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Hierarchical classification of pole‐like objects in mobile laser scanning point clouds / Rufei Liu in Photogrammetric record, vol 35 n° 169 (March 2020)  

Public [article]  inPhotogrammetric record > vol 35 n° 169 (March 2020) . - pp 81 - 107 Titre : Hierarchical classification of pole‐like objects in mobile laser scanning point clouds Type de document : Article/Communication Auteurs : Rufei Liu, Auteur ; Peng Wang, Auteur ; Zhaojin Yan, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 81 - 107 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse de la valeur [Termes descripteurs IGN] classification ascendante hiérarchique [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] lidar mobile [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] valeur propre Résumé : (Auteur) For the classification of pole‐like objects (trees, lamp posts, traffic lights and traffic signs) in mobile laser scanning (MLS) point clouds, a hierarchical classification method is proposed. The method consists of three major steps. (1) The objects’ cylindrical column sections are detected based on the characteristics of arc‐like points using RANSAC after denoising. (2) These detected objects are roughly classified into trees and man‐made poles based on the azimuthal coverage of point clouds above the cylindrical column. (3) Eigenvalue analysis and the principal direction of the upper pole projections are used to differentiate lamp posts, traffic lights and traffic signs. Experimental analysis shows that the method can effectively identify different types of pole‐like objects. Numéro de notice : A2020-133 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12307 date de publication en ligne : 10/01/2020 En ligne : https://doi.org/10.1111/phor.12307 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94819 [article]

The improvement in integer ambiguity resolution with INS aiding for kinematic precise point positioning / Xiaohong Zhang in Journal of geodesy, vol 93 n°7 (July 2019)  

Public [article]  inJournal of geodesy > vol 93 n°7 (July 2019) . - pp 993 - 1010 Titre : The improvement in integer ambiguity resolution with INS aiding for kinematic precise point positioning Type de document : Article/Communication Auteurs : Xiaohong Zhang, Auteur ; Feng Zhu, Auteur ; Yuxi Zhang, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 993 - 1010 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] affaiblissement de la précision [Termes descripteurs IGN] ambiguïté entière [Termes descripteurs IGN] délai d'obtention de la première position [Termes descripteurs IGN] GNSS-INS [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] positionnement ponctuel précis [Termes descripteurs IGN] précision du positionnement [Termes descripteurs IGN] résolution d'ambiguïté Résumé : (auteur) Despite the benefits of integer ambiguity resolution (IAR) in precise point positioning (PPP), observation outages and harsh signal environments still impact float ambiguity estimation in kinematic surveying, consequently resulting in ambiguity-fixed failure. The inertial navigation system (INS) is an autonomous and spontaneous positioning one, which could provide continuous and superior positioning accuracy over short time. Thus, the INS attains more accurate position than code solution. Moreover, the tight integration of INS and PPP is capable of continuous operation where there are less than four satellites available. These advantages can improve float ambiguity estimation and assist in re-initializing the interrupted ambiguity and PPP solution. Based on the good quality of float ambiguity, the ambiguity dilution precision (ADOP) and the size of integer ambiguity search space are reduced, and then, the IAR-PPP is improved. In this work, the INS aiding effect on IAR-PPP was revealed by the sufficient theoretical analysis and performance assessment. A ring laser gyroscope-based navigation-grade IMU and a fiber optic gyroscope-based tactical-grade IMU were utilized to conduct experiments in an open-sky environment and urban area. The assessment adopted the following aspects of ADOP, bootstrapping success rate, time to fix and position errors. It is found that IAR-PPP with INS aiding achieves an enhanced performance during GPS outage when INS could deliver a superior accurate position. For the navigation- and tactical-grade IMU, the INS-aided ambiguity re-fixing performance can be classified as three levels: significant improvement for the outage duration less than 10 s, moderate improvement for the outage duration from 10 to 60 s and a little or zero improvement for the outage duration longer than 60 s. From the viewpoint of the INS-predicted position domain, an accuracy better than 0.1 m and 1.0 m is required for the significant and moderate improvement, while one can only achieve a little or zero improvement if the position error is larger than 1.0 m. Besides, we also performed the INS-aided IAR-PPP in real urban environment. For the urban environments, the span of clean data is often shorter than 30 min due to intermittent signal interruptions; thus, ambiguity re-fixing for PPP always fails. INS-aided information could bridge the data gaps and achieve fast ambiguity re-fixing. In summary, INS aiding information is capable of improving IAR-PPP performance significantly over a short GPS outage. Numéro de notice : A2019-356 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1222-3 date de publication en ligne : 08/12/2018 En ligne : https://link.springer.com/article/10.1007/s00190-018-1222-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93424 [article]

Multilane roads extracted from the OpenStreetMap urban road network using random forests / Yongyang Xu in Transactions in GIS, vol 23 n° 2 (April 2019)  

Public [article]  inTransactions in GIS > vol 23 n° 2 (April 2019) . - pp 224 - 240 Titre : Multilane roads extracted from the OpenStreetMap urban road network using random forests Type de document : Article/Communication Auteurs : Yongyang Xu, Auteur ; Zhong Xie, Auteur ; Liang Wu, Auteur ; Zhanlong Chen, Auteur Année de publication : 2019 Article en page(s) : pp 224 - 240 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] extraction du réseau routier [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] Pékin (Chine) [Termes descripteurs IGN] réseau routier Résumé : (Auteur) The volunteered geographic information (VGI) collected in OpenStreetMap (OSM) has been used in many applications. Extracting multilane roads and establishing a high level of expressed detail play important roles in the field of automated cartographic generalization. An accurate and detailed extraction process benefits geographic analysis, urban region division, and road network construction, as well as transportation applications services. The road networks in OSM have a high level of detail and complex structures; however, they also include many duplicate lines, which degrade the efficiency and increase the difficulty of extracting multilane roads. To resolve these problems, this work proposes a machine‐learning‐based approach, in which the road networks are first converted from lines to polygons. Then, various geometric descriptors, including compactness, width, circularity, area, perimeter, complexity, parallelism, shape descriptor, and width‐to‐length ratio, are used to train a random forest (RF) classifier and identify the candidates. Finally, another RF is trained to evaluate the candidates using all the geometric descriptors and topological features; the outputs of this second trained RF are the predicted multilane roads. An experiment using OSM data from Beijing, China validated the proposed method, which achieves a highly effective performance when extracting multilane roads from OSM. Numéro de notice : A2019-250 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12514 date de publication en ligne : 26/12/2018 En ligne : https://doi.org/10.1111/tgis.12514 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93006 [article]

Land cover classification in combined elevation and optical images supported by OSM data, mixed-level features, and non-local optimization algorithms / Dimitri Bulatov in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 3 (March 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 3 (March 2019) . - pp 179 - 195 Titre : Land cover classification in combined elevation and optical images supported by OSM data, mixed-level features, and non-local optimization algorithms Type de document : Article/Communication Auteurs : Dimitri Bulatov, Auteur ; Gisela Häufel, Auteur ; Lucas Lucks, Auteur ; Melanie Pohl, Auteur Année de publication : 2019 Article en page(s) : pp 179 - 195 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] champ aléatoire de Markov [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] extraction automatique [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] orthoimage Résumé : (Auteur) Land cover classification from airborne data is considered a challenging task in Remote Sensing. Even in the case of available elevation data, shadows and strong intra-class variations of appearances are abundant in urban terrain. In this paper, we propose an approach for supervised land cover classification that has three main contributions. Firstly, for the cumbersome task of training data sampling we propose an algorithm which combines the freely available OpenStreetMap data with the actual sensor data and requires only a minimum of user interaction. The key idea of this algorithm is to rasterize the vector data using a fast segmentation result. Secondly, pixel-wise classification may take long and be quite sensitive to the resolution and quality of input data. Therefore, superpixel decomposition of images, supported by a general framework on operations with superpixels, guarantees fast grouping of pixel-wise features and their assignment to one of four important classes (building, tree, grass and road). Particularly for extraction of street canyons lying in the shadowy regions, high-level features based on stripes are introduced. Finally, the output of a probabilistic learning algorithm can be postprocessed by a non-local optimization module operating on Markov Random Fields, thus allowing to correct noisy results using a smoothness prior. Extensive tests on three datasets of quite different nature have been performed with two probabilistic learners: The well-known Random Forest and by far less known Import Vector Machine are explored. Thus, this work provides insights about promising feature sets for both classifiers. The quantitative results for the ISPRS benchmark dataset Vaihingen are promising, achieving up to 94.5% and 87.1% accuracy on superpixel and on pixel level, respectively, despite the fact that only around 10% of available labeled data were used. At the same time, the results for two additional datasets, validated with the autonomously acquired training data, yielded a significantly lower number of misclassified superpixels. This confirms that the proposed algorithm on training data extraction works quite well in reducing errors of second kind. However, it tends to extract predominantly huge and easy-to-classify areas, while in complicated, ambiguous regions, first type errors often occur. For this and other algorithm shortcomings, directions of future research are outlined. Numéro de notice : A2019-147 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.3.179 date de publication en ligne : 01/03/2019 En ligne : https://doi.org/10.14358/PERS.85.3.179 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92476 [article]

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Point clouds for direct pedestrian pathfinding in urban environments / Jesus Balado in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 148 (February 2019) . - pp 184 - 196 Titre : Point clouds for direct pedestrian pathfinding in urban environments Type de document : Article/Communication Auteurs : Jesus Balado, Auteur ; Lucia Diaz-Vilarino, Auteur ; Pedro Arias, Auteur ; Henrique Lorenzo, Auteur Année de publication : 2019 Article en page(s) : pp 184 - 196 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] accessibilité [Termes descripteurs IGN] chemin le plus court (algorithme) [Termes descripteurs IGN] détection de partie cachée [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] graphe [Termes descripteurs IGN] itinéraire piétionnier [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] navigation pédestre [Termes descripteurs IGN] objet mobile [Termes descripteurs IGN] objet statique [Termes descripteurs IGN] semis de points Mots-clés libres : espace urbain navigable pour piéton Résumé : (Auteur) Pathfinding applications for the citizen in urban environments are usually designed from the perspective of a driver, not being effective for pedestrians. In addition, urban scenes have multiple elements that interfere with pedestrian routes and navigable space. In this paper, a methodology for the direct use of point clouds for pathfinding in urban environments is presented, solving the main limitations for this purpose: (a) the excessive number of points is reduced for transformation into nodes on the final graph, (b) urban static elements acting as permanent obstacles, such as furniture and trees, are delimited and differentiated from dynamic elements such as pedestrians, (c) occlusions on ground elements are corrected to enable a complete graph modelling, and (d) navigable space is delimited from free unobstructed space according to two motor skills (pedestrians without reduced mobility and wheelchairs). The methodology is tested into three different streets sampled as point clouds by mobile laser scanning (MLS) systems: an intersection of several streets with ground composed of sidewalks at different heights; an avenue with wide sidewalks, trees and cars parked on one side; and a street with a single-lane road and narrow sidewalks. By applying Dijkstra pathfinding algorithm to the resulting graphs, the correct viability of the generated routes has been verified based on a visual analysis of the generated routes on the point cloud and on the knowledge of the urban study area. The methodology enables the automatic generation of graphs representing the navigable urban space, on which safe and real routes for different motor skills can be calculated. Numéro de notice : A2019-074 Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.004 date de publication en ligne : 15/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.004 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92161 [article]

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Use of LiDAR for calculating solar irradiance on roofs and façades of buildings at city scale: Methodology, validation, and analysis / Liang Cheng in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

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The bounds of distortion : truth, meaning and efficacy in digital geographic representation / Lucas Godfrey in International journal of cartography, vol 3 n° 1 (June 2017)  

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Urban 3D segmentation and modelling from street view images and LiDAR point clouds / Pouria Babahajiani in Machine Vision and Applications, sans n° ([01/06/2017])  

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