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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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 11 (November 2021) . - pp 2216 - 2237 Titre : A topic model based framework for identifying the distribution of demand for relief supplies using social media data Type de document : Article/Communication Auteurs : Ting Zhang, Auteur ; Shi Shen, Auteur ; Changxiu Cheng, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2216 - 2237 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] allocation de Dirichlet latente [Termes IGN] cartographie thématique [Termes IGN] catastrophe naturelle [Termes IGN] cyclone [Termes IGN] distribution spatiale [Termes IGN] données issues des réseaux sociaux [Termes IGN] Pacifique ouest [Termes IGN] Philippines [Termes IGN] répertoire toponymique [Termes IGN] secours d'urgence Résumé : (auteur) Natural disasters have caused substantial economic losses and numerous casualties. The demand analysis of relief supplies is the premise and basis for efficient relief operations after disasters. With the widespread use of social media, it has become a vital channel for people to report their demand for relief supplies and provides a way to obtain information on disaster areas. Therefore, we present a topic model-based framework and establish a demand dictionary and a gazetteer that aims to identify the spatial distribution of the demand for relief supplies by using social media data. Taking the 2013 Typhoon Haiyan (also called Yolanda) as a case study, we identify the potential topics of tweets with the biterm topic model, screen the tweets related to demands, and obtain the demand and location information from tweets to study the distribution of the relief supplies needs. The results show that, based on the demand dictionary, a gazetteer and the biterm topic model, the effective demand for relief supplies can be extracted from tweets. The proposed framework is feasible for the identification of accurate demand information and its distribution. Further, this framework can be applied to other types of disaster responses and can facilitate relief operations. Numéro de notice : A2021-757 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1869746 Date de publication en ligne : 07/01/2021 En ligne : https://doi.org/10.1080/13658816.2020.1869746 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98772 [article]

Disaster intensity-based selection of training samples for remote sensing building damage classification / Luis Moya in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 10 (October 2021) . - pp 8288 - 8304 Titre : Disaster intensity-based selection of training samples for remote sensing building damage classification Type de document : Article/Communication Auteurs : Luis Moya, Auteur ; Christian Geiss, Auteur ; Masakazu Hashimoto, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 8288 - 8304 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] déformation d'édifice [Termes IGN] détection de changement [Termes IGN] détection du bâti [Termes IGN] dommage matériel [Termes IGN] données de terrain [Termes IGN] échantillonnage de données [Termes IGN] image optique [Termes IGN] inondation [Termes IGN] séisme Résumé : (auteur) Previous applications of machine learning in remote sensing for the identification of damaged buildings in the aftermath of a large-scale disaster have been successful. However, standard methods do not consider the complexity and costs of compiling a training data set after a large-scale disaster. In this article, we study disaster events in which the intensity can be modeled via numerical simulation and/or instrumentation. For such cases, two fully automatic procedures for the detection of severely damaged buildings are introduced. The fundamental assumption is that samples that are located in areas with low disaster intensity mainly represent nondamaged buildings. Furthermore, areas with moderate to strong disaster intensities likely contain damaged and nondamaged buildings. Under this assumption, a procedure that is based on the automatic selection of training samples for learning and calibrating the standard support vector machine classifier is utilized. The second procedure is based on the use of two regularization parameters to define the support vectors. These frameworks avoid the collection of labeled building samples via field surveys and/or visual inspection of optical images, which requires a significant amount of time. The performance of the proposed method is evaluated via application to three real cases: the 2011 Tohoku-Oki earthquake–tsunami, the 2016 Kumamoto earthquake, and the 2018 Okayama floods. The resulted accuracy ranges between 0.85 and 0.89, and thus, it shows that the result can be used for the rapid allocation of affected buildings. Numéro de notice : A2021-711 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3046004 Date de publication en ligne : 13/01/2021 En ligne : https://doi.org/10.1109/TGRS.2020.3046004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98615 [article]

Landslide susceptibility prediction based on image semantic segmentation / Bowen Du in Computers & geosciences, vol 155 (October 2021)  

Public [article]  inComputers & geosciences > vol 155 (October 2021) . - n° 104860 Titre : Landslide susceptibility prediction based on image semantic segmentation Type de document : Article/Communication Auteurs : Bowen Du, Auteur ; Zirong Zhao, Auteur ; Xiao Hu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 104860 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] aléa [Termes IGN] apprentissage automatique [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] effondrement de terrain [Termes IGN] image captée par drone [Termes IGN] modèle de simulation [Termes IGN] prévention des risques [Termes IGN] segmentation sémantique Résumé : (auteur) Numéro de notice : A2021-683 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.104860 Date de publication en ligne : 16/06/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104860 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98408 [article]

On the suitability of a unified GIS-BIM-HBIM framework for cataloguing and assessing vulnerability in Historic Urban Landscapes: a critical review / Rafael Ramirez Eudave in International journal of geographical information science IJGIS, vol 35 n° 10 (October 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 10 (October 2021) . - pp 2047 - 2077 Titre : On the suitability of a unified GIS-BIM-HBIM framework for cataloguing and assessing vulnerability in Historic Urban Landscapes: a critical review Type de document : Article/Communication Auteurs : Rafael Ramirez Eudave, Auteur ; Tiago Miguel Ferreira, Auteur Année de publication : 2021 Article en page(s) : pp 2047 - 2077 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] base de données localisées [Termes IGN] centre urbain [Termes IGN] CityGML [Termes IGN] codage [Termes IGN] format Industry foudation classes IFC [Termes IGN] géoréférencement [Termes IGN] modélisation 3D du bâti BIM [Termes IGN] monument historique [Termes IGN] prévention des risques [Termes IGN] système d'information géographique [Termes IGN] vulnérabilité Résumé : (auteur) The use of digital representations of physical objects allows to simulate phenomena and predict behaviours. The representativeness of a model is based on the congruency between the code, the survey and the modelling strategies. In terms of physical space, two important approaches are the Geographical Information Systems (GIS) and Building Information Modelling (BIM). GIS approach is intended to code environmental information based on geographical references. BIM approach is intended to code buildings in terms of their components, generating parametric descriptions. For historic buildings, BIM extends to the so-called Historical BIM models (HBIM). Together, these strategies allow coding territorial-scale entities, such as historical centres. An application for these models would be the simulation of risk situations, leading to vulnerability analysis. Despite the existence of GIS-BIM-HBIM integration examples, most of their procedures are designed to fit with a specific case study, which questions the suitability of a general coding framework. This paper presents a vision of state-of-the-art technologies and strategies for coding, surveying and model historical centres, with emphases on the analysis of urban vulnerability and risk. Finally, we propose a general comprehensive framework on the convergences of GIS-BIM-HBIM technologies and successful practices. Numéro de notice : A2021-657 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1844208 Date de publication en ligne : 09/11/2020 En ligne : https://doi.org/10.1080/13658816.2020.1844208 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98393 [article]

GIS models for vulnerability of coastal erosion assessment in a tropical protected area / Luís Russo Vieira in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 9 (September 2021) . - n° 598 Titre : GIS models for vulnerability of coastal erosion assessment in a tropical protected area Type de document : Article/Communication Auteurs : Luís Russo Vieira, Auteur ; José Guilherme Vieira, Auteur ; Isabel Marques da silva, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 598 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] Brésil [Termes IGN] érosion côtière [Termes IGN] géoréférencement [Termes IGN] mangrove [Termes IGN] modèle de simulation [Termes IGN] système d'information géographique [Termes IGN] vulnérabilité [Termes IGN] zone intertropicale Résumé : (auteur) Coastal erosion is considered a major worldwide challenge. The vulnerability assessment of coastal areas, in relation to climate change, is a key topic of worldwide increasing interest. The integration of methodologies supported by Remote Sensing, Geographical Information Systems (GIS) and in situ monitoring has allowed a viable identification of vulnerable areas to erosion. In the present study, a model was proposed to the assessment of the estuarine system of Cananéia-Iguape (Brazil), by applying the evaluation and prediction of vulnerability models for the conservation and preservation of mangroves. Approximately 1221 Km2 were classified, with 16% of the total presenting high and very high vulnerability to erosion. Other relevant aspects, were the identification and georeferencing sites that showed strong evidence of erosion and, thus, having a huge influence on the final vulnerability scores. The obtained results led to the development of a multidisciplinary approach through the application of a prediction and description model that resulted from the adaptation of the study system from a set of implemented models for coastal regions, in order to contribute to the erosion vulnerability assessment in the mangroves ecosystems (and associated localities, municipalities and communities). Numéro de notice : A2021-685 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10090598 Date de publication en ligne : 10/09/2021 En ligne : https://doi.org/10.3390/ijgi10090598 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98411 [article]

Establishing vertical separation models for vulnerable coastlines in developing territories / Cassandra Nanlal in Marine geodesy, vol 44 n° 5 (September 2021)  

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Anomalous variations of air temperature prior to earthquakes / Irfan Mahmood in Geocarto international, vol 36 n° 12 ([01/07/2021])  

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Climate warming predispose sessile oak forests to drought-induced tree mortality regardless of management legacies / Any Mary Petritan in Forest ecology and management, vol 491 (1st July 2021)  

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Detecting high-temperature anomalies from Sentinel-2 MSI images / Yongxue Liu in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 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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Groundwater vulnerability assessment of the chalk aquifer in the northern part of France / Lahcen Zouhri in Geocarto international, vol 36 n° 11 ([15/06/2021])  

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Provisioning forest and conservation science with high-resolution maps of potential distribution of major European tree species under climate change / Debojyoti Chakraborty in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)  

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Analysing the impact of climate change on hydrological ecosystem services in Laguna del Sauce (Uruguay) using the SWAT model and remote sensing data / Celina Aznarez in Remote sensing, vol 13 n°10 (May 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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Potentialité des données satellitaires Sentinel-2 pour la cartographie de l’impact des feux de végétation en Afrique tropicale : application au Togo / Yawo Konko in Bois et forêts des tropiques, n° 347 ([02/04/2021])  

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