scholarly journals SAR and Optical Data Comparison for Detecting Co-Seismic Slip and Induced Phenomena during the 2018 Mw 7.5 Sulawesi Earthquake

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3976 ◽  
Author(s):  
Marco Polcari ◽  
Cristiano Tolomei ◽  
Christian Bignami ◽  
Salvatore Stramondo
Keyword(s):  
Synthetic Aperture Radar ◽  
Seismic Event ◽  
Ground Deformation ◽  
Displacement Component ◽  
Synthetic Aperture ◽  
Optical Data ◽  
The North ◽  
Optical Images ◽  
Intensity Images ◽  
Aperture Radar

We use both Synthetic Aperture Radar (SAR) and Optical data to constrain the co-seismic ground deformation produced by the 2018 Mw 7.5 Sulawesi earthquake. We exploit data processing techniques mainly based on pixel cross-correlation approach, applied to Synthetic Aperture Radar (SAR) and optical images to estimate the North–South (NS) displacement component. This component is the most significant because of the NNW–SSE geometry of the fault responsible for the seismic event, i.e., the Palu-Koro fault, characterized by a strike-slip faulting mechanism. Our results show a good agreement between the different data allowing to clearly identify the surface rupture due to the fault slip. Moreover, we use SAR and optical intensity images to investigate several secondary phenomena generated by the seismic event such as tsunami, landslides, and coastal retreat. Finally, we discuss differences between SAR and optical outcomes showing strengths and disadvantages of each one according to the investigated phenomenon.

scholarly journals Removal of systematic seasonal atmospheric signal from interferometric synthetic aperture radar ground deformation time series

2014 ◽  
Vol 41 (17) ◽  
pp. 6123-6130 ◽  
Author(s):  
Sergey V. Samsonov ◽  
Alexander P. Trishchenko ◽  
Kristy Tiampo ◽  
Pablo J. González ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Synthetic Aperture Radar ◽  
Ground Deformation ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Aperture Radar

scholarly journals Multi-Sensor InSAR Analysis of Progressive Land Subsidence over the Coastal City of Urayasu, Japan

2018 ◽  
Vol 10 (8) ◽  
pp. 1304 ◽  
Author(s):  
Yusupujiang Aimaiti ◽  
Fumio Yamazaki ◽  
Wen Liu
Keyword(s):  
Synthetic Aperture Radar ◽  
Survey Data ◽  
Land Subsidence ◽  
Ground Deformation ◽  
Tohoku Earthquake ◽  
Synthetic Aperture ◽  
Alos Palsar ◽  
The 2011 Tohoku Earthquake ◽  
L Band ◽  
Aperture Radar

In earthquake-prone areas, identifying patterns of ground deformation is important before they become latent risk factors. As one of the severely damaged areas due to the 2011 Tohoku earthquake in Japan, Urayasu City in Chiba Prefecture has been suffering from land subsidence as a part of its land was built by a massive land-fill project. To investigate the long-term land deformation patterns in Urayasu City, three sets of synthetic aperture radar (SAR) data acquired during 1993–2006 from European Remote Sensing satellites (ERS-1/-2 (C-band)), during 2006–2010 from the Phased Array L-band Synthetic Aperture Radar onboard the Advanced Land Observation Satellite (ALOS PALSAR (L-band)) and from 2014–2017 from the ALOS-2 PALSAR-2 (L-band) were processed by using multitemporal interferometric SAR (InSAR) techniques. Leveling survey data were also used to verify the accuracy of the InSAR-derived results. The results from the ERS-1/-2, ALOS PALSAR and ALOS-2 PALSAR-2 data processing showed continuing subsidence in several reclaimed areas of Urayasu City due to the integrated effects of numerous natural and anthropogenic processes. The maximum subsidence rate of the period from 1993 to 2006 was approximately 27 mm/year, while the periods from 2006 to 2010 and from 2014 to 2017 were approximately 30 and 18 mm/year, respectively. The quantitative validation results of the InSAR-derived deformation trend during the three observation periods are consistent with the leveling survey data measured from 1993 to 2017. Our results further demonstrate the advantages of InSAR measurements as an alternative to ground-based measurements for land subsidence monitoring in coastal reclaimed areas.

scholarly journals Production-Induced Subsidence at the Los Humeros Geothermal Field Inferred from PS-InSAR

Geofluids ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Eszter Békési ◽  
Peter A. Fokker ◽  
Joana E. Martins ◽  
Jon Limberger ◽  
Damien Bonté ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Geothermal Field ◽  
Synthetic Aperture ◽  
Fluid Extraction ◽  
Volume Changes ◽  
Geomechanical Properties ◽  
Reservoir Compartmentalization ◽  
Aperture Radar

Surface deformation due to fluid extraction can be detected by satellite-based geodetic sensors, providing important insights on subsurface geomechanical properties. In this study, we use Differential Interferometric Synthetic Aperture Radar (DInSAR) observations to measure ground deformation due to fluid extraction at the Los Humeros Geothermal Field (Puebla, Mexico). Our main goal is to reveal the pressure distribution in the reservoir and to identify reservoir compartmentalization, which can be important aspects for optimizing the production of the field. The result of the PS-InSAR (Persistent Scatterer by Synthetic Aperture Radar Interferometry) analysis shows that the subsidence at the LHGF was up to 8 mm/year between April 2003 and March 2007, which is small relative to the produced volume of 5×106 m3/year. The subsidence pattern indicates that the geothermal field is controlled by sealing faults separating the reservoir into several blocks. To assess if this is the case, we relate surface movements with volume changes in the reservoir through analytical solutions for different types of nuclei of strain. We constrain our models with the movements of the PS points as target observations. Our models imply small volume changes in the reservoir, and the different nuclei of strain solutions differ only slightly. These findings suggest that the pressure within the reservoir is well supported and that reservoir recharge is taking place.

APPLIED USE OF HIGH RESOLUTION IMAGERY FOR HUMAN SAFETY AND ENVIRONMENT IN SOUTH SUMATRA, INDONESIA

2005 ◽  
Vol 2005 (1) ◽  
pp. 819-823
Author(s):  
Sarah Terry ◽  
Khalid A. Soofi ◽  
Yuli Kwenandar ◽  
Bill Mcintosh
Keyword(s):  
High Resolution ◽  
Synthetic Aperture Radar ◽  
Spectral Resolution ◽  
Oil And Gas ◽  
Synthetic Aperture ◽  
Vegetation Types ◽  
Response Planning ◽  
Optical Images ◽  
Human Habitat ◽  
Aperture Radar

ABSTRACT The availability of extremely high resolution images offers an unprecedented opportunity to use such images to monitor, maintain and ultimately preserve and rehabilitate the natural environment throughout the life cycle of oil and gas projects. The variety of images available range from optical images such as Landsat ETM1 imagery (14.25 meter/pixel), IKONOS2 imagery (1 meter/pixel) and QuickBird3 imagery (0.6 meter/pixel). These optical images have sufficient spatial and spectral resolution to detect different vegetation types (e.g. old growth vs. new plantations), cleared vegetation caused by logging or human habitat expansion, burned areas due to fire and vegetation stress caused by spills from oil pipelines or storage vessels. These images are also useful for identifying potential pollutant sources such as abandoned wells, old drilling pits or other remediation targets, as well as potential pollutant receptors. Areas which have perpetual cloud cover, such as South Sumatra, of Indonesia, can be monitored using Synthetic Aperture Radar (e.g. European Space Agency's Synthetic Aperture Radar and RadarSat International of Canada). Although a typical SAR does not have the spectral resolution of optical sensors, it does have the advantage of seeing through clouds. The radar backscatter is sensitive to surface roughness and Dielectric Constant which can be used quite effectively to discriminate major vegetation types. These images, when combined with normal GIS tools, take us beyond simple monitoring, to generating predictive tools for planning future sites for drilling wells and placement of facilities such as pipelines and roads. This paper will focus on the use of these techniques for oil spill response planning in South Sumatra, while taking note of other applications of remote sensing and GIS to oil and gas operations in the regional environment.

The Application of PS-InSAR Technology on Land Subsidence in Cangzhou Region

2011 ◽  
Vol 268-270 ◽  
pp. 1934-1939
Author(s):  
Kun Chao Lei ◽  
Hui Li Gong ◽  
Xiao Juan Li ◽  
Bei Bei Chen ◽  
Ji Wei Li ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Land Subsidence ◽  
Radar Data ◽  
Ground Movement ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
The North ◽  
Permanent Scatterers ◽  
Satellite Radar ◽  
Aperture Radar

Land subsidence in Cangzhou of the North China Plain, has been an ongoing problem for the past four decades (since the later 1970s). With the development of new synthetic aperture radar(SAR)sensors and interferometric synthetic aperture radar(InSAR) techniques, the application of satellite Radar data have enhanced capabilities to detect and monitor ground displacements with centimeter to millimeter precision at greater spatial detail and higher temporal resolution. We use Permanent Scatterers interferometric synthetic aperture radar（PS-InSAR）technology (Hooper, A.2004) to detect and measure ground movement in this area（from2004 to 2007）. Results of the cangzhou region study are reported and the utility of the InSAR methodology is discussed.

scholarly journals Artificial Neural Network Modeling of High Arctic Phytomass Using Synthetic Aperture Radar and Multispectral Data

2021 ◽  
Author(s):  
Adam Collingwood ◽  
Paul Treitz ◽  
Francois Charbonneau ◽  
David M. Atkinson
Keyword(s):  
Synthetic Aperture Radar ◽  
High Arctic ◽  
Synthetic Aperture ◽  
The Arctic ◽  
Optical Data ◽  
Neural Network Modeling ◽  
Artificial Neural ◽  
Sar Data ◽  
The Relationship ◽  
Aperture Radar

Vegetation in the Arctic is often sparse, spatially heterogeneous, and difficult to model. Synthetic Aperture Radar (SAR) has shown some promise in above-ground phytomass estimation at sub-arctic latitudes, but the utility of this type of data is not known in the context of the unique environments of the Canadian High Arctic. In this paper, Artificial Neural Networks (ANNs) were created to model the relationship between variables derived from high resolution multi-incidence angle RADARSAT-2 SAR data and optically-derived (GeoEye-1) Soil Adjusted Vegetation Index (SAVI) values. The modeled SAVI values (i.e., from SAR variables) were then used to create maps of above-ground phytomass across the study area. SAVI model results for individual ecological classes of polar semi-desert, mesic heath, wet sedge, and felsenmeer were reasonable, with r2 values of 0.43, 0.43, 0.30, and 0.59, respectively. When the outputs of these models were combined to analyze the relationship between the model output and SAVI as a group, the r2 value was 0.60, with an 8% normalized root mean square error (% of the total range of phytomass values), a positive indicator of a relationship. The above-ground phytomass model also resulted in a very strong relationship (r2 = 0.87) between SAR-modeled and field-measured phytomass. A positive relationship was also found between optically derived SAVI values and field measured phytomass (r2 = 0.79). These relationships demonstrate the utility of SAR data, compared to using optical data alone, for modeling above-ground phytomass in a high arctic environment possessing relatively low levels of vegetation.

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