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Flood depth mapping in street photos with image processing and deep neural networks / Bahareh Alizadeh Kharazi in Computers, Environment and Urban Systems, vol 88 (July 2021)  

Public [article]  inComputers, Environment and Urban Systems > vol 88 (July 2021) . - n° 101628 Titre : Flood depth mapping in street photos with image processing and deep neural networks Type de document : Article/Communication Auteurs : Bahareh Alizadeh Kharazi, Auteur ; Amir H. Behzadan, Auteur Année de publication : 2021 Article en page(s) : n° 101628 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] Canada [Termes IGN] centre urbain [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] crue [Termes IGN] détection de contours [Termes IGN] Etats-Unis [Termes IGN] image Streetview [Termes IGN] inondation [Termes IGN] profondeur [Termes IGN] signalisation routière [Termes IGN] système d'aide à la décision [Termes IGN] traitement d'image [Termes IGN] transformation de Hough [Termes IGN] zone urbaine Résumé : (auteur) Many parts of the world experience severe episodes of flooding every year. In addition to the high cost of mitigation and damage to property, floods make roads impassable and hamper community evacuation, movement of goods and services, and rescue missions. Knowing the depth of floodwater is critical to the success of response and recovery operations that follow. However, flood mapping especially in urban areas using traditional methods such as remote sensing and digital elevation models (DEMs) yields large errors due to reshaped surface topography and microtopographic variations combined with vegetation bias. This paper presents a deep neural network approach to detect submerged stop signs in photos taken from flooded roads and intersections, coupled with Canny edge detection and probabilistic Hough transform to calculate pole length and estimate floodwater depth. Additionally, a tilt correction technique is implemented to address the problem of sideways tilt in visual analysis of submerged stop signs. An in-house dataset, named BluPix 2020.1 consisting of paired web-mined photos of submerged stop signs across 10 FEMA regions (for U.S. locations) and Canada is used to evaluate the models. Overall, pole length is estimated with an RMSE of 17.43 and 8.61 in. in pre- and post-flood photos, respectively, leading to a mean absolute error of 12.63 in. in floodwater depth estimation. Findings of this research are sought to equip jurisdictions, local governments, and citizens in flood-prone regions with a simple, reliable, and scalable solution that can provide (near-) real time estimation of floodwater depth in their surroundings. Numéro de notice : A2021-358 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101628 date de publication en ligne : 01/04/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101628 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97620 [article]

The point-descriptor-precedence representation for point configurations and movements / Amna Qayyum in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 7 (July 2021) . - pp 1374 - 1391 Titre : The point-descriptor-precedence representation for point configurations and movements Type de document : Article/Communication Auteurs : Amna Qayyum, Auteur ; Bernard De Baets, Auteur ; Muhammad Sulman Baig, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1374 - 1391 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] courbe [Termes IGN] détection d'événement [Termes IGN] données spatiotemporelles [Termes IGN] mesurage de distances [Termes IGN] objet mobile [Termes IGN] reconnaissance de formes [Termes IGN] relation topologique [Termes IGN] trafic routier [Termes IGN] véhicule automobile Résumé : (auteur) In this paper, we represent (moving) point configurations along a curved directed line qualitatively by means of a system of relational symbols based on two distance descriptors: one representing distance along the curved directed line and the other representing signed orthogonal distance to the curved directed line. The curved directed line represents the direction of the movement of interest. For instance, it could be straight as in the case of driving along a highway or could be curved as in the case of an intersection or a roundabout. Inspired by the Point Calculus, the order between the points on the curved directed line is described by means of a small set of binary relations () acting upon the distance descriptors. We call this representation the Point-Descriptor-Precedence-Static (PDPS) representation at a time point and Point-Descriptor-Precedence-Dynamic (PDPD) representation during a time interval. To illustrate how the proposed approach can be used to represent and analyse curved movements, some basic micro-analysis traffic examples are studied. Finally, we discuss some extensions of our work to highlight the practical benefits of PDP in identifying motion patterns that could be useful in GIS, autonomous vehicles, sports analytics, and gait analysis. Numéro de notice : A2021-453 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1864378 date de publication en ligne : 11/01/2021 En ligne : https://doi.org/10.1080/13658816.2020.1864378 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97882 [article]

Automated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours / Amir Hossein Safaie in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 174 (April 2021) . - pp 19 - 34 Titre : Automated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours Type de document : Article/Communication Auteurs : Amir Hossein Safaie, Auteur ; Heidar Rastiveis, Auteur ; Alireza Shams, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 19 - 34 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre remarquable [Termes IGN] arbre urbain [Termes IGN] détection d'arbres [Termes IGN] détection de contours [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] sécurité routière [Termes IGN] semis de points [Termes IGN] tessellation [Termes IGN] transformation de Hough Résumé : (auteur) Trees are important road-side objects, and their geometric information plays an essential role in road studies and safety analyses. This paper proposes an efficient method for the automated creation of a road-side tree inventory using Mobile Terrestrial Lidar System (MTLS) point clouds. In the proposed method ground points are filtered through preprocessing to reduce processing time. Next, tree trunks are detected by performing a Hough Transform (HT) algorithm on several generated raster images from the point clouds. By initiating an approximate area of a tree’s foliage through a Voronoi Tessellation (VT) algorithm, the accurate boundary of the foliage is identified by applying Active Contour (AC) models. By extracting the points within this foliage boundary the geometric characteristics of each tree are obtained. This method was evaluated with two sample point clouds from different MTLS systems, and the algorithm correctly extracted all of the trees from both datasets. Additionally, comparing the calculated parameters with manually observed measures, the accuracy of the obtained geometric parameters were promising. Numéro de notice : A2021-206 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.026 date de publication en ligne : 14/02/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.026 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97183 [article]

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A trajectory restoration algorithm for low-sampling-rate floating car data and complex urban road networks / Bozhao Li in International journal of geographical information science IJGIS, vol 35 n° 4 (April 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 4 (April 2021) . - pp 717 - 740 Titre : A trajectory restoration algorithm for low-sampling-rate floating car data and complex urban road networks Type de document : Article/Communication Auteurs : Bozhao Li, Auteur ; Zhongliang Cai, Auteur ; Mengjun Kang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 717 - 740 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] appariement de cartes [Termes IGN] chemin le plus court (algorithme) [Termes IGN] Pékin (Chine) [Termes IGN] réseau routier [Termes IGN] taux d'échantillonnage [Termes IGN] trafic routier [Termes IGN] trajectoire [Termes IGN] zone urbaine Résumé : (auteur) Low-sampling-rate floating car data (FCD) are more challenging than those with high-sampling-rate FCD for map matching (MM) algorithms. Some MM algorithms for low-sampling-rate FCD lack sufficient efficiency nor accuracy, especially related to complex urban road networks. This paper proposes a new method named the trajectory restoration algorithm, which is based on geometry MM algorithms to ensure efficiency and accuracy. The proposed algorithm adopts the modified A* shortest path algorithm to reduce the number of function calls and fully considers road network topology and historical matched points to improve its accuracy. We test the efficiency and accuracy of the trajectory restoration algorithm with FCD data for the complex urban road networks in Beijing. The results have strong continuity which greatly improves the utilization of FCD. We show that the proposed algorithm outperforms related MM methods in efficiency and accuracy and its robustness to restore trajectories of both high and low sampling rates in complex urban road networks. Numéro de notice : A2021-269 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2020.1825721 date de publication en ligne : 20/10/2020 En ligne : https://doi.org/10.1080/13658816.2020.1825721 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97326 [article]

Evaluating the effectiveness of different cartographic design variants for influencing route choice / Stefan Fuest in Cartography and Geographic Information Science, vol 48 n° 2 (March 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 2 (March 2021) . - pp 169 - 185 Titre : Evaluating the effectiveness of different cartographic design variants for influencing route choice Type de document : Article/Communication Auteurs : Stefan Fuest, Auteur ; Susanne Grüner, Auteur ; Mark Vollrath, Auteur ; Monika Sester, Auteur Année de publication : 2021 Article en page(s) : pp 169 - 185 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique [Termes IGN] comportement [Termes IGN] conception cartographique [Termes IGN] convivialité [Termes IGN] itinéraire [Termes IGN] représentation des détails topographiques [Termes IGN] symbole graphique [Termes IGN] trafic routier [Termes IGN] visualisation cartographique Résumé : (Auteur) This paper addresses the suitability of different cartographic design variants for visually communicating recommended routes. We performed a user study, investigating the potential of six different design variants (color hue, distortion, length distortion, size, spacing, and symbols) for influencing route choice using cartographic visualization methods while recommending a longer, but less congested route. The visualizations for all design variants have been prepared in three different levels of intensity of modification (weak, medium, and strong). Although the input data (traffic density) is the same for all representation methods, variations are each visualized using different cartographic design principles. Our results showed that in general, for the majority of routing scenarios, the participants’ route choice has been significantly influenced toward choosing the recommended route – indicating that the modification of route visualizations does actually lead to a different route choice behavior. Results further revealed that for most variants, willingness to choose the recommended route increases with higher intensity of modification. While some of the design variants like symbols or length distortion have been found effective for recommending routes at all levels of intensity, others like size and spacing have not been found suitable. A comparison between route choices and estimated route characteristics suggested a close relationship between willingness to choose the recommended route and the characteristics participants associate with the representation. In particular, route visualizations that create an impression of faster, more convenient, or more fluent travel experience are more likely to influence route choice behavior. Numéro de notice : A2021-181 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1855251 date de publication en ligne : 06/01/2021 En ligne : https://doi.org/10.1080/15230406.2020.1855251 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97068 [article]

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Deep traffic light detection by overlaying synthetic context on arbitrary natural images / Jean Pablo Vieira de Mello in Computers and graphics, vol 94 n° 1 (February 2021)  

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Improving traffic sign recognition results in urban areas by overcoming the impact of scale and rotation / R. Yazdan in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

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Inferencing hourly traffic volume using data-driven machine learning and graph theory / Zhiyan Yi in Computers, Environment and Urban Systems, vol 85 (January 2021)  

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Route intersection reduction with connected autonomous vehicles / Sadegh Motallebi in Geoinformatica [en ligne], vol 25 n° 1 (January 2021)  

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Empirical assessment of road network resilience in natural hazards using crowdsourced traffic data / Yi Qiang in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)  

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Using multi-agent simulation to predict natural crossing points for pedestrians and choose locations for mid-block crosswalks / Egor Smirrnov in Geo-spatial Information Science, vol 23 n° 4 (December 2020)  

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Unfolding spatial-temporal patterns of taxi trip based on an improved network kernel density estimation / Boxi Shen in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)  

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A graph convolutional network model for evaluating potential congestion spots based on local urban built environments / Kun Qin in Transactions in GIS, Vol 24 n° 5 (October 2020)  

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Machine‐learning prediction models for pedestrian traffic flow levels: Towards optimizing walking routes for blind pedestrians / Achituv Cohen in Transactions in GIS, Vol 24 n° 5 (October 2020)  

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Network-constrained bivariate clustering method for detecting urban black holes and volcanoes / Qiliang Liu in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)  

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