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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)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 175 (May 2021) . - pp 132 - 143 Titre : Learning from multimodal and multitemporal earth observation data for building damage mapping Type de document : Article/Communication Auteurs : Bruno Adriano, Auteur ; Naoto Yokoya, Auteur ; Junshi Xia, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 132 - 143 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] cartographie des risques [Termes IGN] catastrophe naturelle [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] cyclone [Termes IGN] dommage [Termes IGN] données multitemporelles [Termes IGN] image à haute résolution [Termes IGN] image optique [Termes IGN] image radar moirée [Termes IGN] observation de la Terre [Termes IGN] segmentation sémantique [Termes IGN] séisme [Termes IGN] surveillance d'ouvrage [Termes IGN] tsunami Résumé : (auteur) Earth observation (EO) technologies, such as optical imaging and synthetic aperture radar (SAR), provide excellent means to continuously monitor ever-growing urban environments. Notably, in the case of large-scale disasters (e.g., tsunamis and earthquakes), in which a response is highly time-critical, images from both data modalities can complement each other to accurately convey the full damage condition in the disaster aftermath. However, due to several factors, such as weather and satellite coverage, which data modality will be the first available for rapid disaster response efforts is often uncertain. Hence, novel methodologies that can utilize all accessible EO datasets are essential for disaster management. In this study, we developed a global multimodal and multitemporal dataset for building damage mapping. We included building damage characteristics from three disaster types, namely, earthquakes, tsunamis, and typhoons, and considered three building damage categories. The global dataset contains high-resolution (HR) optical imagery and high-to-moderate-resolution SAR data acquired before and after each disaster. Using this comprehensive dataset, we analyzed five data modality scenarios for damage mapping: single-mode (optical and SAR datasets), cross-modal (pre-disaster optical and post-disaster SAR datasets), and mode fusion scenarios. We defined a damage mapping framework for semantic segmentation of damaged buildings based on a deep convolutional neural network (CNN) algorithm. We also compared our approach to another state-of-the-art model for damage mapping. The results indicated that our dataset, together with a deep learning network, enabled acceptable predictions for all the data modality scenarios. We also found that the results from cross-modal mapping were comparable to the results obtained from a fusion sensor and optical mode analysis. Numéro de notice : A2021-272 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.02.016 date de publication en ligne : 17/03/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.02.016 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97343 [article]

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A GIS-based system for spatial-temporal availability evaluation of the open spaces used as emergency shelters: The case of Victoria, British Columbia, Canada / Yibing Yao in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 2 (February 2021) . - n° 63 Titre : A GIS-based system for spatial-temporal availability evaluation of the open spaces used as emergency shelters: The case of Victoria, British Columbia, Canada Type de document : Article/Communication Auteurs : Yibing Yao, Auteur ; Yuyang Zhang, Auteur ; Taoyu Yao, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 63 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse multicritère [Termes IGN] cartographie d'urgence [Termes IGN] Colombie-Britannique (Canada) [Termes IGN] données spatiotemporelles [Termes IGN] effondrement de terrain [Termes IGN] planification stratégique [Termes IGN] point d'intérêt [Termes IGN] répartition géographique [Termes IGN] secours d'urgence [Termes IGN] sécurité civile [Termes IGN] séisme [Termes IGN] tsunami [Termes IGN] zone urbaine Résumé : (auteur) Canadian emergency management planners have historically ignored the self-motivated evacuation procedures of people who cannot initially choose the safest evacuation areas. In densely developed urban areas, open spaces can be seen as ideal evacuation areas and should thus be included in shelter planning. In this study, the public open spaces in Great Victoria were selected as the study area and evaluated using GIS technologies. A multi-criteria TOPSIS evaluation model was used to conduct comprehensive quantitative evaluations of the open spaces’ safety, accessibility, and availability. Through hybrid process, service area, and POI aggregation coupling analyses, a model is created that provides an overall evaluation at the district level. In addition to providing a model for evaluating open spaces as emergency shelters, applicable to most Canadian cities, this study emphasizes the importance and disadvantages of open space emergency shelters in Canada, which have heretofore been ignored by decision makers. In Great Victoria, we found that the distribution of open spaces does not match the dynamics of the population distribution, meaning that through inadequate preparation some districts lack a safe evacuation place—this in an area where people are at high risk of earthquake disasters and their subsequent effects. Numéro de notice : A2021-150 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10020063 date de publication en ligne : 02/02/2021 En ligne : https://doi.org/10.3390/ijgi10020063 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97061 [article]

Arctic tsunamis threaten coastal landscapes and communities – survey of Karrat Isfjord 2017 tsunami effects in Nuugaatsiaq, western Greenland / Mateusz C. Strzelecki in Natural Hazards and Earth System Sciences, vol 20 n° 9 (September 2020)  

Public [article]  inNatural Hazards and Earth System Sciences > vol 20 n° 9 (September 2020) . - pp 2521 - 2534 Titre : Arctic tsunamis threaten coastal landscapes and communities – survey of Karrat Isfjord 2017 tsunami effects in Nuugaatsiaq, western Greenland Type de document : Article/Communication Auteurs : Mateusz C. Strzelecki, Auteur ; Marek W. Jaskólski, Auteur Année de publication : 2020 Article en page(s) : pp 2521 - 2534 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse du paysage [Termes IGN] Arctique [Termes IGN] changement climatique [Termes IGN] dégradation des sols [Termes IGN] détection de changement [Termes IGN] effondrement de terrain [Termes IGN] érosion côtière [Termes IGN] fjord [Termes IGN] Groenland [Termes IGN] inondation [Termes IGN] littoral [Termes IGN] paysage [Termes IGN] risque naturel [Termes IGN] toundra [Termes IGN] tsunami Résumé : (auteur) On the 17 June 2017, a massive landslide which mobilized 35–58 million m3 of material entered the Karrat Isfjord in western Greenland. It triggered a tsunami wave with a runup height exceeding 90 m close to the landslide, ca. 50 m on the opposite shore of the fjord. The tsunami travelled ca. 32 km along the fjord and reached the settlement of Nuugaatsiaq with ca. 1–1.5 m high waves which flooded the terrain up to 9 m a.s.l. (above sea level). Tsunami waves were powerful enough to destroy the community infrastructure, impact fragile coastal tundra landscape, and unfortunately injure several inhabitants and cause four deaths. Our field survey carried out 25 months after the event results in documentation of the previously unreported scale of damage in the settlement (ca. 48 % of infrastructure objects including houses and administration buildings were destroyed by the tsunami). We have observed a recognizable difference in the concentration of tsunami deposit accumulations between areas of the settlement overwashed by the wave and areas of runup and return flow. The key tsunami effects preserved in the coastal landscape were eroded coastal bluffs, gullied and dissected edges of cliffed coast in the harbour, and tundra vegetation compressed by boulders or icebergs rafted onshore during the event. Numéro de notice : A2020-612 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/nhess-20-2521-2020 date de publication en ligne : 24/09/2020 En ligne : https://doi.org/10.5194/nhess-20-2521-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95979 [article]

Monitoring suspended particle matter using GOCI satellite data after the Tohoku (Japan) tsunami in 2011 / Audrey Minghelli in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol 12 n° 2 (February 2019)  

Public [article]  inIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing > vol 12 n° 2 (February 2019) . - pp 567 - 576 Titre : Monitoring suspended particle matter using GOCI satellite data after the Tohoku (Japan) tsunami in 2011 Type de document : Article/Communication Auteurs : Audrey Minghelli, Auteur ; Manchun Lei , Auteur ; Sabine Charmasson, Auteur ; Vincent Rey, Auteur ; Malik Chami, Auteur Année de publication : 2019 Projets : AMORAD / Radakovitch, Olivier Article en page(s) : pp 567 - 576 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] détection de changement [Termes IGN] image COMS-GOCI [Termes IGN] Japon [Termes IGN] particule [Termes IGN] risque naturel [Termes IGN] risque technologique [Termes IGN] séisme [Termes IGN] Sendaï [Termes IGN] surveillance géologique [Termes IGN] Tohoku (Japon) [Termes IGN] tsunami Résumé : (auteur) The Fukushima Daiichi nuclear disaster that occurred on March 11, 2011, was caused by the To̅hoku tsunami, which was itself triggered by the devastating 9.0 Mw moment magnitude earthquake. This study investigates spatial and temporal changes of the suspended particulate matter (SPM) content in the North-Eastern part of Japan (Pacific Ocean) using a geostationary ocean color sensor. The Geostationary Ocean Color Imager (GOCI), which is centered on the Korean peninsula but could also observe the Japanese area, is able to acquire eight images per day, thus allowing the analysis of rapid daily changes in water mass. The analysis of GOCI data shows that SPM concentration notably increased both along the coast and within the Bay of Sendaï shortly after the tsunami. Motionless patterns of SPM were observed at 2, 14, 25, and 37 km from the coast. It is shown that SPM concentration rapidly decreased one month later. The SPM concentration did not remain high the following year, contrary to what was observed for the Sumatra Tsunami in 2004. The origin of SPM is also investigated in this study. Our analysis suggests that some of the SPM originates from the resuspension of bottom sediments due to the reflection of the tsunami on the coastline that leads to the migration of marine particles toward the sea surface. The fate of the SPM concentration is then discussed based on the analysis of meteorological conditions, river discharge, and tsunami wave properties. Numéro de notice : A2019-628 Affiliation des auteurs : LaSTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/JSTARS.2019.2894063 date de publication en ligne : 22/02/2019 En ligne : https://doi.org/10.1109/JSTARS.2019.2894063 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95365 [article]

Advanced Remote Sensing Technology for Synthetic Aperture Radar Applications, Tsunami Disasters, and Infrastructure / Maged Marghany (2019)  

Public Titre : Advanced Remote Sensing Technology for Synthetic Aperture Radar Applications, Tsunami Disasters, and Infrastructure Type de document : Monographie Auteurs : Maged Marghany, Editeur scientifique Editeur : Rijeka [Croatie] : InTech Année de publication : 2019 ISBN/ISSN/EAN : 978-1-78985-618-7 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] cartographie des risques [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] géologie [Termes IGN] géophysique [Termes IGN] image 3D [Termes IGN] image captée par drone [Termes IGN] image radar moirée [Termes IGN] image satellite [Termes IGN] interférométrie [Termes IGN] surveillance du littoral [Termes IGN] tsunami Résumé : (éditeur) The advance in space machineries has created a novel technology for observing and monitoring the Earth from space. Most earth observation remote sensing considerations focus on using conventional image processing algorithms or classic edge detection tools. Nevertheless, these techniques do not implement modern physics, applied mathematics, signal communication, remote sensing data, and innovative space technologies. This book provides readers with methods to comprehend how to monitor coastal environments, disaster areas, and infrastructure from space with advanced talent remote sensing technology to bridge the gaps between modern space technology, image processing algorithms, mathematical models and the critical issue of the coastal and infrastructure investigations. Note de contenu : 1- Advanced Ocean Current Simulation from TanDEM Satellite Data 2- On Feature-Based SAR Image Registration: Appropriate Feature and Retrieval Algorithm 3- L-Band SAR Disaster Monitoring for Harbor Facilities Using Interferometric Analysis 4- Utilization of Deep Convolutional Neural Networks for Remote Sensing Scenes Classification 5- Sub-Pixel Technique for Time Series Analysis of Shoreline Changes Based on Multispectral Satellite Imagery 6- Utilization of Dynamic and Static Sensors for Monitoring Infrastructures 7- Geo Spatial Analysis for Tsunami Risk Mapping 8- Utilization of Unmanned Aerial Vehicle for Accurate 3D Imaging Numéro de notice : 25814 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie DOI : 10.5772/intechopen.78525 En ligne : https://www.intechopen.com/books/advanced-remote-sensing-technology-for-syntheti [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95077

Exploring multiplexing tools for co-visualization in crisis units / Christelle Pierkot (2019)    

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Analysis of tsunami evacuation maps for a consensual symbolization rules proposal / Jean-François Girres in International journal of cartography, vol 4 n° 1 (March 2018)  

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MapMuxing : multiplexing cartographique pour la gestion de crise / Charlotte Hoarau (2018) 

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Évolution spatiotemporelle de l’exposition humaine face au tsunami à Padang : diagnostic de la vulnérabilité et des capacités d’évacuations à l’échelle infra-urbaine / Henky Mayaguezz in Revue internationale de géomatique, vol 26 n° 3 (juillet - septembre 2016)  

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Tsunami-wave parameter estimation using GNSS-based sea surface height measurement / Kegen Yu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)

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Modélisation de l'accessibilité territoriale pour l'aide à la gestion de crise tsunami (Mayotte, France) / Frédéric Leone in Annales de géographie, n° 693 (septembre - octobre 2013)

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Tsunami inundation modelling for the coast of Kerala, India / S. Praveen in Marine geodesy, vol 36 n° 1 (January - March 2013)  

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Tsunami inundation modeling and mapping using ALTM- and CARTOSAT-derived coastal topographic data / S. Nayak in Marine geodesy, vol 35 n° 4 (October - December 2012)  

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Modeling of landslide-generated tsunamis with GRASS / M. Cannata in Transactions in GIS, vol 16 n° 2 (April 2012)  

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Co-seismic displacement estimation / M. Crespi in GIM international, vol 25 n° 5 (May 2011)

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