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Cluster-based empirical tropospheric corrections applied to InSAR time series analysis / Kyle Dennis Murray in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 3 (March 2021) . - pp 2204 - 2212 Titre : Cluster-based empirical tropospheric corrections applied to InSAR time series analysis Type de document : Article/Communication Auteurs : Kyle Dennis Murray, Auteur ; Rowena B. Lohman, Auteur ; David P. S. Bekaert, Auteur Année de publication : 2021 Article en page(s) : pp 2204 - 2212 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande C [Termes IGN] bruit atmosphérique [Termes IGN] classification par nuées dynamiques [Termes IGN] déformation de la croute terrestre [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] Mexique [Termes IGN] retard troposphérique [Termes IGN] série temporelle Résumé : (Auteur) Interferometric synthetic aperture radar (InSAR) allows for mapping of crustal deformation on land with high spatial resolution and precision in areas with high signal-to-noise ratios. Efforts to obtain precise displacement time series globally, however, are severely limited by radar path delays within the troposphere. The tropospheric delay is integrated along the full path length between the ground and the satellite, resulting in correlations between the interferometric phase and elevation that can vary dramatically in both space and time. We evaluate the performance of spatially variable, empirical removal of phase-elevation dependence within SAR interferograms through the use of the K -means clustering algorithm. We apply this method to both synthetic test data, as well as to C-band Sentinel-1a/b time series acquired over a large area in south-central Mexico along the Pacific coast and inland—an area with a large elevation gradient that is of particular interest to researchers studying tectonic- and anthropogenic-related deformation. We show that the clustering algorithm is able to identify cases where tropospheric properties vary across topographic divides, reducing total root mean square (rms) by an average of 50%, as opposed to a spatially constant phase-elevation correction, which has insignificant error reduction. Our approach also reduces tropospheric noise while preserving test signals in synthetic examples. Finally, we show the average standard deviation of the residuals from the best-fit linear rate decreases from approximately 3 to 1.5 cm, which corresponds to a change in the error on the best-fit linear rate from 0.94 to 0.63 cm/yr. Numéro de notice : A2021-215 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3003271 Date de publication en ligne : 30/06/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3003271 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97204 [article]

Impact of forest disturbance on InSAR surface displacement time series / Paula M. Bürgi in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 1 (January 2021) . - pp 128 - 138 Titre : Impact of forest disturbance on InSAR surface displacement time series Type de document : Article/Communication Auteurs : Paula M. Bürgi, Auteur ; Rowena B. Lohman, Auteur Année de publication : 2021 Article en page(s) : pp 128 - 138 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] changement d'occupation du sol [Termes IGN] déboisement [Termes IGN] détection de changement [Termes IGN] détection du signal [Termes IGN] erreur de phase [Termes IGN] erreur systématique [Termes IGN] image ALOS [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] retard ionosphèrique [Termes IGN] retard troposphérique [Termes IGN] série temporelle [Termes IGN] Sumatra [Termes IGN] surveillance géologique Résumé : (auteur) As interferometric synthetic aperture radar (InSAR) data improve in their global coverage and temporal sampling, studies of ground deformation using InSAR are becoming feasible even in heavily vegetated regions such as the American Pacific Northwest (PNW) and Sumatra. However, ongoing forest disturbance due to logging, wildfires, or disease can introduce time-variable signals which could be misinterpreted as ground displacements. This study constrains the error introduced into InSAR time series in the presence of time-variable forest disturbance using synthetic data. For satellite platforms with randomly distributed orbital positions in time (e.g., Sentinel-1), mid-time series forest disturbance results in random error on the order of 0.2 and 10 cm/year for 1-year secular and time-variable velocities, respectively. If the orbital positions are not randomly distributed in time (e.g., ALOS-1), a biased error on the order of 10 cm/year is introduced to the inferred secular velocity. A time series using real ALOS-1 data near Eugene, OR, USA, shows agreement with the bias estimated by synthetic models. Mitigation of time-variable land cover change effects can be achieved if their timing is known, either through independent observations of surface properties (e.g., Landsat/Sentinel-2) or through the use of more computationally expensive, nonlinear inversions with additional terms for the timing of height changes. Inclusion of these additional terms reduces the potential for misinterpretation of InSAR signals associated with land surface change as ground deformation. Numéro de notice : A2021-032 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2992938 Date de publication en ligne : 18/05/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2992938 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96727 [article]