scholarly journals Coeruptive and posteruptive crustal deformation associated with the 2018 Kusatsu-Shirane phreatic eruption based on PALSAR-2 time-series analysis

2020 ◽  
Author(s):  
Yuji Himematsu ◽  
Taku Ozawa ◽  
Yosuke Aoki
Keyword(s):  
Time Series ◽  
Crustal Deformation ◽  
Hydrothermal System ◽  
Phreatic Eruption ◽  
Physical Processes ◽  
Cumulative Deformation ◽  
Time Series Analyses ◽  
L Band ◽  
Phreatic Eruptions ◽  
Sar Data

Abstract Coeruptive deformation helps to interpret physical processes associated with volcanic eruptions. Because phreatic eruptions cause small, localized coeruptive deformation, we sometimes fail to identify plausible deformation signals. Satellite synthetic aperture radar (SAR) data allow us to identify extensive deformation fields with high spatial resolutions. Herein, we report coeruptive crustal deformation associated with the 2018 Kusatsu-Shirane phreatic eruption detected by time series analyses of L-band satellite SAR (ALOS-2/PALSAR-2) data. Cumulative deformation maps derived from SAR time series analyses show that subsidence and eastward displacement dominate the southwestern side of an eruptive crater with a spatial extent of approximately 2 km in diameter. Although we were unable to identify any significant deformation signals before the 2018 eruption, posteruptive deformation on the southwestern side of the crater has been ongoing until the end of 2019. This prolonged deformation implies the progression of posteruptive physical processes within a confined hydrothermal system, such as volcanic fluid discharge, similar to the processes observed during the 2014 Ontake eruption. Although accumulated snow and dense vegetation hinder the detection of deformation signals on Kusatsu-Shirane volcano using conventional InSAR data, L-band SAR with various temporal baselines allowed us to successfully extract both coeruptive and posteruptive deformation signals. The extracted cumulative deformation is well explained by a combination of normal faulting with a left-lateral slip component along a southwest-dipping fault plane and an isotropic deflation. Based on the geological background in which the shallow hydrothermal system develops across Kusatsu-Shirane volcano, the inferred dislocation plane can be considered as a degassing pathway from the shallow hydrothermal system to the surface due to the phreatic eruption. We reconfirmed that SAR data is a robust tool for detecting coeruptive and posteruptive deformations, which are helpful for understanding shallow physical processes associated with phreatic eruptions at active volcanoes.

scholarly journals Coeruptive and posteruptive crustal deformation associated with the 2018 Kusatsu-Shirane phreatic eruption based on PALSAR-2 time-series analysis

2020 ◽  
Author(s):  
Yuji Himematsu ◽  
Taku Ozawa ◽  
Yosuke Aoki
Keyword(s):  
Time Series ◽  
Crustal Deformation ◽  
Hydrothermal System ◽  
Phreatic Eruption ◽  
Physical Processes ◽  
Cumulative Deformation ◽  
Time Series Analyses ◽  
L Band ◽  
Phreatic Eruptions ◽  
Sar Data

Abstract Coeruptive deformation helps to interpret physical processes associated with volcanic eruptions. Because phreatic eruptions cause small, localized coeruptive deformation, we sometimes fail to identify plausible deformation signals. Satellite synthetic aperture radar (SAR) data allow us to identify extensive deformation fields with high spatial resolutions. Herein, we report coeruptive crustal deformation associated with the 2018 Kusatsu-Shirane phreatic eruption detected by time series analyses of L-band satellite SAR (ALOS-2/PALSAR-2) data. Cumulative deformation maps derived from SAR time series analyses show that subsidence and eastward displacement dominate the southwestern side of an eruptive crater with a spatial extent of approximately 2 km in diameter. Although we were unable to identify any significant deformation signals before the 2018 eruption, posteruptive deformation on the southwestern side of the crater has been ongoing until the end of 2019. This prolonged deformation implies the progression of posteruptive physical processes within a confined hydrothermal system, such as volcanic fluid discharge, similar to the processes observed during the 2014 Ontake eruption. Although accumulated snow and dense vegetation hinder the detection of deformation signals on Kusatsu-Shirane volcano using conventional InSAR data, L-band SAR with various temporal baselines allowed us to successfully extract both coeruptive and posteruptive deformation signals. The extracted cumulative deformation is well explained by a combination of normal faulting with a left-lateral slip component along a southwest-dipping fault plane and an isotropic deflation. Based on the geological background in which the shallow hydrothermal system develops across Kusatsu-Shirane volcano, the inferred dislocation plane can be considered as a degassing pathway from the shallow hydrothermal system to the surface due to the phreatic eruption. We reconfirmed that SAR data is a robust tool for detecting coeruptive and posteruptive deformations, which are helpful for understanding shallow physical processes associated with phreatic eruptions at active volcanoes.

scholarly journals Coeruptive crustal deformation associated with the 2018 Kusatsu-Shirane phreatic eruption based on PALSAR-2 time-series analysis

2020 ◽  
Author(s):  
Yuji Himematsu ◽  
Taku Ozawa ◽  
Yosuke Aoki
Keyword(s):  
Time Series ◽  
Crustal Deformation ◽  
Hydrothermal System ◽  
Fault Plane ◽  
Phreatic Eruption ◽  
Physical Processes ◽  
Time Series Analyses ◽  
L Band ◽  
Phreatic Eruptions ◽  
Sar Data

Abstract Coeruptive deformation helps to interpret physical processes associated with volcanic eruptions. Because phreatic eruptions cause small, localized coeruptive deformation, we sometimes fail to identify plausible deformation signals. Satellite synthetic aperture radar (SAR) data allow us to identify extensive deformation fields with high spatial resolutions. Herein, we report coeruptive crustal deformation associated with the 2018 Kusatsu-Shirane phreatic eruption detected by time series analyses of L-band satellite SAR (ALOS-2/PALSAR-2) data. Coeruptive deformation maps derived from SAR time series analyses show that subsidence and eastward displacement dominate the southwestern side of an eruptive crater with a spatial extent of approximately 2 km in diameter. Although we were unable to identify any significant deformation signals before the 2018 eruption, posteruptive deformation on the southwestern side of the crater has been ongoing until the end of 2019. This prolonged deformation implies the progression of posteruptive physical processes within a confined hydrothermal system, such as volcanic fluid discharge, similar to the processes observed during the 2014 Ontake eruption. Although accumulated snow and dense vegetation hinder the detection of deformation signals on Kusatsu-Shirane volcano using conventional InSAR data, L-band SAR with various temporal baselines allowed us to successfully extract both coeruptive and posteruptive deformation signals. The extracted coeruptive deformation events are well explained by normal faulting with a left-lateral slip component along a southwest-dipping fault plane rather than by a point source deflation. The inferred fault plane can be considered as a degassing pathway from the shallow hydrothermal system to the surface. We reconfirmed that SAR data is a robust tool for detecting coeruptive and posteruptive deformations, which are helpful for understanding shallow physical processes associated with phreatic eruptions at active volcanoes.

scholarly journals Detecting tropical selective logging with SAR data requires a time series approach

2020 ◽  
Author(s):  
MG Hethcoat ◽  
JMB Carreiras ◽  
DP Edwards ◽  
RG Bryant ◽  
S Quegan
Keyword(s):  
Time Series ◽  
Random Forest ◽  
Forest Degradation ◽  
Selective Logging ◽  
Forest Monitoring ◽  
Free Access ◽  
Alos Palsar ◽  
Lowland Tropical Forest ◽  
Time Series Analyses ◽  
Sar Data

AbstractSelective logging is the primary driver of forest degradation in the tropics and reduces the capacity of forests to harbour biodiversity, maintain key ecosystem processes, sequester carbon, and support human livelihoods. While the preceding decade has seen a tremendous improvement in the ability to monitor forest disturbances from space, advances in forest monitoring have almost universally relied on optical satellite data from the Landsat program, whose effectiveness is limited in tropical regions with frequent cloud cover. Synthetic aperture radar (SAR) data can penetrate clouds and have been utilized in forest mapping applications since the early 1990s, but no study has exclusively used SAR data to map tropical selective logging. A detailed selective logging dataset from three lowland tropical forest regions in the Brazilian Amazon was used to assess the effectiveness of SAR data from Sentinel-1, RADARSAT-2 and PALSAR-2 for monitoring tropical selective logging. We built Random Forest models in an effort to classify pixel-based differences in logged and unlogged areas. In addition, we used the BFAST algorithm to assess if a dense time series of Sentinel-1 imagery displayed recognizable shifts in pixel values after selective logging. Random Forest classification with SAR data (Sentinel-1, RADARSAT-2, and ALOS-2 PALSAR-2) performed poorly, having high commission and omission errors for logged observations. This suggests little to no difference in pixel-based metrics between logged and unlogged areas for these sensors. In contrast, the Sentinel-1 time series analyses indicated that areas under higher intensity selective logging (> 20 m3 ha−1) show a distinct spike in the number of pixels that included a breakpoint during the logging season. BFAST detected breakpoints in 50% of logged pixels and exhibited a false alarm rate of approximately 10% in unlogged forest. Overall our results suggest that SAR data can be used in time series analyses to detect tropical selective logging at high intensity logging locations within the Amazon (> 20 m3 ha−1). These results have important implications for current and future abilities to detect selective logging with freely available SAR data from SAOCOM 1A, the planned continuation missions of Sentinel-1 (C and D), ALOS PALSAR-1 archives (expected to be opened for free access in 2020), and the upcoming launch of NISAR.

scholarly journals InSAR Time Series Analysis of L-band Wide- Swath SAR Data Acquired by ALOS-2

2020 ◽  
Author(s):  
Cunren Liang ◽  
Zhen Liu ◽  
Eric Fielding ◽  
Roland Bürgmann
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Series Analysis ◽  
L Band ◽  
Sar Data ◽  
Wide Swath

scholarly journals InSAR Time Series Analysis of L-Band Wide-Swath SAR Data Acquired by ALOS-2

2018 ◽  
Vol 56 (8) ◽  
pp. 4492-4506 ◽  
Author(s):  
Cunren Liang ◽  
Zhen Liu ◽  
Eric J. Fielding ◽  
Roland Burgmann
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Series Analysis ◽  
L Band ◽  
Sar Data ◽  
Wide Swath

scholarly journals Spatio-Temporal Characterization of a Reclamation Settlement in the Shanghai Coastal Area with Time Series Analyses of X-, C-, and L-Band SAR Datasets

2018 ◽  
Vol 10 (2) ◽  
pp. 329 ◽  
Author(s):  
Mengshi Yang ◽  
Tianliang Yang ◽  
Lu Zhang ◽  
Jinxin Lin ◽  
Xiaoqiong Qin ◽  
...  
Keyword(s):  
Time Series ◽  
Coastal Area ◽  
Time Series Analyses ◽  
L Band ◽  
Spatio Temporal

scholarly journals Mapping Urban Excavation Induced Deformation in 3D via Multiplatform InSAR Time-Series

2021 ◽  
Vol 13 (23) ◽  
pp. 4748
Author(s):  
Kendall Wnuk ◽  
Wendy Zhou ◽  
Marte Gutierrez
Keyword(s):  
Time Series ◽  
Los Angeles ◽  
Surface Deformation ◽  
Continuous Distribution ◽  
Subway Station ◽  
Multiple Sensors ◽  
The North ◽  
L Band ◽  
Sar Data ◽  
Airborne Sar

Excavation of a subway station and rail crossover cavern in downtown Los Angeles, California, USA, induced over 1.8 cm of surface settlement between June 2018 and February 2019 as measured by a ground-based monitoring system. Point measurements of surface deformation above the excavation were extracted by applying Interferometric Synthetic Aperture Radar (InSAR) time-series analyses to data from multiple sensors with different wavelengths. These sensors include C-band Sentinel-1, X-band COSMO-SkyMed, and L-band Uninhabited Aerial Vehicle SAR (UAVSAR). The InSAR time-series point measurements were interpolated to continuous distribution surfaces, weighted by distance, and entered into the Minimum-Acceleration (MinA) algorithm to calculate 3D displacement values. This dataset, composed of satellite and airborne SAR data from X, C, and L band sensors, revealed previously unidentified deformation surrounding the 2nd Street and Broadway Subway Station and the adjacent rail crossover cavern, with maximum vertical and horizontal deformations reaching 2.5 cm and 1.7 cm, respectively. In addition, the analysis shows that airborne SAR data with alternative viewing geometries to traditional polar-orbiting SAR satellites can be used to constrain horizontal displacements in the North-South direction while maintaining agreement with ground-based data.

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