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Accounting for spatiotemporal correlations of GNSS coordinate time series to estimate station velocities / Clément Benoist in Journal of geodynamics, vol 135 (April 2020)
[article]
Titre : Accounting for spatiotemporal correlations of GNSS coordinate time series to estimate station velocities Type de document : Article/Communication Auteurs : Clément Benoist , Auteur ; Xavier Collilieux , Auteur ; Paul Rebischung , Auteur ; Zuheir Altamimi , Auteur ; Olivier Jamet , Auteur ; Laurent Métivier , Auteur ; Kristel Chanard , Auteur ; Liliane Bel, Auteur Année de publication : 2020 Projets : GEODESIE / Coulot, David, Université de Paris / Clerici, Christine Article en page(s) : n° 101693 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] corrélation
[Termes IGN] covariance
[Termes IGN] données spatiotemporelles
[Termes IGN] repère de référence terrestre conventionnel
[Termes IGN] série temporelle
[Termes IGN] vitesseRésumé : (auteur) It is well known that GNSS permanent station coordinate time series exhibit time-correlated noise. Spatial correlations between coordinate time series of nearby stations are also long-established and generally handled by means of spatial filtering techniques. Accounting for both the temporal and spatial correlations of the noise via a spatiotemporal covariance model is however not yet a common practice. We demonstrate in this paper the interest of using such a spatiotemporal covariance model of the stochastic variations in GNSS time series in order to estimate long-term station coordinates and especially velocities.
We provide a methodology to rigorously assess the covariances between horizontal coordinate variations and use it to derive a simple exponential spatiotemporal covariance model for the stochastic variations in the IGS repro2 station coordinate time series. We then use this model to estimate station velocities for two selected datasets of 10 time series in Europe and 11 time series in the USA. We show that coordinate prediction as well as velocity determination from short time series are improved when using this spatiotemporal model, as compared with the case where spatiotemporal correlations are ignored.Numéro de notice : A2020-460 Affiliation des auteurs : Géodésie+Ext (mi2018-2019) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jog.2020.101693 Date de publication en ligne : 13/01/2020 En ligne : https://doi.org/10.1016/j.jog.2020.101693 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95385
in Journal of geodynamics > vol 135 (April 2020) . - n° 101693[article]Comparative analysis of different atmospheric surface pressure models and their impacts on daily ITRF2014 GNSS residual time series / Zhao Li in Journal of geodesy, vol 94 n°4 (April 2020)
[article]
Titre : Comparative analysis of different atmospheric surface pressure models and their impacts on daily ITRF2014 GNSS residual time series Type de document : Article/Communication Auteurs : Zhao Li, Auteur ; Chen Wu, Auteur ; Tonie M. van Dam, Auteur ; Paul Rebischung , Auteur ; Zuheir Altamimi , Auteur Année de publication : 2020 Projets : 3-projet - voir note / Clerici, Christine Article en page(s) : n° 42 Note générale : bibliographie
This research is supported by the National Key Research and Development Program of China (Project 2016YFB0502101), the European Commission/Research Grants Council (RGC) Collaboration Scheme sponsored by the Research Grants Council of Hong Kong Special Administrative Region, China (Project No. E-PolyU 501/16), and the National Science Foundation for Distinguished Young Scholars of China (Grant No. 41525014).Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] analyse comparative
[Termes IGN] coefficient de corrélation
[Termes IGN] données GNSS
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] MERRA
[Termes IGN] modèle atmosphérique
[Termes IGN] pression atmosphérique
[Termes IGN] radar JPL
[Termes IGN] résidu
[Termes IGN] série temporelle
[Termes IGN] station GNSSRésumé : (auteur) To remove atmospheric pressure loading (ATML) effect from GNSS coordinate time series, surface pressure (SP) models are required to predict the displacements. In this paper, we modeled the 3D ATML surface displacements using the latest MERRA-2 SP grids, together with four other products (NCEP-R-1, NCEP-R-2, ERA-Interim and MERRA) for 596 globally distributed GNSS stations, and compared them with ITRF2014 residual time series. The five sets of ATML displacements are highly consistent with each other, particularly for those stations far away from coasts, of which the lowest correlations in the Up component for all the four models w.r.t MERRA-2 become larger than 0.91. ERA-Interim-derived ATML displacement performs best in reducing scatter of the GNSS height for 90.3% of the stations (89.3% for NCEP-R-1, 89.1% for NCEP-R-2, 86.4% for MERRA and 85.1% for MERRA-2). We think that this may be possibly due to the 4D variational data assimilation method applied. Considering inland stations only, more than 96% exhibit WRMS reduction in the Up direction for all five models, with an average improvement of 3–4% compared with the original ITRF2014 residual time series before ATML correction. Most stations (> 67%) also exhibit horizontal WRMS reductions based on the five models, but of small magnitudes, with most improvements (> 76%) less than 5%. In particular, most stations in South America, South Africa, Oceania and the Southern Oceans show larger WRMS reductions with MERRA-2, while all other four SP datasets lead to larger WRMS reduction for the Up component than MERRA-2 in Europe. Through comparison of the daily pressure variation from the five SP models, we conclude that the bigger model differences in the SP-induced surface displacements and their impacts on the ITRF2014 residuals for coastal/island stations are mainly due to the IB correction based on the different land–sea masks. A unique high spatial resolution land–sea mask should be applied in the future, so that model differences would come from only SP grids. Further research is also required to compare the ATML effect in ice-covered and high mountainous regions, for example the Qinghai–Tibet Plateau in China, the Andes in South America, etc., where larger pressure differences between models tend to occur. Numéro de notice : A2020-159 Affiliation des auteurs : Géodésie+Ext (mi2018-2019) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01370-y Date de publication en ligne : 20/03/2020 En ligne : https://doi.org/10.1007/s00190-020-01370-y Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94813
in Journal of geodesy > vol 94 n°4 (April 2020) . - n° 42[article]Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China / Mingyue Wang in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)
[article]
Titre : Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China Type de document : Article/Communication Auteurs : Mingyue Wang, Auteur ; Jun’e Fu, Auteur ; Zhitao Wu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] coefficient de corrélation
[Termes IGN] données météorologiques
[Termes IGN] données spatiotemporelles
[Termes IGN] écosystème
[Termes IGN] Fleuve jaune (Chine)
[Termes IGN] image Aqua-MODIS
[Termes IGN] image SPOT
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle de simulation
[Termes IGN] modèle dynamique
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] précipitation
[Termes IGN] série temporelle
[Termes IGN] température
[Termes IGN] variation saisonnièreRésumé : (auteur) Research on vegetation variation is an important aspect of global warming studies. The quantification of the relationship between vegetation change and climate change has become a central topic and challenge in current global change studies. The source region of the Yellow River (SRYR) is an appropriate area to study global change because of its unique natural conditions and vulnerable terrestrial ecosystem. Therefore, we chose the SRYR for a case study to determine the driving forces behind vegetation variation under global warming. Using the Normalized Difference Vegetation Index (NDVI) and climate data, we investigated the NDVI variation in the growing season in the region from 1998 to 2016 and its response to climate change based on trend analysis, the Mann–Kendall trend test and partial correlation analysis. Finally, an NDVI–climate mathematical model was built to predict the NDVI trends from 2020 to 2038. The results indicated the following: (1) over the past 19 years, the NDVI showed an increasing trend, with a growth rate of 0.00204/a. There was an upward trend in NDVI over 71.40% of the region. (2) Both the precipitation and temperature in the growing season showed upward trends over the last 19 years. NDVI was positively correlated with precipitation and temperature. The areas with significant relationships with precipitation covered 31.01% of the region, while those with significant relationships with temperature covered 56.40%. The sensitivity of the NDVI to temperature was higher than that to precipitation. Over half (56.58%) of the areas were found to exhibit negative impacts of human activities on the NDVI. (3) According to the simulation, the NDVI will increase slightly over the next 19 years, with a linear tendency of 0.00096/a. From the perspective of spatiotemporal changes, we combined the past and future variations in vegetation, which could adequately reflect the long-term vegetation trends. The results provide a theoretical basis and reference for the sustainable development of the natural environment and a response to vegetation change under the background of climate change in the study area. Numéro de notice : A2020-262 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040282 Date de publication en ligne : 24/04/2020 En ligne : https://doi.org/10.3390/ijgi9040282 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95022
in ISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 17 p.[article]Techniques for efficient detection of rapid weather changes and analysis of their impacts on a highway network / Adil Alim in Geoinformatica, vol 24 n° 2 (April 2020)
[article]
Titre : Techniques for efficient detection of rapid weather changes and analysis of their impacts on a highway network Type de document : Article/Communication Auteurs : Adil Alim, Auteur ; Aparna Joshi, Auteur ; Feng Chen, Auteur ; Catherine T. Lawson, Auteur Année de publication : 2020 Article en page(s) : pp 269 – 299 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] corrélation
[Termes IGN] détection d'événement
[Termes IGN] détection de changement
[Termes IGN] données spatiotemporelles
[Termes IGN] entretien du réseau
[Termes IGN] hiver
[Termes IGN] météorologie
[Termes IGN] prévision météorologique
[Termes IGN] réseau routier
[Termes IGN] sécurité routière
[Termes IGN] trafic routierRésumé : (auteur) Adverse weather conditions have a significant impact on the safety, mobility, and efficiency of highway networks. Weather contributed to 23 percent of all non-reoccurring delay and approximately 544 million vehicle hours of delay each year (2014). Nearly 2.3 billion dollars each year are spent by transportation agencies for winter maintenance that contribute to close to 20 percent of most DOT’s yearly budgets (2014). These safety and mobility factors make it important to develop new and more effective methods to address road conditions during adverse weather conditions. Given weather and traffic sensors installed along side of the highway networks, how can we automatically detect weather and traffic change events and prevent from the traffic delay or harsh weather accidents? To this end, we propose a novel framework to address this problem. This paper develops techniques for efficiently detecting rapid weather change events and analyzing their impacts on the traffic flow characteristics of a highway network. It is composed of three components, including 1) detection of rapid weather change events in a highway network using the streaming weather information from a sensor network of weather stations; 2) detection of rapid traffic change events on the traffic flow characteristics (e.g., travel time) of the highway network; and 3) analysis of correlations between the detected weather and traffic change events in space and time. The proposed approach was applied to a weather dataset provided by New York State Mesonet and a traffic flow dataset the National Performance Management Research Data Set (NPMRDS) provided by NYSDOT. The empirical results provide potential evidence about the significant impacts of rapid weather change events on traffic flow characteristics of the Interstate 90 (I-90) Highway in the state of New York. We show the quantitative performance evaluation of our change event detection algorithm and three baseline methods on manually labeled the weather dataset and our method outperforms baselines in terms of precision, recall and F-score. We present the analysis of Top K detected change events as case studies and also provide the spatio-temporal correlation statistics of top k weather and traffic change events. The limitations of the proposed approach and the empirical study are also discussed. Numéro de notice : A2020-358 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00395-x Date de publication en ligne : 12/02/2020 En ligne : https://doi.org/10.1007/s10707-020-00395-x Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95263
in Geoinformatica > vol 24 n° 2 (April 2020) . - pp 269 – 299[article]Multi-spectral image change detection based on single-band iterative weighting and fuzzy C-means clustering / Liyuan Ma in European journal of remote sensing, vol 53 n° 1 (2020)
[article]
Titre : Multi-spectral image change detection based on single-band iterative weighting and fuzzy C-means clustering Type de document : Article/Communication Auteurs : Liyuan Ma, Auteur ; Jia Zhenhong, Auteur ; Jie Yang, Auteur ; Nikola Kasabov, Auteur Année de publication : 2020 Article en page(s) : pp 1 -13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] bruit blanc
[Termes IGN] classification floue
[Termes IGN] classification non dirigée
[Termes IGN] coefficient de corrélation
[Termes IGN] détection de changement
[Termes IGN] distance euclidienne
[Termes IGN] image multibande
[Termes IGN] itération
[Termes IGN] masque
[Termes IGN] pondérationRésumé : (auteur) In the present study, an improved iteratively reweighted multivariate alteration detection (IR-MAD) algorithm was proposed to improve the contribution of weakly correlated bands in multi-spectral image change detection. In the proposed algorithm, each image band was given a different weight through single-band iterative weighting, improving the correlation between each pair of bands. This method was used to obtain the characteristic difference in the diagrams of the band that contain more variation information. After removing Gaussian noise from each feature-difference graph, the difference graphs of each band were fused into a change-intensity graph using the Euclidean distance formula. Finally, unsupervised fuzzy C-means (FCM) clustering was used to perform binary clustering on the fused difference graphs to obtain the change detection results. By comparing the original multivariate alteration detection (MAD) algorithm, the IR-MAD algorithm and the proposed IR-MAD algorithm, which used a mask to eliminate strong changes, the experimental results revealed that the multi-spectral change detection results of the proposed algorithm are closer to the actual value and had higher detection accuracy than the other algorithms. Numéro de notice : A2020-164 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2019.1707124 Date de publication en ligne : 26/12/2020 En ligne : https://doi.org/10.1080/22797254.2019.1707124 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94831
in European journal of remote sensing > vol 53 n° 1 (2020) . - pp 1 -13[article]Assessment of inner reliability in the Gauss-Helmert model / Andreas Ettlinger in Journal of applied geodesy, vol 14 n° 1 (January 2020)PermalinkPermalinkRobust multisource remote sensing image registration method based on scene shape similarity / Ming Hao in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 10 (October 2019)PermalinkMultitemporal Landsat-MODIS fusion for cropland drought monitoring in El Salvador / Nguyen-Thanh Son in Geocarto international, vol 34 n° 12 ([15/09/2019])PermalinkA factor model approach for the joint segmentation with between‐series correlation / Xavier Collilieux in Scandinavian Journal of Statistics, vol 46 n° 3 (September 2019)PermalinkRobust M–M unscented Kalman filtering for GPS/IMU navigation / Cheng Yang in Journal of geodesy, vol 93 n° 8 (August 2019)PermalinkGeometric and statistical interpretation of correlation between fault tests in integrated GPS/INS systems / Ali Almagbile in Journal of applied geodesy, vol 13 n° 3 (July 2019)PermalinkComparing finite and infinitesimal map distortion measures / Krisztian Kerkovits in International journal of cartography, vol 5 n° 1 (March 2019)PermalinkSingle-image photogrammetry for deriving tree architectural traits in mature forest stands: a comparison with terrestrial laser scanning / Kamil Kędra in Annals of Forest Science, vol 76 n° 1 (March 2019)PermalinkAnalyse d’images par méthode de Deep Learning appliquée au contexte routier en conditions météorologiques dégradées / Khouloud Dahmane (2019)Permalink