SVI never considered the White as vulnerable. LQ further indicates that the concentration of minorities (i.e., 88,895) and vulnerable houses (i.e., 26,235) are much higher compared to the numbers of the minorities and houses indicated by SVI, which are only 11,772 and 8323, respectively. The LQ based thematic mapping, as a promising method for vulnerability assessment of urban hazards and risks, can make a significant contribution to hazard management efforts to reduce urban vulnerability and hence enhance urban resilience to hazards in the future. Numéro de notice : A2020-002 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2019.101417 date de publication en ligne : 14/09/2019 En ligne : https://doi.org/10.1016/j.compenvurbsys.2019.101417 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93621
in Computers, Environment and Urban Systems > vol 79 (January 2020)[article]Deep learning for multi-modal classification of cloud, shadow and land cover scenes in PlanetScope and Sentinel-2 imagery / Yuri Shendryk in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)
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Titre : Deep learning for multi-modal classification of cloud, shadow and land cover scenes in PlanetScope and Sentinel-2 imagery Type de document : Article/Communication Auteurs : Yuri Shendryk, Auteur ; Yannik Rist, Auteur ; Catherine Ticehurst, Auteur ; Peter Thorburn, Auteur Année de publication : 2019 Article en page(s) : pp 124 - 136 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes descripteurs IGN] Amazonie
[Termes descripteurs IGN] apprentissage profond
[Termes descripteurs IGN] Australie
[Termes descripteurs IGN] classification par réseau neuronal convolutif
[Termes descripteurs IGN] détection d'ombre
[Termes descripteurs IGN] état de l'art
[Termes descripteurs IGN] image à haute résolution
[Termes descripteurs IGN] image PlanetScope
[Termes descripteurs IGN] image Sentinel-MSI
[Termes descripteurs IGN] Normalized Difference Vegetation Index
[Termes descripteurs IGN] nuage
[Termes descripteurs IGN] occupation du sol
[Termes descripteurs IGN] zone tropicale humideRésumé : (Auteur) With the increasing availability of high-resolution satellite imagery it is important to improve the efficiency and accuracy of satellite image indexing, retrieval and classification. Furthermore, there is a need for utilizing all available satellite imagery in identifying general land cover types and monitoring their changes through time irrespective of their spatial, spectral, temporal and radiometric resolutions. Therefore, in this study, we developed deep learning models able to efficiently and accurately classify cloud, shadow and land cover scenes in different high-resolution ( Numéro de notice : A2019-494 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.08.018 date de publication en ligne : 17/09/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.08.018 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93727
in ISPRS Journal of photogrammetry and remote sensing > vol 157 (November 2019) . - pp 124 - 136[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019111 SL Revue Centre de documentation Revues en salle Disponible 081-2019113 DEP-RECP Revue MATIS Dépôt en unité Exclu du prêt 081-2019112 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Evolution of sand encroachment using supervised classification of Landsat data during the period 1987–2011 in a part of Laâyoune-Tarfaya basin of Morocco / Ali Aydda in Geocarto international, vol 34 n° 13 ([15/10/2019])
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Titre : Evolution of sand encroachment using supervised classification of Landsat data during the period 1987–2011 in a part of Laâyoune-Tarfaya basin of Morocco Type de document : Article/Communication Auteurs : Ali Aydda, Auteur ; Omar F. Althuwaynee, Auteur ; Ahmed Algouti, Auteur ; Abdellah Algouti, Auteur Année de publication : 2019 Article en page(s) : pp 1514 - 1529 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes descripteurs IGN] carte géomorphologique
[Termes descripteurs IGN] classification barycentrique
[Termes descripteurs IGN] classification dirigée
[Termes descripteurs IGN] classification par maximum de vraisemblance
[Termes descripteurs IGN] classification par séparateurs à vaste marge
[Termes descripteurs IGN] dune
[Termes descripteurs IGN] image Landsat
[Termes descripteurs IGN] image multitemporelle
[Termes descripteurs IGN] littoral
[Termes descripteurs IGN] Maroc
[Termes descripteurs IGN] sable
[Termes descripteurs IGN] vent de sableRésumé : (auteur) The study anticipated to understand sand encroachment evolution through analysis of sand contribution across space and time using remote sensing in Laâyoune-Tarfaya basin, Morocco, over the period from 1987 to 2011. The assessment based on supervised classifications of Landsat imagery orthorectified data, using Maximum Likelihood (ML), Minimum Distance (MD) and Support Vector Machine (SVM) classifiers. In order to ameliorate the information, principal components analysis (PCA) and co-occurrence measurement algorithm were used for choosing bands and data transformation. Images differencing was applied on image pairs derived from classification to analyze sand encroachment evolution. All classifiers present enhanced performances, and revealed that area covered by sand was increased by 7%, 4.66% and 4.59% for ML, MD and SVM, respectively. Consequently, images differencing results confirmed that sand material increasing arise not only from coastal area contribution but also mostly from erosion of complicated sand dunes exist in the middle part of the studied area. Evaluating of the presented phenomenon dimensions and its consequences are extremely important to increase the local authorities awareness and mainly for avoiding or minimizing the consequences of the future sand dunes threats. Numéro de notice : A2019-511 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1493154 date de publication en ligne : 07/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1493154 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93820
in Geocarto international > vol 34 n° 13 [15/10/2019] . - pp 1514 - 1529[article]Combining machine learning and compact polarimetry for estimating soil moisture from C-Band SAR data / Emanuele Santi in Remote sensing, Vol 11 n° 20 (2 October 2019)
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Titre : Combining machine learning and compact polarimetry for estimating soil moisture from C-Band SAR data Type de document : Article/Communication Auteurs : Emanuele Santi, Auteur ; Mohammed Dabboor, Auteur ; Simone Pettinato, Auteur ; Simonetta Paloscia, Auteur Année de publication : 2019 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes descripteurs IGN] apprentissage automatique
[Termes descripteurs IGN] bande C
[Termes descripteurs IGN] extraction de traits caractéristiques
[Termes descripteurs IGN] humidité du sol
[Termes descripteurs IGN] image radar moirée
[Termes descripteurs IGN] image Radarsat
[Termes descripteurs IGN] Manitoba (Canada)
[Termes descripteurs IGN] polarimétrie
[Termes descripteurs IGN] polarisation
[Termes descripteurs IGN] réseau neuronal artificiel
[Termes descripteurs IGN] série temporelle
[Termes descripteurs IGN] surface cultivéeRésumé : (auteur) This research aimed at exploiting the joint use of machine learning and polarimetry for improving the retrieval of surface soil moisture content (SMC) from synthetic aperture radar (SAR) acquisitions at C-band. The study was conducted on two agricultural areas in Canada, for which a series of RADARSAT-2 (RS2) images were available along with direct measurements of SMC from in situ stations. The analysis confirmed the sensitivity of RS2 backscattering (O°) to SMC. The comparison of SMC with the compact polarimetry (CP) parameters, computed from the RS2 acquisitions by the CP data simulator, pointed out that some CP parameters had a sensitivity to SMC equal or better than O°, with correlation coe?cients up to R ' 0.4. Based on these results, the potential of machine learning (ML) for SMC retrieval was exploited by implementing and testing on the available data an artificial neural network (ANN) algorithm. The algorithm was implemented using several combinations of O° and CP parameters. Validation results of the algorithm with in situ observations confirmed the promising capabilities of the ML techniques for SMC monitoring. Furthermore, results pointed out the potential of CP in improving the SMC retrieval accuracy, especially when used in combination with linearly polarized O°. Depending on the considered input combination, the ANN algorithm was able to estimate SMC with Root Mean Square Error (RMSE) between 3% and 7% of SMC and R between 0.7 and 0.9. Numéro de notice : A2019-555 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs11202451 date de publication en ligne : 22/10/2019 En ligne : https://doi.org/10.3390/rs11202451 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94210
in Remote sensing > Vol 11 n° 20 (2 October 2019) . - 18 p.[article]Sea ice extent detection in the Bohai Sea using Sentinel-3 OLCI data / Hua Su in Remote sensing, Vol 11 n° 20 (2 October 2019)
PermalinkAutomated fusion of forest airborne and terrestrial point clouds through canopy density analysis / Wenxia Dai in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)
PermalinkComparative analysis of the accuracy of surface soil moisture estimation from the C- and L-bands / Mohammad El Hajj in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)
PermalinkPermalinkGNSS metadata and data validation in the EUREF Permanent Network / Carine Bruyninx in GPS solutions, vol 23 n° 4 (October 2019)
PermalinkIntroducing a vertical land motion model for improving estimates of sea level rates derived from tide gauge records affected by earthquakes / Anna Klos in GPS solutions, vol 23 n° 4 (October 2019)
PermalinkKalman-filter-based undifferenced cycle slip estimation in real-time precise point positioning / Pan Li in GPS solutions, vol 23 n° 4 (October 2019)
PermalinkOptimal segmentation of high spatial resolution images for the classification of buildings using random forests / James Bialas in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)
PermalinkPerformance evaluation of real-time global ionospheric maps provided by different IGS analysis centers / Xiaodong Ren in GPS solutions, vol 23 n° 4 (October 2019)
PermalinkPerformance of Galileo-only dual-frequency absolute positioning using the fully serviceable Galileo constellation / Tomasz Hadas in GPS solutions, vol 23 n° 4 (October 2019)
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