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Méthode de comparaison de nuages de points acquis par scanner laser mobile pour caractériser les éboulements des falaises côtières / Baptiste Feldmann in XYZ, n° 156 (septembre - novembre 2018)
[article]
Titre : Méthode de comparaison de nuages de points acquis par scanner laser mobile pour caractériser les éboulements des falaises côtières Type de document : Article/Communication Auteurs : Baptiste Feldmann, Auteur ; Clara Lévy, Auteur ; Thomas Dewez, Auteur ; Nathalie Marçot, Auteur Année de publication : 2018 Article en page(s) : pp 57 - 62 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] analyse diachronique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] éboulement
[Termes IGN] falaise
[Termes IGN] littoral méditerranéen
[Termes IGN] risque naturel
[Termes IGN] semis de pointsRésumé : (Auteur) La comparaison diachronique de nuages de points LiDAR a permis d’estimer l’aléa éboulement pour de nombreuses falaises alpines. L’acquisition de données adéquates pour des falaises côtières est plus ardue car la position idéale pour des mesures TLS (Terrestrial Laser Scanning) ou le pilotage d’un drone est située dans la zone submersible. L’acquisition de données LiDAR depuis un bateau avait donc été testée lors du projet VALSE (2011 - 2015), montrant les difficultés de traitement de ces données (Giuliano, 2015). Cette étude vient compléter les travaux existants en proposant une méthode de comparaison de levés LiDAR avec un point de vue vecteur (c’est-à-dire, sans rastérisation des données), élaborée en utilisant l’algorithme M3C2 (Lague et al, 2013). Les distances entre nuages, qualifiées statistiquement, servent à cartographier les zones d’érosion, ainsi qu’à déduire la forme des blocs éboulés par regroupement des points appartenant à ces zones. Numéro de notice : A2018-398 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90840
in XYZ > n° 156 (septembre - novembre 2018) . - pp 57 - 62[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 112-2018031 RAB Revue Centre de documentation En réserve L003 Disponible Algorithm of land cover spatial data processing for the local flood risk mapping / Monika Siejka in Survey review, vol 50 n° 362 (August 2018)
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Titre : Algorithm of land cover spatial data processing for the local flood risk mapping Type de document : Article/Communication Auteurs : Monika Siejka, Auteur ; Monika Mika, Auteur ; Tomasz Salata, Auteur ; Przemysław Leń, Auteur Année de publication : 2018 Article en page(s) : pp 397 - 403 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] cartographie des risques
[Termes IGN] cours d'eau
[Termes IGN] inondation
[Termes IGN] occupation du sol
[Termes IGN] Pologne
[Termes IGN] risque naturel
[Termes IGN] traitement de données localiséesRésumé : (Auteur) Floods are a natural phenomenon that has always been and will pose a threat to people’s life and health, their property and the environment. Total elimination of the flood is impossible, but the current state of knowledge enables the use of the available tools in order to reduce the scale of these threats. The aim of the study is to develop a methodology of identification of the areas of hindered flow of water, located in the immediate vicinity of rivers. The proposed methodology is based on a study of the land cover. The developed algorithm of land cover spatial data processing for the local flood risk mapping implements GIS tools. Verification of the developed method was carried out on the example of selected rivers in Poland, only one of which is covered by the plans of flood risk management and causes periodic floodings. Numéro de notice : A2018-446 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2017.1287620 Date de publication en ligne : 22/02/2017 En ligne : https://doi.org/10.1080/00396265.2017.1287620 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91031
in Survey review > vol 50 n° 362 (August 2018) . - pp 397 - 403[article]Estimating storm damage with the help of low-altitude photographs and different sampling designs and estimators / Pekka Hyvönen in Silva fennica, vol 52 n° 3 ([01/08/2018])
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Titre : Estimating storm damage with the help of low-altitude photographs and different sampling designs and estimators Type de document : Article/Communication Auteurs : Pekka Hyvönen, Auteur ; Jaakko Heinonen, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] dommage matériel
[Termes IGN] estimateur
[Termes IGN] Finlande
[Termes IGN] forêt
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle de simulation
[Termes IGN] plan de volMots-clés libres : Théorème central limite Résumé : (Auteur) Climate change has been estimated to increase the risk of storm damage in forests in Finland. There is a growing need for methods to obtain information on the extent and severity of storm damage after a storm occurrence. The first objective of this study was to test whether digital photographs taken from aircrafts flying at low-altitude can be utilized in locating storm-damaged areas and estimating the need for harvesting of wind-thrown trees. The second objective was to test the performance of selected estimators. Depending on distances between flight lines, plots on lines and the used estimator, the relative standard errors of storm area estimates varied between 7.7 and 48.7%. For the area for harvesting and volume of wind-thrown trees, the relative standard errors of estimates varied between 16.8 and 167.3%. Using forest area information from Multisource National Forest Inventory data improved the accuracy of the estimates. However, performance of a simple random sampling estimator and ratio estimator were quite similar. Lindeberg’s method for variance estimation based on adjacent lines was sensitive to line directions in relation to possible trends in storm-damaged area locations. Our results showed that the tested method could be used in estimating storm-damaged area provided that the network of flight lines and photographs on lines are sufficiently dense. The developed model for simulations can be utilized also with forthcoming storms as model’s parameters can be freely adjusted to meet, e.g., the intensity and extent of the storm. Numéro de notice : A2018-508 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14214/sf.7710 Date de publication en ligne : 05/06/2018 En ligne : https://doi.org/10.14214/sf.7710 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91189
in Silva fennica > vol 52 n° 3 [01/08/2018][article]Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment / Bernd Resch in Cartography and Geographic Information Science, Vol 45 n° 4 (July 2018)
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Titre : Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment Type de document : Article/Communication Auteurs : Bernd Resch, Auteur ; Florian Usländer, Auteur ; Clemens Havas, Auteur Année de publication : 2018 Article en page(s) : pp 362 - 376 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] apprentissage automatique
[Termes IGN] carte thématique
[Termes IGN] catastrophe naturelle
[Termes IGN] dommage matériel
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] empreinte
[Termes IGN] gestion de criseRésumé : (Auteur) Current disaster management procedures to cope with human and economic losses and to manage a disaster’s aftermath suffer from a number of shortcomings like high temporal lags or limited temporal and spatial resolution. This paper presents an approach to analyze social media posts to assess the footprint of and the damage caused by natural disasters through combining machine-learning techniques (Latent Dirichlet Allocation) for semantic information extraction with spatial and temporal analysis (local spatial autocorrelation) for hot spot detection. Our results demonstrate that earthquake footprints can be reliably and accurately identified in our use case. More, a number of relevant semantic topics can be automatically identified without a priori knowledge, revealing clearly differing temporal and spatial signatures. Furthermore, we are able to generate a damage map that indicates where significant losses have occurred. The validation of our results using statistical measures, complemented by the official earthquake footprint by US Geological Survey and the results of the HAZUS loss model, shows that our approach produces valid and reliable outputs. Thus, our approach may improve current disaster management procedures through generating a new and unseen information layer in near real time. Numéro de notice : A2018-136 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2017.1356242 Date de publication en ligne : 03/08/2017 En ligne : https://doi.org/10.1080/15230406.2017.1356242 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89678
in Cartography and Geographic Information Science > Vol 45 n° 4 (July 2018) . - pp 362 - 376[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2018041 RAB Revue Centre de documentation En réserve L003 Disponible Modeling of inland flood vulnerability zones through remote sensing and GIS techniques in the highland region of Papua New Guinea / Porejane Harley in Applied geomatics, vol 10 n° 2 (June 2018)
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Titre : Modeling of inland flood vulnerability zones through remote sensing and GIS techniques in the highland region of Papua New Guinea Type de document : Article/Communication Auteurs : Porejane Harley, Auteur ; Sailesh Samanta, Auteur Année de publication : 2018 Article en page(s) : pp 159 - 171 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] altitude
[Termes IGN] analyse multicritère
[Termes IGN] cartographie des risques
[Termes IGN] catastrophe naturelle
[Termes IGN] image Landsat-OLI
[Termes IGN] inondation
[Termes IGN] occupation du sol
[Termes IGN] Papouasie-Nouvelle-Guinée
[Termes IGN] pente
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] relief
[Termes IGN] risque naturel
[Termes IGN] texture du sol
[Termes IGN] vulnérabilitéRésumé : (Auteur) Papua New Guinea (PNG) is saddled with frequent natural disasters like earthquakes, volcanic eruptions, landslides, droughts, floods, etc. Flooding, as a hydrological disaster to humankind’s niche, brings about a powerful and often sudden, pernicious change in the surface distribution of water on land, while the benevolence of flooding manifests in restoring the health of the thalweg from excessive siltation by redistributing the fertile sediments on the riverine floodplains. In respect to social, economic, and environmental perspectives, flooding is one of the most devastating disasters in PNG. This research is conducted to investigate the usefulness of remote sensing (RS), the geographic information system (GIS), and multi-criteria analysis (MCA) for flood susceptibility mapping. MCA methods such as weighted linear combination (WLC) and analytical hierarchy processes (AHP) were used to assess flood vulnerability in the Wahgi catchment area through RS and GIS technology. In the study, attention was focused on different parameters that cause flooding. These parameters include elevation, slope, distance from drainage, soil texture, soil drainage, rainfall, landform, and land use and land cover. The classes within parameters were ranked and suitably weighted depending on their influence to flooding with reference to the PNG Resource Information System (PNGRIS) metadata. The result of the analysis is a flood-susceptibility map showing the most vulnerable areas. This type of map is very useful for better management, planning, and mitigation of future flooding in the Wahgi catchment area. The validation of the flood-susceptibility map was carried out using past flood records in the study area. Numéro de notice : A2018-156 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-018-0220-8 Date de publication en ligne : 04/05/2018 En ligne : https://doi.org/10.1007/s12518-018-0220-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89775
in Applied geomatics > vol 10 n° 2 (June 2018) . - pp 159 - 171[article]TAGGS : grouping tweets to improve global geoparsing for disaster response / Jens A. de Bruijn in Journal of Geovisualization and Spatial Analysis, vol 2 n° 1 (June 2018)PermalinkMigrating pattern of deformation prior to the Tohoku-Oki earthquake revealed by GRACE data / Isabelle Panet in Nature geoscience, vol 11 n° 5 (May 2018)PermalinkError-regulated multi-pass DInSAR analysis for landslide risk assessment / Jung Rack Kim in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 4 (April 2018)PermalinkA spatio-temporal scenario model for emergency decision / Cheng Liu in Geoinformatica, vol 22 n° 2 (April 2018)PermalinkAn open source framework for publishing flood inundation extent libraries in a Web GIS environment using open source technologies / Vinod Kumar Sharma in International journal of cartography, vol 4 n° 1 (March 2018)PermalinkAnalyse du risque végétation dans les emprises ferroviaires à partir de données LiDAR acquises par drones / Luc Perrin in XYZ, n° 154 (mars - mai 2018)PermalinkContextual classification using photometry and elevation data for damage detection after an earthquake event / Ewelina Rupnik in European journal of remote sensing, vol 51 n° 1 (2018)PermalinkEvaluation of web maps for the communication of flood risks to the public in Europe / Maaike Van Kerkvoorde in International journal of cartography, vol 4 n° 1 (March 2018)PermalinkExtraction of pluvial flood relevant volunteered geographic information (VGI) by deep learning from user generated texts and photos / Yu Feng in ISPRS International journal of geo-information, vol 7 n° 2 (February 2018)PermalinkAssessing forest windthrow damage using single-date, post-event airborne laser scanning data / Gherardo Chirici in Forestry, an international journal of forest research, vol 91 n° 1 (January 2018)Permalink