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  • 1
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    Basel, Beijing, Wuhan, Barcelona, Belgrade : MDPI
    Schlagwort(e): Synthetic Aperture Radar ; SAR Sensors ; SAR Interferometry ; DEM Generation from SAR Data ; Surface Motion Estimation from SAR ; SAR Polarimetry ; SAR constellations ; Geosynchronous SAR ; Ground based SAR ; SAR applications
    Beschreibung / Inhaltsverzeichnis: Deng, X.; López-Martínez, C.; Chen, J.; Han, P. Statistical Modeling of Polarimetric SAR Data: A Survey and Challenges. Remote Sens. 2017, 9(4), 348; https://doi.org/10.3390/rs9040348 --- Braun, A.; Hochschild, V. A SAR-Based Index for Landscape Changes in African Savannas. Remote Sens. 2017, 9(4), 359; https://doi.org/10.3390/rs9040359 --- Ghafouri, A.; Amini, J.; Dehmollaian, M.; Kavoosi, M. Better Estimated IEM Input Parameters Using Random Fractal Geometry Applied on Multi-Frequency SAR Data. Remote Sens. 2017, 9(5), 445; https://doi.org/10.3390/rs9050445 --- Kim, S.; Yu, J.; Jeon, S.; Dewantari, A.; Ka, M. Signal Processing for a Multiple-Input, Multiple-Output (MIMO) Video Synthetic Aperture Radar (SAR) with Beat Frequency Division Frequency-Modulated Continuous Wave (FMCW). Remote Sens. 2017, 9(5), 491; https://doi.org/10.3390/rs9050491 --- Chen, Q.; Li, L.; Xu, Q.; Yang, S.; Shi, X.; Liu, X. Multi-Feature Segmentation for High-Resolution Polarimetric SAR Data Based on Fractal Net Evolution Approach. Remote Sens. 2017, 9(6), 570; https://doi.org/10.3390/rs9060570 --- Garthwaite, M. On the Design of Radar Corner Reflectors for Deformation Monitoring in Multi-Frequency InSAR. Remote Sens. 2017, 9(7), 648; https://doi.org/10.3390/rs9070648 --- Tao, C.; Chen, S.; Li, Y.; Xiao, S. PolSAR Land Cover Classification Based on Roll-Invariant and Selected Hidden Polarimetric Features in the Rotation Domain. Remote Sens. 2017, 9(7), 660; https://doi.org/10.3390/rs9070660 --- Giudici, D.; Monti Guarnieri, A.; Cuesta Gonzalez, J. Pre-Flight SAOCOM-1A SAR Performance Assessment by Outdoor Campaign. Remote Sens. 2017, 9(7), 729; https://doi.org/10.3390/rs9070729 --- Libert, L.; Derauw, D.; d’Oreye, N.; Barbier, C.; Orban, A. Split-Band Interferometry-Assisted Phase Unwrapping for the Phase Ambiguities Correction. Remote Sens. 2017, 9(9), 879; https://doi.org/10.3390/rs9090879 --- Zhao, J.; Wu, J.; Ding, X.; Wang, M. Elevation Extraction and Deformation Monitoring by Multitemporal InSAR of Lupu Bridge in Shanghai. Remote Sens. 2017, 9(9), 897; https://doi.org/10.3390/rs9090897 --- Park, J.; Kim, J.; Won, J. Fast and Efficient Correction of Ground Moving Targets in a Synthetic Aperture Radar, Single-Look Complex Image. Remote Sens. 2017, 9(9), 926; https://doi.org/10.3390/rs9090926 --- Shi, X.; Jiang, H.; Zhang, L.; Liao, M. Landslide Displacement Monitoring with Split-Bandwidth Interferometry: A Case Study of the Shuping Landslide in the Three Gorges Area. Remote Sens. 2017, 9(9), 937; https://doi.org/10.3390/rs9090937 --- Zhai, A.; Wen, X.; Xu, H.; Yuan, L.; Meng, Q. Multi-Layer Model Based on Multi-Scale and Multi-Feature Fusion for SAR Images. Remote Sens. 2017, 9(10), 1085; https://doi.org/10.3390/rs9101085 --- Wang, C.; Chen, L.; Zhao, H.; Lu, Z.; Bian, M.; Zhang, R.; Feng, J. Ionospheric Reconstructions Using Faraday Rotation in Spaceborne Polarimetric SAR Data. Remote Sens. 2017, 9(11), 1169; https://doi.org/10.3390/rs9111169 --- Monti-Guarnieri, A.; Giudici, D.; Recchia, A. Identification of C-Band Radio Frequency Interferences from Sentinel-1 Data. Remote Sens. 2017, 9(11), 1183; https://doi.org/10.3390/rs9111183 --- Behnamian, A.; Banks, S.; White, L.; Brisco, B.; Millard, K.; Pasher, J.; Chen, Z.; Duffe, J.; Bourgeau-Chavez, L.; Battaglia, M. Semi-Automated Surface Water Detection with Synthetic Aperture Radar Data: A Wetland Case Study. Remote Sens. 2017, 9(12), 1209; https://doi.org/10.3390/rs9121209 --- Sun, L.; Muller, J.; Chen, J. Time Series Analysis of Very Slow Landslides in the Three Gorges Region through Small Baseline SAR Offset Tracking. Remote Sens. 2017, 9(12), 1314; https://doi.org/10.3390/rs9121314 --- Di Martino, G.; Iodice, A.; Riccio, D.; Ruello, G.; Zinno, I. The Role of Resolution in the Estimation of Fractal Dimension Maps From SAR Data. Remote Sens. 2018, 10(1), 9; https://doi.org/10.3390/rs10010009 --- Garthwaite, M. Correction: Garthwaite, M.C. on the Design of Radar Corner Reflectors for Deformation Monitoring in Multi-Frequency InSAR. Remote Sens. 2017, 9, 648. Remote Sens. 2018, 10(1), 86; https://doi.org/10.3390/rs10010086 --- Zhang, H.; Tang, J.; Wang, R.; Deng, Y.; Wang, W.; Li, N. An Accelerated Backprojection Algorithm for Monostatic and Bistatic SAR Processing. Remote Sens. 2018, 10(1), 140; https://doi.org/10.3390/rs10010140 --- Eshqi Molan, Y.; Kim, J.; Lu, Z.; Agram, P. L-Band Temporal Coherence Assessment and Modeling Using Amplitude and Snow Depth over Interior Alaska. Remote Sens. 2018, 10(1), 150; https://doi.org/10.3390/rs10010150 --- Dong, Y.; Jiang, H.; Zhang, L.; Liao, M. An Efficient Maximum Likelihood Estimation Approach of Multi-Baseline SAR Interferometry for Refined Topographic Mapping in Mountainous Areas. Remote Sens. 2018, 10(3), 454; https://doi.org/10.3390/rs10030454 --- Bu, Y.; Liang, X.; Wang, Y.; Zhang, F.; Li, Y. A Unified Algorithm for Channel Imbalance and Antenna Phase Center Position Calibration of a Single-Pass Multi-Baseline TomoSAR System. Remote Sens. 2018, 10(3), 456; https://doi.org/10.3390/rs10030456 --- Neelmeijer, J.; Schöne, T.; Dill, R.; Klemann, V.; Motagh, M. Ground Deformations around the Toktogul Reservoir, Kyrgyzstan, from Envisat ASAR and Sentinel-1 Data—A Case Study about the Impact of Atmospheric Corrections on InSAR Time Series. Remote Sens. 2018, 10(3), 462; https://doi.org/10.3390/rs10030462 --- Tian, X.; Malhotra, R.; Xu, B.; Qi, H.; Ma, Y. Modeling Orbital Error in InSAR Interferogram Using Frequency and Spatial Domain Based Methods. Remote Sens. 2018, 10(4), 508; https://doi.org/10.3390/rs10040508 --- Even, M.; Schulz, K. InSAR Deformation Analysis with Distributed Scatterers: A Review Complemented by New Advances. Remote Sens. 2018, 10(5), 744; https://doi.org/10.3390/rs10050744 --- Washaya, P.; Balz, T.; Mohamadi, B. Coherence Change-Detection with Sentinel-1 for Natural and Anthropogenic Disaster Monitoring in Urban Areas. Remote Sens. 2018, 10(7), 1026; https://doi.org/10.3390/rs10071026 --- Balz, T.; Sörgel, U.; Crespi, M.; Osmanoglu, B. Editorial for Special Issue “Advances in SAR: Sensors, Methodologies, and Applications”. Remote Sens. 2018, 10(8), 1233; https://doi.org/10.3390/rs10081233
    Seiten: Online-Ressource (X, 515 Seiten) , Illustrationen, Diagramme, Karten
    Ausgabe: Printed Edition of the Special Issue Published in Remote Sensing
    ISBN: 9783038971832
    Sprache: Englisch
    Standort Signatur Erwartet Verfügbarkeit
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  • 2
    Publikationsdatum: 2020-12-15
    Beschreibung: The knowledge of coseismic deformations due to earthquakes represents the fundamentals on which studies on seismic cycle and fault source mechanism are based on. Geodetic methods, in particular the recent developments of GNSS monitoring, are the only onescapable of providing the displacements of reference sites due to the occurrence of significant seismic events. Usually the detection of seismic offsets is done by comparing coordinates estimated before and after the earthquake. Here, considering the test case of the 30 October, 2016 central Italy seismic event, we show that it is possible to achieve such offsets also in real-time through the application of the new functionalities of the VADASE (Variometric Approach for Displacements Analysis Stand-alone Engine) approach. The comparison between the seismic offsets coming from the two approaches (static and realtime) is shown and discussed; the mean overall agreement is at the level of about half centimetre.
    Beschreibung: Published
    Beschreibung: 189-198
    Beschreibung: 2T. Deformazione crostale attiva
    Schlagwort(e): Coseismic Offset ; VADASE ; Tectonic deformation ; Central Italy 2016 earthquakes ; 04.03. Geodesy
    Repository-Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Materialart: book chapter
    Standort Signatur Erwartet Verfügbarkeit
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  • 3
    Publikationsdatum: 2022-05-06
    Beschreibung: The goal of this article is the illustration of the new functionalities of the VADASE (Variometric Approach for Displacements Analysis Stand-alone Engine) processing approach. VADASE was presented in previous works as an approach able to estimate in real time the velocities and displacements in a global reference frame (ITRF), using high-rate (1 Hz or more) carrier phase observations and broadcast products (orbits, clocks) collected by a stand-alone GNSS receiver, achieving a displacements accuracy within 1–2 cm (usually better) over intervals up to a few minutes. It has been well known since the very first implementation and testing of VADASE that the estimated displacements might be impacted by two different effects: spurious spikes in the velocities due to outliers (consequently, displacements, obtained through velocities integration, are severely corrupted) and trends in the displacements time series, mainly due to broadcast orbit and clock errors. Two strategies are herein introduced, respectively based on Leave-One-Out cross-validation (VADASE-LOO) for a receiver autonomous outlier detection, and on a network augmentation strategy to filter common trends out (A-VADASE); they are combined (first, VADASE-LOO; second, A-VADASE) for a complete solution. Moreover, starting from this VADASE improved solution, an additional strategy is proposed to estimate in real time the overall coseismic displacement occurring at each GNSS receiver. New VADASE advances are successfully applied to the GPS data collected during the recent three strong earthquakes that occurred in Central Italy on 24 August and 26 and 30 October 2016, and the results are herein presented and discussed. The VADASE real-time estimated coseismic displacements are compared to the static ones derived from the daily solutions obtained within the standard post-processing procedure by the Istituto Nazionale di Geofisica e Vulcanologia.
    Beschreibung: Published
    Beschreibung: id 1201
    Beschreibung: 2T. Deformazione crostale attiva
    Beschreibung: JCR Journal
    Schlagwort(e): GNSS seismology ; variometric approach improvements ; real-time coseismic displacements ; Central Italy 2016 earthquakes
    Repository-Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Materialart: article
    Standort Signatur Erwartet Verfügbarkeit
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