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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 / 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]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)
[article]
Titre : Assessment of inner reliability in the Gauss-Helmert model Type de document : Article/Communication Auteurs : Andreas Ettlinger, Auteur ; Hans Neuner, Auteur Année de publication : 2020 Article en page(s) : pp 13 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie
[Termes IGN] coefficient de corrélation
[Termes IGN] compensation par moindres carrés
[Termes IGN] détection d'erreur
[Termes IGN] erreur systématique
[Termes IGN] fiabilité des données
[Termes IGN] filtre de Kalman
[Termes IGN] modèle d'erreur
[Termes IGN] modèle de Gauss-Helmert
[Termes IGN] valeur aberranteRésumé : (auteur) In this contribution, the minimum detectable bias (MDB) as well as the statistical tests to identify disturbed observations are introduced for the Gauss-Helmert model. Especially, if the observations are uncorrelated, these quantities will have the same structure as in the Gauss-Markov model, where the redundancy numbers play a key role. All the derivations are based on one-dimensional and additive observation errors respectively offsets which are modeled as additional parameters to be estimated. The formulas to compute these additional parameters with the corresponding variances are also derived in this contribution. The numerical examples of plane fitting and yaw computation show, that the MDB is also in the GHM an appropriate measure to analyze the ability of an implemented least-squares algorithm to detect if outliers are present. Two sources negatively influencing detectability are identified: columns close to the zero vector in the observation matrix B and sub-optimal configuration in the design matrix A. Even if these issues can be excluded, it can be difficult to identify the correct observation as being erroneous. Therefore, the correlation coefficients between two test values are derived and analyzed. Together with the MDB these correlation coefficients are an useful tool to assess the inner reliability – and therefore the detection and identification of outliers – in the Gauss-Helmert model. Numéro de notice : A2020-040 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0013 Date de publication en ligne : 19/10/2019 En ligne : https://doi.org/10.1515/jag-2019-0013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94511
in Journal of applied geodesy > vol 14 n° 1 (January 2020) . - pp 13 - 28[article]Robust 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)
[article]
Titre : Robust multisource remote sensing image registration method based on scene shape similarity Type de document : Article/Communication Auteurs : Ming Hao, Auteur ; Jian Jin, Auteur ; Mengchao Zhou, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 725 - 736 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] appariement de modèles conceptuels de données
[Termes IGN] coefficient de corrélation
[Termes IGN] figuré du terrain
[Termes IGN] image multibande
[Termes IGN] image radar moirée
[Termes IGN] niveau de gris (image)
[Termes IGN] points homologues
[Termes IGN] superposition d'images
[Termes IGN] temps de pose
[Termes IGN] transformation linéaireRésumé : (Auteur) Image registration is an indispensable component of remote sensing applications, such as disaster monitoring, change detection, and classification. Grayscale differences and geometric distortions often occur among multisource images due to their different imaging mechanisms, thus making it difficult to acquire feature points and match corresponding points. This article proposes a scene shape similarity feature (SSSF) descriptor based on scene shape features and shape context algorithms. A new similarity measure called SSSFncc is then defined by computing the normalized correlation coefficient of the SSSF descriptors between multisource remote sensing images. Furthermore, the tie points between the reference and the sensed image are extracted via a template matching strategy. A global consistency check method is then used to remove the mismatched tie points. Finally, a piecewise linear transform model is selected to rectify the remote sensing image. The proposed SSSFncc aims to extract the scene shape similarity between multisource images. The accuracy of the proposed SSSFncc is evaluated using five pairs of experimental images from optical, synthetic aperture radar, and map data. Registration results demonstrate that the SSSFncc similarity measure is robust enough for complex nonlinear grayscale differences among multisource remote sensing images. The proposed method achieves more reliable registration outcomes compared with other popular methods. Numéro de notice : A2019-521 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.10.725 Date de publication en ligne : 01/10/2019 En ligne : https://doi.org/10.14358/PERS.85.10.725 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93989
in Photogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 10 (October 2019) . - pp 725 - 736[article]Réservation
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