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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)
[article]
Titre : Simulation d'ouragans et de collectes de déchets sur QGIS pour l'amélioration de la collecte des déchets post-ouragan Type de document : Article/Communication Auteurs : Quy Thy Truong , Auteur ; Anne Ruas , Auteur Année de publication : 2022 Conférence : ICC 2021, 30th ICA international cartographic conference 14/12/2021 18/12/2021 Florence Italie Article en page(s) : pp 61 - 63 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] catastrophe naturelle
[Termes IGN] collecte des déchets
[Termes IGN] dommage matériel
[Termes IGN] gestion de crise
[Termes IGN] implémentation (informatique)
[Termes IGN] module d'extension
[Termes IGN] prototype
[Termes IGN] QGIS
[Termes IGN] Saint-Martin, île de
[Termes IGN] simulation spatiale
[Termes IGN] stockage
[Termes IGN] tempêteRésumé : (Auteur) [Contexte] Au cours des dernières décennies, des évènements naturels catastrophiques tels que des tempêtes et des ouragans ont touché des millions de personnes dans le Monde : environ 33 millions de personnes sont touchées chaque année entre 2007 et 2016 (Bellow et Wallemacq, 2018). Par exemple, l'ouragan Katrina (Etas-Unis, 2015) a causé des dégâts catastrophiques du centre de la Floride à l'est du Texas, au moins 1836 personnes sont mortes et le total des dommages matériels a été estimé à 125 milliards de dollars. Par ailleurs, le changement climatique est susceptible d'augmenter la fréquence des catégories d'ouragans les plus intenses ainsi que le niveau de la mer, entraînant des ondes de tempête plus destructrices lorsque des ouragans se produisent (GIEC, 2013). Les ouragans génèrent de grandes quantités de déchets directement liés aux impacts induits (Brown et al., 2011). La rapidité de collecte et de tri des déchets est essentielle car non seulement les déchets bloquent et ralentissent l'activité humaine mais ils génèrent aussi des pollutions. La gestion de ces déchets est donc un enjeu majeur dans la gestion de crise post-ouragan. L'ouragan Irma, qui a frappé les Caraïbes au début de septembre 2017, en particulier les îles de Saint-Martin et Saint-Barthélémy, est un exemple frappant de ce problème. Dans cet article nous présentons un système d'information pour améliorer la collecte des déchets post-ouragan aux Antilles françaises. Ces travaux sont faits dans le cadre du projet de recherche DéPOs financé par l'ANR. Numéro de notice : A2022-676 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101891
in Cartes & Géomatique > n° 247-248 (mars-juin 2022) . - pp 61 - 63[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 021-2022011 SL Revue Centre de documentation Revues en salle Disponible Traffic sign three-dimensional reconstruction based on point clouds and panoramic images / Minye Wang in Photogrammetric record, vol 37 n° 177 (March 2022)
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Titre : Traffic sign three-dimensional reconstruction based on point clouds and panoramic images Type de document : Article/Communication Auteurs : Minye Wang, Auteur ; Rufei Liu, Auteur ; Jiben Yang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 87 - 110 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] correction d'image
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image panoramique
[Termes IGN] lidar mobile
[Termes IGN] reconstruction 3D
[Termes IGN] semis de points
[Termes IGN] signalisation routièreRésumé : (auteur) Traffic signs are a very important source of information for drivers and pilotless automobiles. With the advance of Mobile LiDAR System (MLS), massive point clouds have been applied in three-dimensional digital city modelling. However, traffic signs in MLS point clouds are low density, colourless and incomplete. This paper presents a new method for the reconstruction of vertical rectangle traffic sign point clouds based on panoramic images. In this method, traffic sign point clouds are extracted based on arc feature and spatial semantic features analysis. Traffic signs in images are detected by colour and shape features and a convolutional neural network. Traffic sign point cloud and images are registered based on outline features. Finally, traffic sign points match traffic sign pixels to reconstruct the traffic sign point cloud. Experimental results have demonstrated that this proposed method can effectively obtain colourful and complete traffic sign point clouds with high resolution. Numéro de notice : A2022-254 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12398 Date de publication en ligne : 05/03/2022 En ligne : https://doi.org/10.1111/phor.12398 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100217
in Photogrammetric record > vol 37 n° 177 (March 2022) . - pp 87 - 110[article]Understanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea / Yang Xu in Computers, Environment and Urban Systems, vol 92 (March 2022)
[article]
Titre : Understanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea Type de document : Article/Communication Auteurs : Yang Xu, Auteur ; Dan Zou, Auteur ; Sangwon Park, Auteur ; et al., Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] chaîne de Markov
[Termes IGN] classification par réseau neuronal récurrent
[Termes IGN] Corée du sud
[Termes IGN] durée de trajet
[Termes IGN] mobilité humaine
[Termes IGN] modèle de simulation
[Termes IGN] prévision à court terme
[Termes IGN] téléphone intelligent
[Termes IGN] téléphonie mobile
[Termes IGN] tourisme
[Termes IGN] voyageRésumé : (auteur) The abilities to predict tourist movements are critical to many urban applications, such as travel recommendations, targeted advertising, and infrastructure planning. Despite its importance, our understanding on the movement predictability of urban tourists and visitors is still limited, partially due to difficulties in accessing large scale mobility observations. In this study, we aim to bridge this gap by analyzing a nationwide mobile phone dataset. The dataset captures movement traces of a large number of international travelers who visited South Korea in 2018. By introducing two prediction models, one being Markov chain and the other with a recurrent neural network architecture, we assess how well travelers’ movements can be predicted under different model settings, and examine how predictability relates to travelers’ length of stay and activeness in travel patterns. Since travelers’ destination choices are quite diverse in South Korea, this enables us to further investigate the geographic variation of the models’ performance. Results show that the Markov chain model achieves an overall accuracy between 33.4% (@Acc1 metric) and 64.2% (@Acc5 metric), compared to 41.9% (@Acc1) and 67.7% (@Acc5) for the recurrent neural network model. The prediction capabilities of both models are largely unequal across individuals, with active travelers being more predictable in general. There is a notable geographic variation in the models’ performance, meaning that travelers’ movements are more predictable in some cities, but less in others. We believe this study represents a new effort in portraying the movement predictability of urban tourists and visitors. The analytical framework can be applied to assist tourism planning and service deployment in cities. Numéro de notice : A2022-085 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101753 Date de publication en ligne : 06/01/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101753 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99490
in Computers, Environment and Urban Systems > vol 92 (March 2022)[article]Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata / Aditya Tafta Nugraha in Computers, Environment and Urban Systems, vol 92 (March 2022)
[article]
Titre : Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata Type de document : Article/Communication Auteurs : Aditya Tafta Nugraha, Auteur ; Ben J. Waterson, Auteur ; Simon P. Blainey, Auteur ; et al., Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] dynamique spatiale
[Termes IGN] Grande-Bretagne
[Termes IGN] interaction spatiale
[Termes IGN] modèle orienté agent
[Termes IGN] morphologie urbaine
[Termes IGN] planification urbaine
[Termes IGN] port
[Termes IGN] transport urbain
[Termes IGN] utilisation du solRésumé : (auteur) The urban morphology is characterised by self-organisation where interactions of multiple agents produce emerging patterns on the urban form. Port-urban relationship added to the complexity of port cities' urban form. Most urban cellular automata (CA) models simulate land-use evolution through transition rules representing multi-factored local interactions. However, calibration of CA-based urban land use and transport interaction (LUTI) models often utilise manual methods due to complexity of the process. This limits insights on urban interactions to a few explored settlements and prevents applications for planning and assessment of transport policies in other contexts. This paper, therefore, addresses three main points. The paper (i) demonstrates an improved method for the calibration of CA-based LUTI models, (ii) contributes to a better understanding of the urban dynamics in port city systems by quantifying generalizable interactions from a wide range of port-urban settlements, and (iii) illustrates how the use of these interactions in a simulation model can allow long-term impact predictions of planning interventions. These were done by formulating a model in a similar structure as a neural network model to enable automatic calibration using an application of the gradient-descent algorithm. The model was then used to quantify the dynamics between land-use, geographic, and transport factors in 46 port-based and 10 non-port settlements across Great Britain, thus enabling cross-sectional analysis. Cluster analysis of the calibrated interactions in the study areas was conducted to examine the variations of these interactions. This produced two main groups. In the first group, consisting larger settlements, connections between ports and other urban activities were weaker than in the second group which consisted of smaller port-settlements. Overall, the findings of the research are consistent with existing evidence in the port-cities literature but go further in quantifying the interaction between urban agents within port-urban systems of various sizes and types. These quantified interactions will enable planners to better predict the longer-term consequences of their interventions. Numéro de notice : A2022-084 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101733 Date de publication en ligne : 25/11/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101733 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99489
in Computers, Environment and Urban Systems > vol 92 (March 2022)[article]Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis / Kai Zhang in Sustainable Cities and Society, vol 78 (March 2022)
[article]
Titre : Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis Type de document : Article/Communication Auteurs : Kai Zhang, Auteur ; Zhen Qian, Auteur ; Yue Yang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 103598 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage profond
[Termes IGN] cartographie du bruit
[Termes IGN] Chine
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] distribution spatiale
[Termes IGN] image Streetview
[Termes IGN] lutte contre le bruit
[Termes IGN] milieu urbain
[Termes IGN] OpenStreetMap
[Termes IGN] planification urbaine
[Termes IGN] pollution acoustique
[Termes IGN] trafic routier
[Termes IGN] ville durableRésumé : (auteur) Road noise barriers (RNBs) are important urban infrastructures to relieve the harm of traffic noise pollution for citizens. Therefore, obtaining the spatial distribution characteristics of RNBs, such as precise positions and mileage, can be of great help for obtaining more accurate urban noise maps and assessing the quality of the urban living environment for sustainable urban development. However, an effective and efficient method for identifying RNBs and acquiring their attributes in large areas is scarce. This study constructs an ensemble classification model (ECM) to automatically identify RNBs at the city level based on Baidu Street View (BSV). Firstly, the bootstrap sampling method is proposed to build a street view image-based train set, where the effect of imbalanced categories of samples was reduced by adding confusing negative samples. Secondly, two state-of-the-art deep learning models, ResNet and DenseNet, are ensembled to construct an ECM based on the bagging framework. Finally, a post-processing method has been proposed based on geospatial analysis to eliminate street view images (SVIs) that are misclassified as RNBs. This study takes Suzhou, China as the study area to validate the proposed method. The model achieved an accuracy and F1-score of 0.98 and 0.90, respectively. The total mileage of the RNBs in Suzhou was 178,919 m. The results demonstrated the performance of the proposed RNBs identification framework. The significance of obtaining RNBs attributes for accelerating sustainable urban development has been demonstrated through the case of photovoltaic noise barriers (PVNBs). Numéro de notice : A2022-241 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1016/j.scs.2021.103598 Date de publication en ligne : 20/12/2021 En ligne : https://doi.org/10.1016/j.scs.2021.103598 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100167
in Sustainable Cities and Society > vol 78 (March 2022) . - n° 103598[article]A method of vision aided GNSS positioning using semantic information in complex urban environment / Rui Zhai in Remote sensing, vol 14 n° 4 (February-2 2022)PermalinkSimulating fire-safe cities using a machine learning-based algorithm for the complex urban forms of developing nations: a case of Mumbai India / Vaibhav Kumar in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkDiscovering transition patterns among OpenStreetMap feature classes based on the Louvain method / Yijiang Zhao in Transactions in GIS, vol 26 n° 1 (February 2022)PermalinkEmerging technologies for smart cities’ transportation: Geo-information, data analytics and machine learning approaches / Li-Minn Ang in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)PermalinkExploring the advantages of the maximum entropy model in calibrating cellular automata for urban growth simulation: a comparative study of four methods / Bin Zhang in GIScience and remote sensing, vol 59 n° 1 (2022)PermalinkGenerating 2m fine-scale urban tree cover product over 34 metropolises in China based on deep context-aware sub-pixel mapping network / Da He in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)PermalinkMapping abundance distributions of allergenic tree species in urbanized landscapes: A nation-wide study for Belgium using forest inventory and citizen science data / Sébastien Dujardin in Landscape and Urban Planning, vol 218 (February 2022)PermalinkRaw GIS to 3D road modeling for real-time traffic simulation / Yacine Amara in The Visual Computer, vol 38 n° 1 (January 2022)PermalinkRecurrent origin–destination network for exploration of human periodic collective dynamics / Xiaojian Chen in Transactions in GIS, vol 26 n° 1 (February 2022)PermalinkLes risques-réseaux : une matrice des défaillances des réseaux urbains interdépendants / Nabil Touili in Belgeo, vol 2022 n° 1 (2022)Permalink