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Flood vulnerability and buildings’ flood exposure assessment in a densely urbanised city: comparative analysis of three scenarios using a neural network approach / Quoc Bao Pham in Natural Hazards, vol 113 n° 2 (September 2022)  

Public [article]  inNatural Hazards > vol 113 n° 2 (September 2022) . - pp 1043 - 1081 Titre : Flood vulnerability and buildings’ flood exposure assessment in a densely urbanised city: comparative analysis of three scenarios using a neural network approach Type de document : Article/Communication Auteurs : Quoc Bao Pham, Auteur ; Sk Ajim Ali, Auteur ; Elzbieta Bielecka, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1043 - 1081 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] aléa [Termes IGN] apprentissage profond [Termes IGN] cartographie des risques [Termes IGN] classification par Perceptron multicouche [Termes IGN] inondation [Termes IGN] modèle de simulation [Termes IGN] prévention des risques [Termes IGN] processus de hiérarchisation analytique [Termes IGN] régression logistique [Termes IGN] réseau neuronal artificiel [Termes IGN] système d'information géographique [Termes IGN] Varsovie (Pologne) [Termes IGN] vulnérabilité [Termes IGN] zone urbaine dense Résumé : (auteur) Advances in the availability of multi-sensor, remote sensing-derived datasets, and machine learning algorithms can now provide an unprecedented possibility to predict flood events and risk. Therefore, this study was undertaken to develop a flood vulnerability map and to assess the exposure of buildings to flood risk in Warsaw, the capital of Poland. This goal was pursued in four research phases. The thirteen flood predictors were evaluated using information gain ratio (IGR), and finally reduced to eight of the most causative ones and used for flood vulnerability mapping with three machine learning algorithms, Artificial Neural Network Multi-Layer Perceptron (ANN/MLP), Deep Learning Neural Network based approach—DL4j (DLNN-DL4j) and Bayesian Logistic Regression (BLR). These algorithms show a good predictive performance with the receiver operating curve (ROC) value of 0.851, 0.877 and 0.697, respectively. The buildings’ exposure to flood was assessed in line with criteria established in European and national legal regulations. The introduced new buildings' flood hazard index (BFH) revealed a significant similarity of potential flood risk for both models, highlighting the greatest risk in zones with high vulnerability to flooding. Depending on the method used, the BFH value was 0.54 (ANN), 0.52 (DLNNs) or 0.64 (BLR). The holistic approach proposed in this study could assist local authorities in improving flood management. Numéro de notice : A2022-705 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1007/s11069-022-05336-5 Date de publication en ligne : 05/04/2022 En ligne : https://doi.org/10.1007/s11069-022-05336-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101569 [article]

Feasibility of the space-time cube in temporal cultural landscape visualization / Edyta P. Bogucka in ISPRS International journal of geo-information, vol 7 n° 6 (June 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 6 (June 2018) Titre : Feasibility of the space-time cube in temporal cultural landscape visualization Type de document : Article/Communication Auteurs : Edyta P. Bogucka, Auteur ; Mathias Jahnke, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cube espace-temps [Termes IGN] données spatiotemporelles [Termes IGN] oculométrie [Termes IGN] patrimoine culturel [Termes IGN] site historique [Termes IGN] système d'information géographique [Termes IGN] Varsovie (Pologne) [Termes IGN] visualisation de données [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) Change acts as an inherent characteristic of the landscape, and expresses dynamic interactions between its tangible and intangible elements. While the documentation and analysis of spatiotemporal patterns have been broadly discussed, major challenges concern the design of task-oriented, user-friendly landscape visualizations. Geographic information system (GIS) techniques and approaches from visual analytics may bring solutions to those questions. This paper considers the milestone documents for the representation of cultural heritage, and proposes a workflow for assessing the feasibility of the space–time cube concept in landscape representation. The usability of the visualization was examined during the interview with domain experts and potential interdisciplinary users. The evaluation session covered benchmark tasks, feedback, and eye-tracking. The performance of the space–time cube was compared with another spatiotemporal visualization technique and measured in terms of correctness, response time, and satisfaction. The Royal Castle in Warsaw, which was registered in 1980 as a part of Warsaw’s World Heritage Site of United Nations Educational, Scientific and Cultural Organization (UNESCO), served as the case study. The user tests show that the designed space–time cube excels for the completion rate; however, more time is required to provide answers to question tasks focusing on comparisons. Together, the case study and feedback from domain experts and participants demonstrate the benefit of the space–time cube concept in designing landscape visualizations. Numéro de notice : A2018-344 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7060209 Date de publication en ligne : 31/05/2018 En ligne : https://doi.org/10.10.3390/ijgi7060209 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90566 [article]