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Evaluation of multipath mitigation performance using signal-to-noise ratio (SNR) based signal selection methods / Valanon Uaratanawong in Journal of applied geodesy, vol 15 n° 1 (January 2021)  

Public [article]  inJournal of applied geodesy > vol 15 n° 1 (January 2021) . - pp 75 - 85 Titre : Evaluation of multipath mitigation performance using signal-to-noise ratio (SNR) based signal selection methods Type de document : Article/Communication Auteurs : Valanon Uaratanawong, Auteur ; Chalermchon Satirapod, Auteur ; Toshiaki Tsujii, Auteur Année de publication : 2021 Article en page(s) : pp 75 - 85 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes descripteurs IGN] classification par nuées dynamiques [Termes descripteurs IGN] correction du trajet multiple [Termes descripteurs IGN] positionnement statique [Termes descripteurs IGN] précision du positionnement [Termes descripteurs IGN] qualité du signal [Termes descripteurs IGN] rapport signal sur bruit Résumé : (auteur) Satellite signal strength sometimes decreases when multipath exists. This effect reduces signal quality and can lead to a large static positioning error, even the survey-grade receivers are used. Three signal selection methods based on signal-to-noise ratio (SNR) measurements were proposed. The first was the conventional method, based on elevation-dependent average SNR, the second used a moving average of SNR fluctuation and the third method used NLOS exclusion based on SNR residual clustering by the K-means algorithm. To evaluate the positioning accuracy improvement, the static 1 Hz single-point positioning (SPP) test was performed in real-time in two different multipath environments using both dual and quad- constellation GNSS receivers. Trimble and CHC receivers were used at each point to examine the effect on each measurement. Results indicated that the three proposed methods mainly reduced multipath error in horizontal direction compared with the normal SPP. Numéro de notice : A2021-046 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2020-0045 date de publication en ligne : 09/12/2020 En ligne : https://doi.org/10.1515/jag-2020-0045 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96774 [article]

An overview of clustering methods for geo-referenced time series: from one-way clustering to co- and tri-clustering / Xiaojing Wu in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 9 (September 2020) . - pp 1822 - 1848 Titre : An overview of clustering methods for geo-referenced time series: from one-way clustering to co- and tri-clustering Type de document : Article/Communication Auteurs : Xiaojing Wu, Auteur ; Changxiu Cheng, Auteur ; Raul Zurita-Milla, Auteur Année de publication : 2020 Article en page(s) : pp 1822 - 1848 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] classification barycentrique [Termes descripteurs IGN] classification par nuées dynamiques [Termes descripteurs IGN] exploration de données [Termes descripteurs IGN] géoréférencement [Termes descripteurs IGN] modélisation spatio-temporelle [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] taxinomie Résumé : (auteur) Even though many studies have shown the usefulness of clustering for the exploration of spatio-temporal patterns, until now there is no systematic description of clustering methods for geo-referenced time series (GTS) classified as one-way clustering, co-clustering and tri-clustering methods. Moreover, the selection of a suitable clustering method for a given dataset and task remains to be a challenge. Therefore, we present an overview of existing clustering methods for GTS, using the aforementioned classification, and compare different methods to provide suggestions for the selection of appropriate methods. For this purpose, we define a taxonomy of clustering-related geographical questions and compare the clustering methods by using representative algorithms and a case study dataset. Our results indicate that tri-clustering methods are more powerful in exploring complex patterns at the cost of additional computational effort, whereas one-way clustering and co-clustering methods yield less complex patterns and require less running time. However, the selection of the most suitable method should depend on the data type, research questions, computational complexity, and the availability of the methods. Finally, the described classification can include novel clustering methods, thereby enabling the exploration of more complex spatio-temporal patterns. Numéro de notice : A2020-477 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1726922 date de publication en ligne : 16/02/2020 En ligne : https://doi.org/10.1080/13658816.2020.1726922 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95624 [article]

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Semi-automated framework for generating cycling lane centerlines on roads with roadside barriers from noisy MLS data / Yang Ma in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 167 (September 2020) . - pp 396 - 417 Titre : Semi-automated framework for generating cycling lane centerlines on roads with roadside barriers from noisy MLS data Type de document : Article/Communication Auteurs : Yang Ma, Auteur ; Yubing Zheng, Auteur ; Said Easa, Auteur ; Jianchuan Cheng, Auteur Année de publication : 2020 Article en page(s) : pp 396 - 417 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] axe médian [Termes descripteurs IGN] bicyclette [Termes descripteurs IGN] classification par nuées dynamiques [Termes descripteurs IGN] classification semi-dirigée [Termes descripteurs IGN] numérisation automatique [Termes descripteurs IGN] rastérisation [Termes descripteurs IGN] sécurité routière [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] télémétrie laser mobile [Termes descripteurs IGN] tracé routier Résumé : (auteur) Cycling lane centerlines (CLC) play an important role in the evaluation of safety-related conditions and guiding systems for cyclists along road corridors. The unavailability of design files or undocumented changes in the road infrastructures after improvements has created great difficulty in delineating CLC on existing roads. In this study, mobile laser scanning (MLS) data are introduced into this domain and a four-step semi-automated framework is proposed for generating CLC on roads with roadside barriers (RB). First, MLS data are restructured into the aligned scan-pattern grid using the mapping trajectory data. Second, a rasterization-based clustering approach is applied to segment the off-ground objects from the reorganized MLS data. Third, the RB amongst the segmented objects are identified using a sequential application of the k-Means clustering method and the proposed unidirectional growing method. Finally, the moving average technique and natural cubic spline are applied to generate CLC from the critical positions alongside the identified RB. Testing on three road sections with different types of RB demonstrated that the developed framework can successfully generate CLC from MLS data in the presence of considerable noises. The results also show that the proposed procedure shows better accuracy performance on processing roads with wide RB than a road with narrow RB. Numéro de notice : A2020-550 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.07.009 date de publication en ligne : 04/08/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.07.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95779 [article]

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An OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data / Xiaogang Guo in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 2 (February 2020) Titre : An OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data Type de document : Article/Communication Auteurs : Xiaogang Guo, Auteur ; Zhijie Xu, Auteur ; Jianqin Zhang, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] classification par nuées dynamiques [Termes descripteurs IGN] distance euclidienne [Termes descripteurs IGN] données de flux [Termes descripteurs IGN] données vectorielles [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] origine - destination [Termes descripteurs IGN] Pékin (Chine) [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] taxi [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] zone urbaine Résumé : (auteur) Origin-destination (OD) flow pattern mining is an important research method of urban dynamics, in which OD flow clustering analysis discovers the activity patterns of urban residents and mine the coupling relationship of urban subspace and dynamic causes. The existing flow clustering methods are limited by the spatial constraints of OD points, rely on the spatial similarity of geographical points, and lack in-depth analysis of high-dimensional flow characteristics, and therefore it is difficult to find irregular flow clusters. In this paper, we propose an OD flow clustering method based on vector constraints (ODFCVC), which defines OD flow event point and OD flow vector to express the spatial location relationship and geometric flow behavior characteristics of OD flow. First, the OD flow vector coordinate system is normalized by the Euclidean distance-based OD flow event point spatial clustering, and then the OD flow clusters with similar flow patterns are mined using adjusted cosine similarity-based OD flow vector feature clustering. The transformation of OD data from point set space to vector space is realized by constraining the vector coordinate system and vector similarity through two-step clustering, which simplifies the calculation of high-dimensional similarity of OD flow and helps mining representative OD flow clusters in flow space. Due to the OD flow cluster property, the k-means algorithm is selected as the basic clustering logic in the two-step clustering method, and a sum of squared error perceptually important points algorithm considering silhouette coefficients (SSEPIP) is adopted to automatically extract the optimal cluster number without defining any parameters. Tested by origin-destination flow data in Beijing, China, new traffic flow communities based on traffic hubs are obtained by using the ODFCVC method, and irregular traffic flow clusters (including cluster mode, divergence mode, and convergence mode) with representative travel trends are found. Numéro de notice : A2020-114 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9020128 date de publication en ligne : 22/02/2020 En ligne : https://doi.org/10.3390/ijgi9020128 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94720 [article]

Segmenting mangrove ecosystems drone images using SLIC superpixels / Edward Zimudzi in Geocarto international, vol 34 n° 14 ([30/10/2019])  

Public [article]  inGeocarto international > vol 34 n° 14 [30/10/2019] . - pp 1648 - 1662 Titre : Segmenting mangrove ecosystems drone images using SLIC superpixels Type de document : Article/Communication Auteurs : Edward Zimudzi, Auteur ; Ian Sanders, Auteur ; Nicholas Rollings, Auteur ; Christian Omlin, Auteur Année de publication : 2019 Article en page(s) : pp 1648 - 1662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] algorithme de superpixels [Termes descripteurs IGN] classification par nuées dynamiques [Termes descripteurs IGN] classification pixellaire [Termes descripteurs IGN] écosystème [Termes descripteurs IGN] Fidji [Termes descripteurs IGN] image captée par drone [Termes descripteurs IGN] mangrove [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] orthophotoplan numérique [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] SLIC algorithm Résumé : (auteur) Mangrove ecosystems play a very important ecological role on land–ocean interfaces in tropical regions. These ecosystems comprise of various tree species and aquatic animals, protecting the environment and providing a habitat that supports many living organisms including humans. The identification of image regions in mangrove ecosystems plays a significant role in ecosystem monitoring and conservation. Recent studies have suggested oversegmentation of colour images using superpixels as a solution to the segmentation of image regions. This study used the SLIC superpixel algorithm and k-means clustering to segment images taken from a camera mounted on a drone from a mangrove ecosystem in Fiji. The SLIC superpixel algorithm performed well to demarcate image regions with similar colour and texture information into patches and to use k-means for the segmentation of the whole image. These results lend support to the use of superpixel algorithms for the segmentation of mangrove ecosystems. Understanding how superpixels can be used for the segmentation of drone images will assist conservation efforts in mangrove ecosystems. Numéro de notice : A2019-539 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1497093 date de publication en ligne : 22/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1497093 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94114 [article]

An iterative method for obtaining a mean 3D axis from a set of GNSS traces for use in positional controls / A. Mozas-Calvache in Survey review, vol 49 n° 355 (October 2017)  

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Extracting urban functional regions from points of interest and human activities on location-based social networks / Song Gao in Transactions in GIS, vol 21 n° 3 (June 2017)  

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Contributions à la segmentation non supervisée d'images hyperspectrales : trois approches algébriques et géométriques / Saadallah El Asmar (2016)  

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Traitements numériques des images de télédétection, Vol. 3. Traitements appliqués à la photo-interprétation / Olivier de Joinville (2012)

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Traitement des données de télédétection / Michel-Claude Girard (2010)

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Consultation et classification d'échantillons cartographiques / Guillaume Ménégaux (2007)

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Traitement des données de télédétection / Michel-Claude Girard (2004)

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Cartogenèse numérique des types de sols et de leurs incertitudes par la combinaison de corrélations sur les facteurs environnementaux et des géostatistiques : application aux sols des environs de La Rochelle / F. Carre in Photo interprétation, vol 38 n° 3-4 (Septembre 2000)

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Color image processing and applications / K.N. Plataniotis (2000)

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Utilisation des données NOAA-AVHRR 1km pour la cartographie de l'occupation des sols sur le sud de la France / D. Arcos (1997)

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