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scientifique

Peut-on prédire les séismes ? / Laurent Polidori in Géomètre, n° 2211 (mars 2023)

Public [article]  inGéomètre > n° 2211 (mars 2023) . - pp 21 - 21 Titre : Peut-on prédire les séismes ? Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2023 Article en page(s) : pp 21 - 21 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] catastrophe naturelle [Termes IGN] déformation de la croute terrestre [Termes IGN] Demeter (microsatellite) [Termes IGN] observation de la Terre [Termes IGN] risque naturel [Termes IGN] séisme [Termes IGN] station GNSS [Termes IGN] tectonique des plaques Résumé : (Auteur) Le 6 février, un séisme de magnitude 7,8 s’est produit à la frontière entre la Turquie et la Syrie, faisant près de 50000 victimes. Quelques minutes auraient suffi pour épargner presque toutes les vies, aussi s’interroge-t-on à chaque catastrophe : aurait-on pu la prédire ? Numéro de notice : A2023-066 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 01/03/2023 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102713 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
063-2023031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Open mapping towards sustainable development goals / Patricia Solís (2023)  

Public Titre : Open mapping towards sustainable development goals : Voices of youthmappers on community engaged scholarship Type de document : Monographie Auteurs : Patricia Solís, Éditeur scientifique ; Marcela Zeballos, Éditeur scientifique Editeur : Springer Nature Année de publication : 2023 Importance : 382 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-031-05182-1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] Afrique occidentale [Termes IGN] approche participative [Termes IGN] Asie (géographie politique) [Termes IGN] cartographe [Termes IGN] cartographie thématique [Termes IGN] catastrophe naturelle [Termes IGN] changement climatique [Termes IGN] développement durable [Termes IGN] données localisées [Termes IGN] eau [Termes IGN] édition en libre accès [Termes IGN] formation [Termes IGN] géopolitique [Termes IGN] OpenStreetMap [Termes IGN] université Résumé : (éditeur) This collection amplifies the experiences of some of the world’s young people who are working to address SDGs using geospatial technologies and multi-national collaboration. Authors from every region of the world who have emerged as leaders in the YouthMappers movement share their perspectives and knowledge in an accessible and peer-friendly format. YouthMappers are university students who create and use open mapping for development and humanitarian purposes. Their work leverages digital innovations - both geospatial platforms and communications technologies - to answer the call for leadership to address sustainability challenges. The book conveys a sense of robust knowledge emerging from formal studies or informal academic experiences - in the first-person voices of students and recent graduates who are at the forefront of creating a new map of the world. YouthMappers use OpenStreetMap as the foundational sharing mechanism for creating data together. Authors impart the way they are learning about themselves, about each other, about the world. They are developing technology skills, and simultaneously teaching the rest of the world about the potential contributions of a highly connected generation of emerging world leaders for the SDGs. The book is timely, in that it captures a pivotal moment in the trajectory of the YouthMappers movement’s ability to share emerging expertise, and one that coincides with a pivotal moment in the geopolitical history of planet earth whose inhabitants need to hear from them. Most volumes that cover the topic of sustainability in terms of youth development are written by non-youth authors. Moreover, most are written by non-majoritarian, entrenched academic scholars. This book instead puts forward the diverse voices of students and recent graduates in countries where YouthMappers works, all over the world. Authors cover topics that range from water, agriculture, food, to waste, education, gender, climate action and disasters from their own eyes in working with data, mapping, and humanitarian action, often working across national boundaries and across continents. To inspire readers with their insights, the chapters are mapped to the United Nations 17 Sustainable Development Goals (SDGs) in ways that connect a youth agenda to a global agenda. With a preface written by Carrie Stokes, Chief Geographer and GeoCenter Director, United States Agency for International Development (USAID). This is an open access book. Note de contenu : 1- Introduction Part I- Mapping for the goals on poverty, hunger, health, education, gender, water, and energy 2- Open data addressing challenges associated with informal settlements in the global South 3- Leveraging spatial technology for agricultural intensification to address hunger in Ghana 4- Rural household food insecurity and child malnutrition in Northern Ghana 5- Where is the closest health clinic? YouthMappers map their communities before and during the COVID-19 pandemic 6- Cross-continental youthmappers action to fight schistosomiasis transmission in Senegal 7- Understanding youthmappers’ contributions to building resilient communities in Asia 8- Activating education for sustainable development goals through youthmappers 9- Seeing the world through maps: An inclusive and youth-oriented approach 10- Youth engagement and the water–energy–land nexus in Costa Rica 11- Power grid mapping in West Africa 12- Mapping access to electricity in urban and rural Nigeria Part II- Youth action on work, leadership, innovation, inequality, cities, production and land 13- Stories from students building sustainability through transfer of leadership 14- Drones for good: Mapping out the SDGs using innovative technology in Malawi 15- Assessing youthmappers contributions to the generation of open geospatial data in Africa 16- Mapping invisible and inaccessible areas of Brazilian cities to reduce inequalities 17- Visualizing youthMappers’ contributions to environmental resilience in Latin America Numéro de notice : 24082 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.1007/978-3-031-05182-1 En ligne : https://doi.org/10.1007/978-3-031-05182-1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102333

Spatio-temporal graph convolutional networks for road network inundation status prediction during urban flooding / Faxi Yuan in Computers, Environment and Urban Systems, vol 97 (October 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 97 (October 2022) . - n° 101870 Titre : Spatio-temporal graph convolutional networks for road network inundation status prediction during urban flooding Type de document : Article/Communication Auteurs : Faxi Yuan, Auteur ; Yuanchang Xu, Auteur ; Qingchun Li, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101870 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] catastrophe naturelle [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] graphe [Termes IGN] inondation [Termes IGN] modèle de simulation [Termes IGN] polynôme de Chebysheff [Termes IGN] prévention des risques [Termes IGN] réseau neuronal de graphes [Termes IGN] réseau routier [Termes IGN] Texas (Etats-Unis) [Termes IGN] zone urbaine Résumé : (auteur) The objective of this study is to predict the near-future flooding status of road segments based on their own and adjacent road segments' current status through the use of deep learning framework on fine-grained traffic data. Predictive flood monitoring for situational awareness of road network status plays a critical role to support crisis response activities such as evaluation of the loss of access to hospitals and shelters. Existing studies related to near-future prediction of road network flooding status at road segment level are missing. Using fine-grained traffic speed data related to road sections, this study designed and implemented three spatio-temporal graph convolutional network (STGCN) models to predict road network status during flood events at the road segment level in the context of the 2017 hurricane Harvey in Harris County (Texas, USA). Model 1 consists of two spatio-temporal blocks considering the adjacency and distance between road segments, while model 2 contains an additional elevation block to account for elevation difference between road segments. Model 3 includes three blocks for considering the adjacency and the product of distance and elevation difference between road segments. The analysis tested the STGCN models and evaluated their prediction performance. Our results indicated that model 1 and model 2 have reliable and accurate performance for predicting road network flooding status in near future (e.g., 2–4 h) with model precision and recall values larger than 98% and 96%, respectively. With reliable road network status predictions in floods, the proposed model can benefit affected communities to avoid flooded roads and the emergency management agencies to implement evacuation and relief resource delivery plans. Numéro de notice : A2022-656 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101870 Date de publication en ligne : 22/08/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101870 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101506 [article]

A geographical and content-based approach to prioritize relevant and reliable tweets for emergency management / A. Marcela Suarez in Cartography and Geographic Information Science, Vol 49 n° 5 (September 2022)  

Public [article]  inCartography and Geographic Information Science > Vol 49 n° 5 (September 2022) . - pp 443 - 463 Titre : A geographical and content-based approach to prioritize relevant and reliable tweets for emergency management Type de document : Article/Communication Auteurs : A. Marcela Suarez, Auteur ; Keith C. Clarke, Auteur Année de publication : 2022 Article en page(s) : pp 443 - 463 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] catastrophe naturelle [Termes IGN] classement [Termes IGN] données issues des réseaux sociaux [Termes IGN] Etats-Unis [Termes IGN] fiabilité des données [Termes IGN] filtrage d'information [Termes IGN] gestion de crise [Termes IGN] pertinence [Termes IGN] qualité des données [Termes IGN] secours d'urgence [Termes IGN] tempête [Termes IGN] Twitter Résumé : (auteur) Tweets posted by the general public during disaster events represent timely, up-to-date, and on-site data that may be useful for emergency responders. However, since Twitter data has been deemed to be unverifiable and untrustworthy, it is challenging to identify those reliable and relevant tweets that can inform emergency response operations. Although computational methods exist both to classify overwhelming amounts of tweets and to filter those relevant to emergency response, using contextual geographic information regarding the disaster event to filter tweets has been overlooked. We review the existing research on the quality of data contributed by the general public from a geographical perspective, and then propose an approach to prioritize tweets for emergency response based on their relevance and reliability. The novelty of the approach is twofold: a) the use of both authoritative data such as hazard-related information and on-the-ground reports provided by weather spotters and validated by the National Weather Service; and b) the fact that it leverages tweets content as well as their geographical context and location. Using Hurricane Harvey in 2017 as a case study, results show that by following the proposed approach 79% of tweets sent from post-identified flooded areas were classified as of high or medium relevance and reliability. This suggests that the proposed approach can provide an accurate prioritization of tweets to be used for real time emergency management. Numéro de notice : A2022-633 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2022.2081257 En ligne : https://doi.org/10.1080/15230406.2022.2081257 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101399 [article]

Visualising post-disaster damage on maps: a user study / Thomas Candela 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 1364 - 1393 Titre : Visualising post-disaster damage on maps: a user study Type de document : Article/Communication Auteurs : Thomas Candela, Auteur ; Matthieu Péroche, Auteur ; Arnaud Sallaberry, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1364 - 1393 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte de répartition par points [Termes IGN] catastrophe naturelle [Termes IGN] comportement [Termes IGN] dommage matériel [Termes IGN] enquête [Termes IGN] lecture de carte [Termes IGN] oculométrie [Termes IGN] psychologie cognitive [Termes IGN] représentation cartographique [Termes IGN] sémiologie graphique [Termes IGN] tessellation [Vedettes matières IGN] Géovisualisation Résumé : (auteur) The mapping of the damage caused by natural disasters is a crucial step in deciding on the actions to take at the international, national, and local levels. The large variety of representations that we have observed leads to problems of transfer and variations in analysis. In this article, we propose a representation, Regular Dot map (RD), and we compare it to 4 others routinely used to visualise post-disaster damage. Our comparison is based on a user study in which a set of participants carried out various tasks on multiple datasets using the various visualisations. We then analysed the behaviour during the experiment using three approaches: (1) quantitative analysis of user answers according to the reality on the ground, (2) quantitative analysis of user preferences in terms of perceived effectiveness and appearance, and (3) qualitative analysis of the data collected using an eye tracker. The results of this study lead us to believe that RD is the best compromise in terms of effectiveness among the various representations studied. Numéro de notice : A2022-492 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2063872 Date de publication en ligne : 19/04/2022 En ligne : https://doi.org/10.1080/13658816.2022.2063872 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100971 [article]

Exemplaires(1)

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

Simulation d'ouragans et de collectes de déchets sur QGIS pour l'amélioration de la collecte des déchets post-ouragan / Quy Thy Truong in Cartes & Géomatique, n° 247-248 (mars-juin 2022)

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Automated construction of a French Entity Linking dataset to geolocate social network posts in the context of natural disasters / Gaëtan Caillaut (2022)  

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Cartographier l'anthropocène 2022 / IGN (2022)    

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A repeatable change detection approach to map extreme storm-related damages caused by intense surface runoff based on optical and SAR remote sensing: Evidence from three case studies in the South of France / Arnaud Cerbelaud in ISPRS Journal of photogrammetry and remote sensing, Vol 182 (December 2021)  

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A topic model based framework for identifying the distribution of demand for relief supplies using social media data / Ting Zhang in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

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Disaster Image Classification by Fusing Multimodal Social Media Data / Zhiqiang Zou in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)  

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A framework to manage uncertainty in the computation of waste collection routes after a flood / Arnaud Le Guilcher in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-4-2021 (July 2021)  

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Learning from multimodal and multitemporal earth observation data for building damage mapping / Bruno Adriano in ISPRS Journal of photogrammetry and remote sensing, vol 175 (May 2021)  

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Développement d’outils d’exploitation des archives photographiques aériennes de l’IGN pour caractériser l’évolution pluridécennale du littoral sur l’île de la Réunion / Adinane Oladjidé Ayichemi (2021)  

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Optimisations cartographiques pour la gestion des crises et des risques majeurs : le cas de la cartographie des dommages post-catastrophes / Thomas Candela (2021)  

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