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Ground surface elevation changes over permafrost areas revealed by multiple GNSS interferometric reflectometry / Yufeng Hu in Journal of geodesy, vol 96 n° 8 (August 2022)  

Public [article]  inJournal of geodesy > vol 96 n° 8 (August 2022) . - n° 56 Titre : Ground surface elevation changes over permafrost areas revealed by multiple GNSS interferometric reflectometry Type de document : Article/Communication Auteurs : Yufeng Hu, Auteur ; Ji Wang, Auteur ; Zhenhong Li, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 56 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] Alaska (Etats-Unis) [Termes IGN] analyse diachronique [Termes IGN] dégel [Termes IGN] données Galileo [Termes IGN] données GLONASS [Termes IGN] pergélisol [Termes IGN] rapport signal sur bruit [Termes IGN] réflecteur [Termes IGN] réflectométrie par GNSS [Termes IGN] signal GNSS [Termes IGN] surface du sol [Termes IGN] variation saisonnière Résumé : (auteur) Ground subsidence and uplift caused by the annual thawing and freezing of the active layer are important variables in permafrost studies. Global positioning system interferometric reflectometry (GPS-IR) has been successfully applied to retrieve the continuous ground surface movements in permafrost areas. However, only GPS signals were used in previous studies. In this study, using multiple global navigation satellite system (GNSS) signal-to-noise ratio (SNR) observations recorded by a GNSS station SG27 in Utqiaġvik, Alaska during the period from 2018 to 2021, we applied multiple GNSS-IR (multi-GNSS-IR) technique to the SNR data and obtained the complete and continuous ground surface elevation changes over the permafrost area at a daily interval in snow-free seasons in 2018 and 2019. The GLONASS-IR and Galileo-IR measurements agreed with the GPS-IR measurements at L1 frequency, which are the most consistent measurements among all multi-GNSS measurements, in terms of the overall subsidence trend but clearly showed periodic noises. We proposed a method to reconstruct the GLONASS- and Galileo-IR elevation changes by specifically grouping and fitting them with a composite model. Compared with GPS L1 results, the unbiased root mean square error (RMSE) of the reconstructed Galileo measurements reduced by 50.0% and 42.2% in 2018 and 2019, respectively, while the unbiased RMSE of the reconstructed GLONASS measurements decreased by 41.8% and 25.8% in 2018 and 2019, respectively. Fitting the composite model to the combined multi-GNSS-IR, we obtained seasonal displacements of − 3.27 ± 0.13 cm (R2 = 0.763) and − 10.56 ± 0.10 cm (R2 = 0.912) in 2018 and 2019, respectively. Moreover, we found that the abnormal summer heave was strongly correlated with rain events, implying hydrological effects on the ground surface elevation changes. Our study shows the feasibility of multi-GNSS-IR in permafrost areas for the first time. Multi-GNSS-IR opens up a great opportunity for us to investigate ground surface movements over permafrost areas with multi-source observations, which are important for our robust analysis and quantitative understanding of frozen ground dynamics under climate change. Numéro de notice : A2022-606 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-022-01646-5 Date de publication en ligne : 13/08/2022 En ligne : https://doi.org/10.1007/s00190-022-01646-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101385 [article]

Phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation / Peng Liu in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 180 (October 2021) . - pp 14 - 28 Titre : Phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation Type de document : Article/Communication Auteurs : Peng Liu, Auteur ; Zhenhong Li, Auteur ; Shisheng Wang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 14 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse des mélanges spectraux [Termes IGN] chevauchement [Termes IGN] Chine [Termes IGN] discontinuité [Termes IGN] image radar moirée [Termes IGN] image TerraSAR-X [Termes IGN] modèle numérique de surface [Termes IGN] ombre [Termes IGN] segmentation [Termes IGN] semis de points Résumé : (auteur) Staring spotlight images with a spatial resolution of up to tens of centimeters are good data sources for urban applications including displacement mapping. However, phase discontinuities, layover, and shadowing effect are also associated with staring spotlight interferograms, adding to the difficulties in height estimation and spatial phase unwrapping. The scattering mechanism of the staring spotlight images in the urban environment is complicated, thus it is difficult to simulate and remove the reference height of staring spotlight interferograms directly. In addition, global spatial phase unwrapping networks tend to smooth phase discontinuities. With the aim of implementing height estimation and phase unwrapping for TerraSAR-X Staring Spotlight interferograms, a workflow for phase unmixing of TerraSAR-X staring spotlight interferograms is proposed in this paper. The PS height is estimated in the baseline domain rather than the spatial domain. Taking into account the length and height change of each connection, the spatial phase unwrapping network is adjusted and segmented into isolated networks. The connected components of the adjusted spatial phase unwrapping network can be identified using graph theory. Spatial phase unwrapping is implemented in individual networks. The unfolded height phase is separated from the unwrapped phase, and the remaining phase is deformation dominated. Compared with the traditional global spatial phase unwrapping method, this study demonstrates the feasibility of the proposed least squares parameter search and graph partition based workflow in urban area, for phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation, as evidenced by external LiDAR DSM and temperature records. Numéro de notice : A2021-652 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.08.007 Date de publication en ligne : 14/08/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.08.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98382 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2021101	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2021103	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2021102	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Delineating and modeling activity space using geotagged social media data / Lingqian Hu in Cartography and Geographic Information Science, vol 47 n° 3 (May 2020)  

Public [article]  inCartography and Geographic Information Science > vol 47 n° 3 (May 2020) . - pp 277 - 288 Titre : Delineating and modeling activity space using geotagged social media data Type de document : Article/Communication Auteurs : Lingqian Hu, Auteur ; Zhenhong Li, Auteur ; Xinyue Ye, Auteur Année de publication : 2020 Article en page(s) : pp 277 - 288 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] distance [Termes IGN] données localisées des bénévoles [Termes IGN] données massives [Termes IGN] données socio-économiques [Termes IGN] logement [Termes IGN] loisir [Termes IGN] Los Angeles [Termes IGN] quartier [Termes IGN] réseau social [Termes IGN] sport [Termes IGN] Twitter [Termes IGN] voisinage (relation topologique) [Termes IGN] zone urbaine Résumé : (auteur) It has become increasingly important in spatial equity studies to understand activity spaces – where people conduct regular out-of-home activities. Big data can advance the identification of activity spaces and the understanding of spatial equity. Using the Los Angeles metropolitan area for the case study, this paper employs geotagged Twitter data to delineate activity spaces with two spatial measures: first, the average distance between users’ home location and activity locations; and second, the area covered between home and activity locations. The paper also finds significant relationship between the spatial measures of activity spaces and neighborhood spatial and socioeconomic characteristics. This research enriches the literature that aims to address spatial equity in activity spaces and demonstrates the applicability of big data in urban socio-spatial research. Numéro de notice : A2020-135 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2019.1705187 Date de publication en ligne : 10/02/2020 En ligne : https://doi.org/10.1080/15230406.2019.1705187 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94843 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
032-2020031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Random Forest and Rotation Forest for fully polarized SAR image classification using polarimetric and spatial features / Peijun Du in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 105 (July 2015) . - pp 38 - 53 Titre : Random Forest and Rotation Forest for fully polarized SAR image classification using polarimetric and spatial features Type de document : Article/Communication Auteurs : Peijun Du, Auteur ; Alim Samat, Auteur ; Björn Waske, Auteur ; Sicong Liu, Auteur ; Zhenhong Li, Auteur Année de publication : 2015 Article en page(s) : pp 38 - 53 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] données polarimétriques [Termes IGN] image Radarsat [Termes IGN] polarimétrie radar [Termes IGN] Rotation Forest classification [Termes IGN] texture d'image Résumé : (auteur) Fully Polarimetric Synthetic Aperture Radar (PolSAR) has the advantages of all-weather, day and night observation and high resolution capabilities. The collected data are usually sorted in Sinclair matrix, coherence or covariance matrices which are directly related to physical properties of natural media and backscattering mechanism. Additional information related to the nature of scattering medium can be exploited through polarimetric decomposition theorems. Accordingly, PolSAR image classification gains increasing attentions from remote sensing communities in recent years. However, the above polarimetric measurements or parameters cannot provide sufficient information for accurate PolSAR image classification in some scenarios, e.g. in complex urban areas where different scattering mediums may exhibit similar PolSAR response due to couples of unavoidable reasons. Inspired by the complementarity between spectral and spatial features bringing remarkable improvements in optical image classification, the complementary information between polarimetric and spatial features may also contribute to PolSAR image classification. Therefore, the roles of textural features such as contrast, dissimilarity, homogeneity and local range, morphological profiles (MPs) in PolSAR image classification are investigated using two advanced ensemble learning (EL) classifiers: Random Forest and Rotation Forest. Supervised Wishart classifier and support vector machines (SVMs) are used as benchmark classifiers for the evaluation and comparison purposes. Experimental results with three Radarsat-2 images in quad polarization mode indicate that classification accuracies could be significantly increased by integrating spatial and polarimetric features using ensemble learning strategies. Rotation Forest can get better accuracy than SVM and Random Forest, in the meantime, Random Forest is much faster than Rotation Forest. Numéro de notice : A2015-706 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.03.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.03.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78342 [article]

Using small baseline Interferometric SAR to map nonlinear ground motion: a case study in Northern Tibet / Zhenhong Li in Journal of applied geodesy, vol 3 n° 3 (August 2009)  

Public [article]  inJournal of applied geodesy > vol 3 n° 3 (August 2009) . - pp 163 - 170 Titre : Using small baseline Interferometric SAR to map nonlinear ground motion: a case study in Northern Tibet Type de document : Article/Communication Auteurs : Zhenhong Li, Auteur ; Yanxiong Liu, Auteur ; et al., Auteur Année de publication : 2009 Article en page(s) : pp 163 - 170 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] déformation de la croute terrestre [Termes IGN] image Envisat-ASAR [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] mouvement de terrain [Termes IGN] Tibet Résumé : (auteur) With its global coverage and all-weather imaging capability, Interferometric SAR (InSAR) has been revolutionizing our ability to image the Earth's surface and the evolution of its shape over time. In turn, this has led to many new insights into geophysical and engineering processes, such as volcanoes, earthquakes, landslides and mining activity. In this study, we used an advanced InSAR time series technique to map ground motion of an area in Northern Tibet using ENVISAT images acquired between 2003 and 2007. In order to minimise the effects of baseline decorrelation, a subset of possible pairs having a perpendicular baseline (i.e. orbital separation) of less than 400 m was chosen for the InSAR time series analysis. The time series results reveal an ‘unexpected’ nonlinear ground motion: the area of interest was relatively stable during the period from 2003 to the middle of 2004, whilst it has exhibited a nearly linear uplift of about 8 cm since the middle of 2004. Examination of high-resolution ALOS PRISM images shows that the uplift signal occurred over the Huatugou oil field and is most likely caused by water injection. This study highlights the potential of InSAR as an early detection tool of surface deformations. Numéro de notice : A2009-568 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1515/JAG.2009.017 Date de publication en ligne : 18/08/2009 En ligne : https://doi.org/10.1515/JAG.2009.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75409 [article]