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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)
[article]
Titre : TAGGS : grouping tweets to improve global geoparsing for disaster response Type de document : Article/Communication Auteurs : Jens A. de Bruijn, Auteur ; Hans de Moel, Auteur ; Brenden Jongman, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Linguistique
[Termes IGN] catastrophe naturelle
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] Geoparsing
[Termes IGN] inondation
[Termes IGN] prise en compte du contexte
[Termes IGN] risque naturel
[Termes IGN] TwitterRésumé : (Auteur) Timely and accurate information about ongoing events are crucial for relief organizations seeking to effectively respond to disasters. Recently, social media platforms, especially Twitter, have gained traction as a novel source of information on disaster events. Unfortunately, geographical information is rarely attached to tweets, which hinders the use of Twitter for geographical applications. As a solution, geoparsing algorithms extract and can locate geographical locations referenced in a tweet’s text. This paper describes TAGGS, a new algorithm that enhances location disambiguation by employing both metadata and the contextual spatial information of groups of tweets referencing the same location regarding a specific disaster type. Validation demonstrated that TAGGS approximately attains a recall of 0.82 and precision of 0.91. Without lowering precision, this roughly doubles the number of correctly found administrative subdivisions and cities, towns, and villages as compared to individual geoparsing. We applied TAGGS to 55.1 million flood-related tweets in 12 languages, collected over 3 years. We found 19.2 million tweets mentioning one or more flood locations, which can be towns (11.2 million), administrative subdivisions (5.1 million), or countries (4.6 million). In the future, TAGGS could form the basis for a global event detection system. Numéro de notice : A2018-588 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s41651-017-0010-6 Date de publication en ligne : 26/12/2017 En ligne : https://doi.org/10.1007/s41651-017-0010-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92505
in Journal of Geovisualization and Spatial Analysis > vol 2 n° 1 (June 2018)[article]Exploring the sensitivity of coastal inundation modelling to DEM vertical error / Harry West in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)
[article]
Titre : Exploring the sensitivity of coastal inundation modelling to DEM vertical error Type de document : Article/Communication Auteurs : Harry West, Auteur ; Michael Horswell, Auteur ; Nevil Quinn, Auteur Année de publication : 2018 Article en page(s) : pp 1172 - 1193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse de sensibilité
[Termes IGN] erreur en altitude
[Termes IGN] estuaire
[Termes IGN] incertitude géométrique
[Termes IGN] inondation
[Termes IGN] littoral
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle numérique de surface
[Termes IGN] montée du niveau de la mer
[Termes IGN] Royaume-UniRésumé : (Auteur) As sea level is projected to rise throughout the twenty-first century due to climate change, there is a need to ensure that sea level rise (SLR) models accurately and defensibly represent future flood inundation levels to allow for effective coastal zone management. Digital elevation models (DEMs) are integral to SLR modelling, but are subject to error, including in their vertical resolution. Error in DEMs leads to uncertainty in the output of SLR inundation models, which if not considered, may result in poor coastal management decisions. However, DEM error is not usually described in detail by DEM suppliers; commonly only the RMSE is reported. This research explores the impact of stated vertical error in delineating zones of inundation in two locations along the Devon, United Kingdom, coastline (Exe and Otter Estuaries). We explore the consequences of needing to make assumptions about the distribution of error in the absence of detailed error data using a 1 m, publically available composite DEM with a maximum RMSE of 0.15 m, typical of recent LiDAR-derived DEMs. We compare uncertainty using two methods (i) the NOAA inundation uncertainty mapping method which assumes a normal distribution of error and (ii) a hydrologically correct bathtub method where the DEM is uniformly perturbed between the upper and lower bounds of a 95% linear error in 500 Monte Carlo Simulations (HBM+MCS). The NOAA method produced a broader zone of uncertainty (an increase of 134.9% on the HBM+MCS method), which is particularly evident in the flatter topography of the upper estuaries. The HBM+MCS method generates a narrower band of uncertainty for these flatter areas, but very similar extents where shorelines are steeper. The differences in inundation extents produced by the methods relate to a number of underpinning assumptions, and particularly, how the stated RMSE is interpreted and used to represent error in a practical sense. Unlike the NOAA method, the HBM+MCS model is computationally intensive, depending on the areas under consideration and the number of iterations. We therefore used the HBM+ MCS method to derive a regression relationship between elevation and inundation probability for the Exe Estuary. We then apply this to the adjacent Otter Estuary and show that it can defensibly reproduce zones of inundation uncertainty, avoiding the computationally intensive step of the HBM+MCS. The equation-derived zone of uncertainty was 112.1% larger than the HBM+MCS method, compared to the NOAA method which produced an uncertain area 423.9% larger. Each approach has advantages and disadvantages and requires value judgements to be made. Their use underscores the need for transparency in assumptions and communications of outputs. We urge DEM publishers to move beyond provision of a generalised RMSE and provide more detailed estimates of spatial error and complete metadata, including locations of ground control points and associated land cover. Numéro de notice : A2018-203 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1444165 Date de publication en ligne : 14/03/2018 En ligne : https://doi.org/10.1080/13658816.2018.1444165 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89874
in International journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 1172 - 1193[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2018031 RAB Revue Centre de documentation En réserve L003 Disponible An 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)
[article]
Titre : An open source framework for publishing flood inundation extent libraries in a Web GIS environment using open source technologies Type de document : Article/Communication Auteurs : Vinod Kumar Sharma, Auteur ; Nitin Mishra, Auteur ; C.M. Bhatt, Auteur ; G. Srinivasa Rao, Auteur ; V. Bhanumurthy, Auteur Année de publication : 2018 Article en page(s) : pp 65 - 77 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] base de données localisées
[Termes IGN] bibliothèque logicielle
[Termes IGN] cadre conceptuel
[Termes IGN] cartographie des risques
[Termes IGN] Inde
[Termes IGN] inondation
[Termes IGN] risque naturel
[Termes IGN] visualisation de données
[Termes IGN] WebSIGRésumé : (auteur) The concept of static flood inundation extent libraries and their utilisation to anticipate the extent of inundation to alert and evacuate the population likely to get affected has been suggested by many researchers in different prototype studies. Actual implementation of the concept for a nation like India demands an automated practical operational software framework for systematic organisation, retrieval and visualisation of flood inundation extent libraries in a Geographic Information System (GIS) environment. Implementation of a software framework in a Web GIS environment facilitates decision-makers to access the inundation library with a functionality to overlay other spatial layers for proper situation assessment and decision-making. Utilisation of an open source software library for developing the software framework reduces the overall project cost and its re-distribution. The present work addresses the development of an automated operational framework for one of the chronically flood affected states in India (Bihar) using open source libraries for updating libraries, cataloguing, database organisation, retrieval of data and visualisation of flood extent. The developed framework first reads and arranges the flood forecast information followed by database organisation for identifying the corresponding inundation extent and other related layers available in the library for visualisation. Numéro de notice : A2018-082 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2017.1370861 En ligne : https://doi.org/10.1080/23729333.2017.1370861 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89450
in International journal of cartography > vol 4 n° 1 (March 2018) . - pp 65 - 77[article]Evaluation 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)
[article]
Titre : Evaluation of web maps for the communication of flood risks to the public in Europe Type de document : Article/Communication Auteurs : Maaike Van Kerkvoorde, Auteur ; Wim Kellens, Auteur ; Els Verfaillie, Auteur ; Kristien Ooms, Auteur Année de publication : 2018 Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] cartographie des risques
[Termes IGN] conception cartographique
[Termes IGN] convivialité
[Termes IGN] inondation
[Termes IGN] questionnaire
[Termes IGN] risque naturel
[Termes IGN] utilisateurRésumé : (auteur) Floods are one of the most significant hazards in Europe. This paper describes an iterative approach consisting of designing and evaluating static flood risk maps. In the first step, the use of different colour schemes and background types (e.g. topographic map, street map, and satellite images) is evaluated in an online survey. Next the design is optimized based on the outcomes of dedicated focus groups. The usability tests include the users’ preference, also considering their characteristics (age, gender, and expertise). The obtained results of each step are integrated to optimize the design of evacuation route maps and flood depth maps. Numéro de notice : A2018-081 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2017.1371411 Date de publication en ligne : 06/11/2017 En ligne : https://doi.org/10.1080/23729333.2017.1371411 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89449
in International journal of cartography > vol 4 n° 1 (March 2018) . - pp[article]Extraction 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)
[article]
Titre : Extraction of pluvial flood relevant volunteered geographic information (VGI) by deep learning from user generated texts and photos Type de document : Article/Communication Auteurs : Yu Feng, Auteur ; Monika Sester, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] apprentissage profond
[Termes IGN] Berlin
[Termes IGN] cartographie des risques
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] inondation
[Termes IGN] Londres
[Termes IGN] Paris (75)
[Termes IGN] protection civile
[Termes IGN] risque naturel
[Termes IGN] zone sinistrée
[Termes IGN] zone urbaineRésumé : (Auteur) In recent years, pluvial floods caused by extreme rainfall events have occurred frequently. Especially in urban areas, they lead to serious damages and endanger the citizens’ safety. Therefore, real-time information about such events is desirable. With the increasing popularity of social media platforms, such as Twitter or Instagram, information provided by voluntary users becomes a valuable source for emergency response. Many applications have been built for disaster detection and flood mapping using crowdsourcing. Most of the applications so far have merely used keyword filtering or classical language processing methods to identify disaster relevant documents based on user generated texts. As the reliability of social media information is often under criticism, the precision of information retrieval plays a significant role for further analyses. Thus, in this paper, high quality eyewitnesses of rainfall and flooding events are retrieved from social media by applying deep learning approaches on user generated texts and photos. Subsequently, events are detected through spatiotemporal clustering and visualized together with these high quality eyewitnesses in a web map application. Analyses and case studies are conducted during flooding events in Paris, London and Berlin. Numéro de notice : A2018-105 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7020039 En ligne : https://doi.org/10.3390/ijgi7020039 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89530
in ISPRS International journal of geo-information > vol 7 n° 2 (February 2018)[article]Caractérisation et qualification de Modèles Numériques de Surfaces (MNS) - Analyse de la cohérence avec des masques d’eau / Guillaume Sutter (2018)PermalinkRegard pluridisciplinaire sur les usages sociaux de géovisualisations 3D pour la sensibilisation au risque d’inondation : Un exemple rhodanien / Julia Bonaccorsi in Revue internationale de géomatique, vol 28 n° 1 (janvier - mars 2018)PermalinkPermalinkPermalinkChangement climatique et risque inondation / William Halbecq in Géomatique expert, n° 119 (novembre - décembre 2017)PermalinkA cloud-enabled automatic disaster analysis system of multi-sourced data streams: An example synthesizing social media, remote sensing and Wikipedia data / Qunying Huang in Computers, Environment and Urban Systems, vol 66 (November 2017)PermalinkGéovisualisation de récits d’inondations et des effets dominos : De la méthode de géovisualisation à son évaluation dans un contexte expert / Cécile Saint-Marc in Revue internationale de géomatique, vol 27 n° 4 (octobre - décembre 2017)PermalinkEnseignements du test utilisateur d'une géovisualisation dynamique : des améliorations possibles pour les expériences en cartographie / Cécile Saint-Marc in Cartes & Géomatique, n° 233 (septembre - novembre 2017)PermalinkOptimization of simulation and visualization analysis of dam-failure flood disaster for diverse computing systems / Mingwei Liu in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)PermalinkHERA: A dynamic web application for visualizing community exposure to flood hazards based on storm and sea level rise scenarios / Jeanne M. Jones in Computers & geosciences, vol 109 (December 2017)Permalink