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Traffic signal detection from in-vehicle GPS speed profiles using functional data analysis and machine learning / Yann Méneroux in International Journal of Data Science and Analytics JDSA, vol inconnu ([01/10/2019])  

Public [article]  inInternational Journal of Data Science and Analytics JDSA > vol inconnu [01/10/2019] Titre : Traffic signal detection from in-vehicle GPS speed profiles using functional data analysis and machine learning Type de document : Article/Communication Auteurs : Yann Méneroux , Auteur ; Arnaud Le Guilcher , Auteur ; Guillaume Saint Pierre, Auteur ; Mohammad Ghasemi Hamed, Auteur ; Sébastien Mustière , Auteur ; O. Orfila, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] analyse fonctionnelle (mathématiques) [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] carte routière [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] contenu généré par les utilisateurs [Termes descripteurs IGN] détection d'objet [Termes descripteurs IGN] données routières [Termes descripteurs IGN] feu de circulation [Termes descripteurs IGN] inférence [Termes descripteurs IGN] reconnaissance de formes [Termes descripteurs IGN] signalisation routière [Termes descripteurs IGN] trace GPS [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] transformation en ondelettes [Termes descripteurs IGN] vitesse Résumé : (auteur) The increasing availability of large-scale global positioning system data stemming from in-vehicle-embedded terminal devices enables the design of methods deriving road network cartographic information from drivers’ recorded traces. Some machine learning approaches have been proposed in the past to train automatic road network map inference, and recently this approach has been successfully extended to infer road attributes as well, such as speed limitation or number of lanes. In this paper, we address the problem of detecting traffic signals from a set of vehicle speed profiles, under a classification perspective. Each data instance is a speed versus distance plot depicting over a hundred profiles on a 100-m-long road span. We proposed three different ways of deriving features: The first one relies on the raw speed measurements; the second one uses image recognition techniques; and the third one is based on functional data analysis. We input them into most commonly used classification algorithms, and a comparative analysis demonstrated that a functional description of speed profiles with wavelet transforms seems to outperform the other approaches with most of the tested classifiers. It also highlighted that random forests yield an accurate detection of traffic signals, regardless of the chosen feature extraction method, while keeping a remarkably low confusion rate with stop signs. Numéro de notice : A2019-497 Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s41060-019-00197-x date de publication en ligne : 04/10/2019 En ligne : https://doi.org/10.1007/s41060-019-00197-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93755 [article]

Geospatial data organization methods with emphasis on aperture-3 hexagonal discrete global grid systems / Ali Mahdavi Amiri in Cartographica, vol 54 n° 1 (spring 2019)  

Public [article]  inCartographica > vol 54 n° 1 (spring 2019) . - pp 30 - 50 Titre : Geospatial data organization methods with emphasis on aperture-3 hexagonal discrete global grid systems Type de document : Article/Communication Auteurs : Ali Mahdavi Amiri, Auteur ; Troy Alderson, Auteur ; Faramarz Samavati, Auteur Année de publication : 2019 Article en page(s) : pp 30 - 50 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] arbre de décision [Termes descripteurs IGN] données vectorielles [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] ondelette de Haar [Termes descripteurs IGN] régression [Termes descripteurs IGN] système de grille globale discrète [Termes descripteurs IGN] transformation en ondelettes Résumé : (Auteur) Digital Earth frameworks deal with data sets of different types collected from various sources. To effectively store, retrieve, and transmit these data sets, efficient multi-scale data representations that are compatible with the underlying structure of the Digital Earth framework are required. In this article, we describe several such techniques and their properties: namely, how to represent data in the multi-scale cell hierarchy of a discrete global grid system (DGGS) or in the multi-scale hierarchy of a customized wavelet transform. We also discuss how these techniques can be tuned to be applicable to the A3H DGGS. Numéro de notice : A2019-435 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart.54.1.2018-0010 En ligne : https://doi.org/10.3138/cart.54.1.2018-0010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92761 [article]

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A new waveform decomposition method for multispectral LiDAR / Shalei Song in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 149 (March 2019) . - pp 40 - 49 Titre : A new waveform decomposition method for multispectral LiDAR Type de document : Article/Communication Auteurs : Shalei Song, Auteur ; Binhui Wang, Auteur ; Wei Gong, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 40 - 49 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] couvert végétal [Termes descripteurs IGN] décomposition de Gauss [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] extraction de la végétation [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] forme d'onde pleine [Termes descripteurs IGN] transformation en ondelettes Résumé : (Auteur) Information derived from waveform decomposition of full-waveform light detection and ranging (LiDAR) data has been widely used in vegetation detection and three-dimensional urban terrain modeling to investigate and interpret the structural diversity of surface coverage. Most prevailing waveform decomposition methods involve only a single wavelength, but these methods do not apply to full-waveform multispectral LiDAR (FWMSL) systems that simultaneously acquire spectral and geometric information. In this paper, we propose a new multispectral waveform decomposition (MSWD) method in order to explore the potential advantages of the FWMSL system. Both simulated data and measured data from our FWMSL system were used to evaluate the performance of the proposed method. The coefficient of determination (R2), root mean square error (RMSE), and relative error (rRMSE) metrics suggest that the decomposition results derived from MSWD exhibit a comparable overall fitting accuracy as a single wavelength waveform decomposition (SWWD) method. We also propose a new evaluation indicator, relative neighbor distance error (RNDE), to represent the relative error in the distance between adjacent targets. The simulation results present clear superiority of MSWD over SWWD in terms of discovering weak or overlapping components and retrieving accurate waveform parameters. The experimental results demonstrated a considerable improvement in RNDE (0.0100–0.0610) over the prevailing SWWD method (0.0566–0.2833). Unlike SWWD, MSWD initializes waveform components using mutually complementary wavelengths thus delivering higher completeness and accuracy. MSWD can be extended to other FWMSL or full-waveform hyperspectral LiDAR systems with additional wavelengths. Numéro de notice : A2019-127 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.014 date de publication en ligne : 22/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.014 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92438 [article]

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Sea level estimation from SNR data of geodetic receivers using wavelet analysis / Xiaolei Wang in GPS solutions, vol 23 n° 1 (January 2019)  

Public [article]  inGPS solutions > vol 23 n° 1 (January 2019) Titre : Sea level estimation from SNR data of geodetic receivers using wavelet analysis Type de document : Article/Communication Auteurs : Xiaolei Wang, Auteur ; Qin Zhang, Auteur ; Shuangcheng Zhang, Auteur Année de publication : 2019 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] niveau de la mer [Termes descripteurs IGN] rapport signal sur bruit [Termes descripteurs IGN] récepteur GNSS [Termes descripteurs IGN] trajet multiple [Termes descripteurs IGN] transformation en ondelettes Résumé : (Auteur) Previous studies have proved that commercial, off-the-shelf, geodetic-quality Global Positioning System (GPS) receivers can monitor water level using multipath interferometric characteristics from the sea surface. A Lomb–Scargle periodogram (LSP) is typically used to extract the multipath frequency from the signal-to-noise ratio (SNR), which relates to the vertical distance between the antenna phase center and the reflecting surface, and subsequently, estimate sea levels. A wavelet transform can be used to analyze the time series with a nonstationary power at different frequencies, as can be the case for multipath signals. In addition, wavelet transform analysis estimates the local energy and instantaneous frequency of the signal at every epoch, which is beneficial for water-level estimation. Therefore, we attempt to extract the instantaneous multipath frequency using wavelet transform analysis for water leveling with a geodetic GPS receiver. This study analyzed SNR data of GPS L1C from three test sites: the Kachemak Bay site PBAY (AK, USA), the Friday Harbor site SC02 (WA, USA), and the Brest Harbor site BRST (France). These sites are located in different multipath environments, from a rural coastal area to a busy harbor, and they experience different tidal regimes. The results show that the wavelet analysis has potential for the retrieval of sea level heights. For measurement site PBAY the comparison of the results obtained by the wavelet and LSP analysis yield consistency within a few percent. At the other two sites, SC02 and BRST, the agreement is significantly lower. Numéro de notice : A2019-055 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-018-0798-7 date de publication en ligne : 01/11/2018 En ligne : https://doi.org/10.1007/s10291-018-0798-7 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92084 [article]

Least-squares cross-wavelet analysis and its applications in geophysical time series / Ebrahim Ghaderpour in Journal of geodesy, vol 92 n° 10 (October 2018)  

Public [article]  inJournal of geodesy > vol 92 n° 10 (October 2018) . - pp 1223 - 1236 Titre : Least-squares cross-wavelet analysis and its applications in geophysical time series Type de document : Article/Communication Auteurs : Ebrahim Ghaderpour, Auteur ; Elmas Sinem Ince, Auteur ; Spiros D. Pagiatakis, Auteur Année de publication : 2018 Article en page(s) : pp 1223 - 1236 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes descripteurs IGN] champ de pesanteur terrestre [Termes descripteurs IGN] données GOCE [Termes descripteurs IGN] données ITGB [Termes descripteurs IGN] gradient de gravitation [Termes descripteurs IGN] matrice de covariance [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] transformation en ondelettes Résumé : (Auteur) The least-squares wavelet analysis, an alternative to the classical wavelet analysis, was introduced in order to analyze unequally spaced and non-stationary time series exhibiting components with variable amplitude and frequency over time. There are a few methods such as cross-wavelet transform and wavelet coherence that can analyze two time series together. However, these methods cannot generally be used to analyze unequally spaced and non-stationary time series with associated covariance matrices that may have trends and/or datum shifts. A new method of analyzing two time series together, namely the least-squares cross-wavelet analysis, is developed and applied to study the disturbances in the gravitational gradients observed by GOCE satellite that arise from plasma flow in the ionosphere represented by Poynting flux. The proposed method also shows its outstanding performance on the Westford–Wettzell very long baseline interferometry baseline length and temperature series. Numéro de notice : A2018-462 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1156-9 date de publication en ligne : 26/05/2018 En ligne : https://doi.org/10.1007/s00190-018-1156-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91061 [article]

Spectral-spatial classification of hyperspectral images using wavelet transform and hidden Markov random fields / Elham Kordi Ghasrodashti in Geocarto international, vol 33 n° 8 (August 2018)  

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Exploring image fusion of ALOS/PALSAR data and LANDSAT data to differentiate forest area / Saygin Abdikan in Geocarto international, vol 33 n° 1 (January 2018)  

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A wavelet decomposition and polynomial fitting-based method for the estimation of time-varying residual motion error in airborne interferometric SAR / Hai Qiang Fu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)  

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WREP : A wavelet-based technique for extracting the red edge position from reflectance spectra for estimating leaf and canopy chlorophyll contents of cereal crops / Dong Li in ISPRS Journal of photogrammetry and remote sensing, vol 129 (July 2017)  

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Regression wavelet analysis for lossless coding of remote-sensing data / Naoufal Amrani in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)  

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A new method for specular and diffuse pseudorange multipath error extraction using wavelet analysis / Giovanni Pugliano in GPS solutions, vol 20 n° 3 (July 2016)  

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Characterization of ionospheric variability in TEC using EOF and wavelets over low-latitude GNSS stations / J.R.K. Kumar Dabbakuti in Advances in space research, vol 57 n° 12 (June 2016)  

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Data fusion technique using wavelet transform and Taguchi methods for automatic landslide detection from airborne laser scanning data and QuickBird satellite imagery / Biswajeet Pradhan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)  

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A robust digital watermarking algorithm for copyright protection of aerial photogrammetric images / Pai-Hui Hsu in Photogrammetric record, vol 31 n° 153 (March - May 2016)  

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Unsupervised segmentation of high-resolution remote sensing images based on classical models of the visual receptive field / Miaozhong Xu in Geocarto international, vol 30 n° 9 - 10 (October - November 2015)  

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