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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]

A framework for classification of volunteered geographic data based on user’s need / Nazila Mohammadi in Geocarto international, vol 36 n° 11 ([01/07/2021])  

Public [article]  inGeocarto international > vol 36 n° 11 [01/07/2021] . - pp 1276 - 1291 Titre : A framework for classification of volunteered geographic data based on user’s need Type de document : Article/Communication Auteurs : Nazila Mohammadi, Auteur ; Amin Sedaghat, Auteur Année de publication : 2021 Article en page(s) : pp 1276 - 1291 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] analyse en composantes principales [Termes IGN] approche participative [Termes IGN] classification par réseau neuronal [Termes IGN] données localisées des bénévoles [Termes IGN] indicateur de qualité [Termes IGN] OpenStreetMap [Termes IGN] Perceptron multicouche [Termes IGN] qualité des données [Termes IGN] zone urbaine Résumé : (auteur) VGI is an attractive source of data, but the quality assurance limits its usages. This study proposes a framework to estimate the quality of the VGI and to classify them based on the user’s need. For this purpose, a set of properties is defined to describe the data in various aspects. The principal component analysis (PCA) method is applied to reach a new set of uncorrelated indicators (UI). Volunteered data is classified based on the user’s need and takes a quality index (QI). UI and QI values are used to train the ANN. Finally, the trained ANN determines the output of the network in a way that returns QI using the UI as inputs. The proposed method was applied to estimate the quality classes of VGI in a part of an urban area. According to the results of the confusion matrix, the total accuracy of the proposed framework was 81.6%. Numéro de notice : A2021-436 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1641562 date de publication en ligne : 16/07/2019 En ligne : https://doi.org/10.1080/10106049.2019.1641562 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97806 [article]

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, V-4-2021 (July 2021)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > V-4-2021 (July 2021) . - pp 61 - 68 Titre : A framework to manage uncertainty in the computation of waste collection routes after a flood Type de document : Article/Communication Auteurs : Arnaud Le Guilcher , Auteur ; Sofiane Martel, Auteur ; Mickaël Brasebin , Auteur ; Yann Méneroux, Auteur Année de publication : 2021 Article en page(s) : pp 61 - 68 Note générale : biblographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] cadre conceptuel [Termes IGN] calcul d'itinéraire [Termes IGN] catastrophe naturelle [Termes IGN] collecte des déchets [Termes IGN] discrétisation spatiale [Termes IGN] incertitude géométrique [Termes IGN] inondation [Termes IGN] programmation stochastique [Termes IGN] variable aléatoire Résumé : (auteur) In this paper, we describe a framework to find a good quality waste collection tour after a flood, without having to solve a complicated optimization problem from scratch in limited time. We model the computation of a waste collection tour as a capacitated routing problem, on the vertices or on the edges of a graph, with uncertain waste quantities and uncertain road availability. Multiple models have been conceived to manage uncertainty in routing problems, and we build on the ideas of discretizing the uncertain parameters and computing master solutions that can be adapted to propose an original method to compute efficient solutions. We first introduce our model for the progressive removal of the uncertainty, then outline our method to compute solutions: our method first considers a low-dimensional set of random variables that govern the behaviour of the problem parameters, discretizes these variables and computes a solution for each discrete point before the flood, and then uses these solutions as a basis to build operational solutions when there are enough information about the parameters of the routing problem. We then give computational tools to implement this method. We give a framework to compute the basis of solutions in an efficient way, by computing all the solutions simultaneously and sharing information (that can lead to good quality solutions) between the different problems based on how close their parameters are, and we also describe how real solutions can be derived from this basis. Our main contributions are our model for the progressive removal of uncertainty, our multi-step method to compute efficient solutions, and our intrusive framework to compute solutions on the discrete grid of parameters. Numéro de notice : A2021-316 Affiliation des auteurs : UGE-LaSTIG (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-4-2021-61-2021 En ligne : https://doi.org/10.5194/isprs-annals-V-4-2021-61-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97946 [article]

Roadside tree extraction and diameter estimation with mms lidar by using point-cloud image / Genki Takahashi in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2021 (July 2021)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > V-2-2021 (July 2021) . - pp 67 - 74 Titre : Roadside tree extraction and diameter estimation with mms lidar by using point-cloud image Type de document : Article/Communication Auteurs : Genki Takahashi, Auteur ; H. Masuda, Auteur Année de publication : 2021 Article en page(s) : pp 67 - 74 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] alignement d'arbres [Termes IGN] apprentissage automatique [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction d'arbres [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] route [Termes IGN] Tokyo (Japon) [Termes IGN] zone urbaine Résumé : (auteur) Efficient management of roadside trees for local governments is important. Mobile Mapping System (MMS) equipped with a high-density LiDAR scanner has the possibility to be applied to estimate DBH of roadside trees using point clouds. In this study, we propose a method for detecting roadside trees and estimating their DBHs automatically from MMS point clouds. In our method, point clouds captured using the MMS are mapped on a 2D image plane, and they are converted into a wireframe model by connecting adjacent points. Then, geometric features are calculated for each point in the wireframe model. Tree points are detected using a machine learning technique. The DBH of each tree is calculated using vertically aligned circles extracted from the wireframe model. Our method allows robustly calculating the DBH even if there is a hump at breast height. We evaluated our method using actual MMS data measured in an urban area in Tokyo. Our method achieved a high extraction performance of 100 percent of precision and 95.1 percent of recall for 102 roadside trees. The average accuracy of the DBH was 2.0 cm. These results indicate that our method is useful for the efficient management of roadside trees. Numéro de notice : A2021-491 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2021-67-2021 date de publication en ligne : 17/06/2021 En ligne : http://dx.doi.org/10.5194/isprs-annals-V-2-2021-67-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97956 [article]

Multi-GNSS PPP/INS tightly coupled integration with atmospheric augmentation and its application in urban vehicle navigation / Shengfeng Gu in Journal of geodesy, vol 95 n° 6 (June 2021)  

Public [article]  inJournal of geodesy > vol 95 n° 6 (June 2021) . - n° 64 Titre : Multi-GNSS PPP/INS tightly coupled integration with atmospheric augmentation and its application in urban vehicle navigation Type de document : Article/Communication Auteurs : Shengfeng Gu, Auteur ; Chunqi Dai, Auteur ; Wentao Fang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 64 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] centrale inertielle [Termes IGN] correction atmosphérique [Termes IGN] couplage GNSS-INS [Termes IGN] milieu urbain [Termes IGN] navigation automobile [Termes IGN] positionnement ponctuel précis [Termes IGN] retard ionosphèrique [Termes IGN] teneur verticale totale en électrons [Termes IGN] Wuhan (Chine) Résumé : (auteur) Precise point positioning (PPP) is receiving increasing interest due to its cost-effectiveness, global coverage and high accuracy. However, its application in the urban environment is still full of challenges due to the satellite tracking sky-view. Thus, we presented a comprehensive positioning model by fusing the multi-GNSS (global navigation satellite system) combination, GNSS/INS (inertial navigation system) tightly coupled integration as well as the ionospheric and tropospheric augmentation in the undifferenced and uncombined PPP. The performance of this model in dual-frequency and single-frequency positioning was assessed with two experiments that denoted as T019 and T023, respectively, and both the experiments were carried out in a real urban environment. Particularly, the experiment T023 was carried out in the Second Ring Road of Wuhan city, which can be regarded as a typical downtown environment. Concerning the regional atmospheric augmentation, observations from 5 reference stations with an inter-station distance of about 40 km were also collected during the experimental time. The comparison between reference stations suggested that the regional tropospheric model had a precision of better than 0.6 cm in terms of zenith tropospheric delay, while the regional ionospheric model had a precision of around 0.5 total electron content unit in terms of Vertical Total Electron Content. It can be concluded that the GPS-only PPP can be improved significantly for urban vehicle navigation with these techniques, i.e., the multi-GNSS, INS tightly coupled integration and the atmospheric augmentation, through the positioning analysis, while INS tightly coupled integration makes the most contributions under the downtown environment, and the improvement of the regional atmospheric augmentation in single-frequency PPP is more significant since that single frequency is more sensitive to the ionospheric delay. In addition, it is proved that the regional atmospheric augmentation accelerates positioning convergence. The 3D positioning root-mean-square (RMS) with the comprehensive positioning model for dual frequency are 0.22 m and 0.77 m for T019 and T023, respectively. Concerning single-frequency PPP, the 3D RMS is 0.45 m and 1.17 m for T019 and T023, respectively. Moreover, taking the lane-level navigation under the downtown environment of T023 into consideration, we further presented the cumulative frequency of the horizontal positioning error less than 1 m, i.e., P(dN2+dE2−−−−−−−−−√ Numéro de notice : A2021-429 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01514-8 date de publication en ligne : 26/05/2021 En ligne : https://doi.org/10.1007/s00190-021-01514-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97789 [article]

An area merging method in map generalization considering typical characteristics of structured geographic objects / Chengming Li in Cartography and Geographic Information Science, vol 48 n° 3 (May 2021)  

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Constructing and analyzing spatial-social networks from location-based social media data / Xuebin Wei in Cartography and Geographic Information Science, vol 48 n° 3 (May 2021)  

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Crowdsourcing of popular toponyms: How to collect and preserve toponyms in spoken use / Daniel Vrbik in ISPRS International journal of geo-information, vol 10 n° 5 (May 2021)  

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Delineation of cities based on scaling properties of urban patterns: a comparison of three methods / Gaëtan Montero in International journal of geographical information science IJGIS, vol 35 n° 5 (May 2021)  

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Identifying urban neighborhoods with higher potential for social investment using GIS-FIS approach / Hossein Aghajani in Applied geomatics, vol 13 n° 1 (May 2021)  

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Integrating a forward feature selection algorithm, random forest, and cellular automata to extrapolate urban growth in the Tehran-Karaj region of Iran / Hossein Shafizadeh-Moghadam in Computers, Environment and Urban Systems, vol 87 (May 2021)  

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Numerical modelling for analysis of the effect of different urban green spaces on urban heat load patterns in the present and in the future / Tamás Gál in Computers, Environment and Urban Systems, vol 87 (May 2021)  

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Quality assessment of heterogeneous training data sets for classification of urban area with Landsat imagery / Neema Nicodemus Lyimo in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 5 (May 2021)  

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Restituer les bidonvilles de Nanterre : l’apport d’un outil de visualisation 3D à un projet de sciences sociales / Paul Lecat in Humanités numériques, n° 3 (2021)  

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Decision-level and feature-level integration of remote sensing and geospatial big data for urban land use mapping / Jiadi Yin in Remote sensing, vol 13 n° 8 (April-2 2021)  

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