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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)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 2 (February 2018) 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 descripteurs IGN] apprentissage profond [Termes descripteurs IGN] Berlin [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] contenu généré par les utilisateurs [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] inondation [Termes descripteurs IGN] Londres [Termes descripteurs IGN] Paris (75) [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] risque naturel [Termes descripteurs IGN] sécurité civile [Termes descripteurs IGN] urgence [Termes descripteurs IGN] zone urbaine Résumé : (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 [article]

10th International Conference on Geographic Information Science (GIScience 2018), August 28-31, 2018 - Melbourne, Australia / Stephan Winter (2018)  

Public Titre : 10th International Conference on Geographic Information Science (GIScience 2018), August 28-31, 2018 - Melbourne, Australia Type de document : Actes de congrès Auteurs : Stephan Winter, Editeur scientifique ; Amy L. Griffin, Editeur scientifique ; Monika Sester, Editeur scientifique Congrès : GIScience 2018, 10th International Conference on Geographic Information Science (28 - 31 aout 2018; Melbourne, Australie) , Auteur Editeur : Leibniz [Allemagne] : Schloss Dagstuhl – Leibniz-Zentrum für Informatik Année de publication : 2018 Collection : LIPIcs Leibniz International Proceedings in Informatics, ISSN 1868-8969 num. 114 ISBN/ISSN/EAN : 978-3-95977-083-5 Langues : Anglais (eng) Numéro de notice : 17545 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Actes En ligne : http://drops.dagstuhl.de/portals/lipics/index.php?semnr=16081 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91334

Contient

• Detection and localization of traffic signals with GPS floating car data and Random Forest / Yann Méneroux (2018)    
• Towards vandalism detection in OpenStreetMap through a data driven approach [short paper] / Quy Thy Truong (2018)    

Generative models for road network reconstruction / Colin Kuntzsch in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 5-6 (May - June 2016) . - pp 1012 - 1039 Titre : Generative models for road network reconstruction Type de document : Article/Communication Auteurs : Colin Kuntzsch, Auteur ; Monika Sester, Auteur ; Claus Brenner, Auteur Année de publication : 2016 Article en page(s) : pp 1012 - 1039 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] appariement de données localisées [Termes descripteurs IGN] coordonnées GPS [Termes descripteurs IGN] information topologique [Termes descripteurs IGN] itinéraire [Termes descripteurs IGN] méthode de Monte-Carlo par chaînes de Markov [Termes descripteurs IGN] modèle cartographique [Termes descripteurs IGN] réalité de terrain [Termes descripteurs IGN] reconstruction d'objet [Termes descripteurs IGN] réseau routier [Termes descripteurs IGN] trafic routier Résumé : (Auteur) This work aims at the inference of traffic networks from GPS trajectories. We perform geometry and topology reconstruction of the network in a multistep process. Our main contributions are the formulation of an explicit intersection model with a score function that accounts for consistency with the raw tracking data, as well as for a topology prior and the search for the best model by maximization of this score function using a Markov chain Monte Carlo sampler. We demonstrate the viability of our model-based approach with experiments on GPS data sets of varying size and data quality, followed by a comparison with results achieved by alternative, heuristic approaches. Numéro de notice : A2016-293 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1092151 En ligne : https://doi.org/10.1080/13658816.2015.1092151 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80872 [article]

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Information from imagery: ISPRS scientific vision and research agenda / Jun Chen in ISPRS Journal of photogrammetry and remote sensing, vol 115 (May 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 115 (May 2016) . - pp 3 – 21 Titre : Information from imagery: ISPRS scientific vision and research agenda Type de document : Article/Communication Auteurs : Jun Chen, Auteur ; Ian J. Dowman, Auteur ; Songnian Li, Auteur ; Zhilin li, Auteur ; Marguerite Madden, Auteur ; Jon Mills, Auteur ; Nicolas Paparoditis , Auteur ; Franz Rottensteiner, Auteur ; Monika Sester, Auteur ; Charles K. Toth, Auteur ; John C. Trinder, Auteur ; Christian Heipke, Auteur Année de publication : 2016 Article en page(s) : pp 3 – 21 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] information géographique [Termes descripteurs IGN] informatique ubiquitaire [Termes descripteurs IGN] recherche et développement [Termes descripteurs IGN] technologies de l'information et de la communication [Termes descripteurs IGN] télédétection spatiale Mots-clés libres : Research agenda  Photogrammetry  Remote sensing  Spatial information science Résumé : (auteur) With the increased availability of very high-resolution satellite imagery, terrain based imaging and participatory sensing, inexpensive platforms, and advanced information and communication technologies, the application of imagery is now ubiquitous, playing an important role in many aspects of life and work today. As a leading organisation in this field, the International Society for Photogrammetry and Remote Sensing (ISPRS) has been devoted to effectively and efficiently obtaining and utilising information from imagery since its foundation in the year 1910. This paper examines the significant challenges currently facing ISPRS and its communities, such as providing high-quality information, enabling advanced geospatial computing, and supporting collaborative problem solving. The state-of-the-art in ISPRS related research and development is reviewed and the trends and topics for future work are identified. By providing an overarching scientific vision and research agenda, we hope to call on and mobilise all ISPRS scientists, practitioners and other stakeholders to continue improving our understanding and capacity on information from imagery and to deliver advanced geospatial knowledge that enables humankind to better deal with the challenges ahead, posed for example by global change, ubiquitous sensing, and a demand for real-time information generation. Numéro de notice : A2016-541 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.09.008 date de publication en ligne : 09/10/2015 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.09.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81686 [article]

Estimation of precipitation fields from 1-minute rain gauge time series – comparison of spatial and spatio-temporal interpolation methods / D. Fitzner in International journal of geographical information science IJGIS, vol 29 n° 9 (September 2015)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 29 n° 9 (September 2015) . - pp 1668 - 1693 Titre : Estimation of precipitation fields from 1-minute rain gauge time series – comparison of spatial and spatio-temporal interpolation methods Type de document : Article/Communication Auteurs : D. Fitzner, Auteur ; Monika Sester, Auteur Année de publication : 2015 Article en page(s) : pp 1668 - 1693 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] géostatistique [Termes descripteurs IGN] interpolation [Termes descripteurs IGN] précipitation [Termes descripteurs IGN] série temporelle Résumé : (Auteur) Accurate estimations of spatio-temporal fields at unsampled locations are important in a number of applications. Often, spatio-temporal fields are advected, which means the change in field values over time at a particular point in space stems to a large extent from motion of a more or less constant spatial field. For such dynamic fields, interpolation methods including information on the motion behaviour of the field are promising extensions of solely spatial (snapshot) and symmetric spatio-temporal methods. In this paper, the performance of different deterministic and geostatistical interpolation methods is compared for precipitation estimation from 1-minute time series of spatially distributed rain gauges. The focus is on spatio-temporal methods that include information on the motion behaviour of the rainfield, estimated from weather radar using optical flow. The different interpolation methods are introduced and evaluated using rain gauge measurements of a 15-day period and cross-validation. The results show that including information on the motion behaviour significantly improves interpolation quality in terms of RMSE. Numéro de notice : A2015-609 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1040022 En ligne : https://doi.org/10.1080/13658816.2015.1040022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78038 [article]

Model generalization of two different drainage patterns by self-organizing maps / Alper Sen in Cartography and Geographic Information Science, vol 41 n° 2 (March 2014)  

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A generative statistical approach to automatic 3D building roof reconstruction from laser scanning data / Hai Huang in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)

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Spatial relations and properties for semantically enhanced 3D city models / Bénédicte Bucher (2012)

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Quality analysis of OpenStreetMap data based on application needs / J. Mondzech in Cartographica, vol 46 n° 2 (June 2011)

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Aggregation of LoD 1 building models as an optimization problem / R. Guercke in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 2 (March - April 2011)

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vol 66 n° 2 - March - April 2011 - Quality, scale and analysis aspects of urban city models (Bulletin de ISPRS Journal of photogrammetry and remote sensing) / Monika Sester  

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Augmented paper maps: Exploring the design space of a mixed reality system / Volker Paelke in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 3 (May - June 2010)

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Advances in GIScience, Proceedings of the 12th AGILE Conference [AGILE 2009] / Monika Sester (2009)  

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EuroSDR & ISPRS Workshop Geosensor Networks, February 20 - 22 2008, Hannover Germany / Christian Heipke (2008)  

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ISPRS workshop Multiple representation and interoperability of spatial data, Hanover, Germany, 22. - 24. February 2006 / M. Hampe (2006)  

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