scholarly journals Analysis of synthetic aperture radar Data collected over the southwestern Greenland ice sheet

1993 ◽  
Vol 39 (131) ◽  
pp. 119-132 ◽  
Author(s):  
K. C. Jezek ◽  
M. R. Drinkwater ◽  
J. P. Crawford ◽  
R. Bindschadler ◽  
R. Kwok
Keyword(s):  
Synthetic Aperture Radar ◽  
Large Scale ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Synthetic Aperture ◽  
Model Calculations ◽  
Synthetic Aperture Radar Data ◽  
Surface Patterns ◽  
Sar Data ◽  
Aperture Radar

AbstractAnalyses of the first aircraft multi-frequency, Polarimetric synthetic aperture radar (SAR) data acquired over the southwestern Greenland ice sheet are presented. Data were collected on 31 August 1989 by the Jet Propulsion Laboratory SAR using the NASA DC-8 aircraft. Along with curvilinear patterns associated with large-scale morphologic features such as crevasses, lakes and streams, frequency and polarization dependencies are observed in the P-, L-and C-band image products. Model calculations that include firn grain-size and volumetric water content suggest that tonal variations in and between the images are attributable to large-scale variations in the snow-and ice-surface characteristics, especially snow wetness. In particular, systematic trends in back-scatter strength observed at C-band across regions of changing snow wetness are suggestive of a capability to delineate boundaries between snow facies. Ice lenses and ice pipes are the speculated cause for similar trends in P-band back-scatter. Finally, comparison between SEASAT SAR data collected in 1978 and these airborne data collected in 1989 indicate a remarkable stability of surface patterns associated with the locations of supraglacial lake and stream systems.

scholarly journals Analysis of synthetic aperture radar Data collected over the southwestern Greenland ice sheet

1993 ◽  
Vol 39 (131) ◽  
pp. 119-132 ◽  
Author(s):  
K. C. Jezek ◽  
M. R. Drinkwater ◽  
J. P. Crawford ◽  
R. Bindschadler ◽  
R. Kwok
Keyword(s):  
Synthetic Aperture Radar ◽  
Large Scale ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Synthetic Aperture ◽  
Model Calculations ◽  
Synthetic Aperture Radar Data ◽  
Surface Patterns ◽  
Sar Data ◽  
Aperture Radar

AbstractAnalyses of the first aircraft multi-frequency, Polarimetric synthetic aperture radar (SAR) data acquired over the southwestern Greenland ice sheet are presented. Data were collected on 31 August 1989 by the Jet Propulsion Laboratory SAR using the NASA DC-8 aircraft. Along with curvilinear patterns associated with large-scale morphologic features such as crevasses, lakes and streams, frequency and polarization dependencies are observed in the P-, L-and C-band image products. Model calculations that include firn grain-size and volumetric water content suggest that tonal variations in and between the images are attributable to large-scale variations in the snow-and ice-surface characteristics, especially snow wetness. In particular, systematic trends in back-scatter strength observed at C-band across regions of changing snow wetness are suggestive of a capability to delineate boundaries between snow facies. Ice lenses and ice pipes are the speculated cause for similar trends in P-band back-scatter. Finally, comparison between SEASAT SAR data collected in 1978 and these airborne data collected in 1989 indicate a remarkable stability of surface patterns associated with the locations of supraglacial lake and stream systems.

scholarly journals Spaceborne L-Band Synthetic Aperture Radar Data for Geoscientific Analyses in Coastal Land Applications: A Review

2020 ◽  
Vol 12 (14) ◽  
pp. 2228
Author(s):  
Marco Ottinger ◽  
Claudia Kuenzer
Keyword(s):  
Synthetic Aperture Radar ◽  
Anthropogenic Impacts ◽  
Continuous Mapping ◽  
Synthetic Aperture ◽  
Comprehensive Overview ◽  
Synthetic Aperture Radar Data ◽  
L Band ◽  
Sar Data ◽  
Coastal Land ◽  
Aperture Radar

The coastal zone offers among the world’s most productive and valuable ecosystems and is experiencing increasing pressure from anthropogenic impacts: human settlements, agriculture, aquaculture, trade, industrial activities, oil and gas exploitation and tourism. Earth observation has great capability to deliver valuable data at the local, regional and global scales and can support the assessment and monitoring of land- and water-related applications in coastal zones. Compared to optical satellites, cloud-cover does not limit the timeliness of data acquisition with spaceborne Synthetic Aperture Radar (SAR) sensors, which have all-weather, day and night capabilities. Hence, active radar systems demonstrate great potential for continuous mapping and monitoring of coastal regions, particularly in cloud-prone tropical and sub-tropical climates. The canopy penetration capability with long radar wavelength enables L-band SAR data to be used for coastal terrestrial environments and has been widely applied and investigated for the following geoscientific topics: mapping and monitoring of flooded vegetation and inundated areas; the retrieval of aboveground biomass; and the estimation of soil moisture. Human activities, global population growth, urban sprawl and climate change-induced impacts are leading to increased pressure on coastal ecosystems causing land degradation, deforestation and land use change. This review presents a comprehensive overview of existing research articles that apply spaceborne L-band SAR data for geoscientific analyses that are relevant for coastal land applications.

scholarly journals Quantification of oil lost from tanker vessel using space borne radar datasets - Case study of Haldia port oil spill, July 2018.

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
S.J Prasad ◽  
T.M. Balakrishnan Nair
Keyword(s):  
Synthetic Aperture Radar ◽  
Oil Spill ◽  
European Space Agency ◽  
Fuel Oil ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Data ◽  
Space Agency ◽  
Sar Data ◽  
Spilled Oil ◽  
Aperture Radar

Abstract 686884 Determining the spilled volume of the marine oil pollutant is an essential requisite for the oil spill modellers and the responders. Generally, the mass of the spilled pollutant is computed from the total quantity and the remaining quantity of the storage tank of the distressed vessel. A method to estimate the quantity of the spilled oil pollutant using the space -borne synthetic aperture radar dataset is elaborated here. The synthetic aperture radar data, its ability to penetrate cloud cover, irrespective of weather conditions, has been widely used to detect the signature of spilt oil. SAR data available from European Space Agency and Canadian Space Agency were used to detect the oil spills as they are proved to be appropriate for oil spill detection. Minor oil spill occured off Haldia Port, off Kolkata from SSL tanker vessel on 14 July 2018. The geographical location of the distressed vessel is 88.775 ′E, 21.441 ′N. The zone of the vessel distress was monitored for oil slicks. The acquisition plan of the Radar satellite Sentinel -1A was obtained from European Space Agency. As per that, the pass of the Sentinel -1A was available on 15 July 2018 and 17 July 2018 for the region of study. The Synthetic Aperture Radar (SAR) datasets were obtained from Sentinel -1A as per their availability. Those datasets were processed using Sentinel Application Platform (SNAP) tool box. The SAR data is subjected to terrain correction, which automatically reprojects the radar scene. The next stage is performing radiometric calibration, which converts the amplitude into intensity values. The radar reflectance values are converted to Sigma0 intensity values in Sentinel tool box. This Sigma0 values were wrote in netcdf format for identifying the oil slicks. The pixels of lesser intensity values are identified and are interpreted for oil slicks. The zone of the oil slicks in the radar scene are considered as irregular polygons. The area of those polygons were computed. Later the volume of the spilled oil is computed using the thickness of the spilled oil pollutant. Finally the mass of the pollutant is computed. It was collectively estimated from the SAR datasets, that, 33 Tons of Fuel oil was lost from SSL vessel that sank off Haldia Port. This paper elaborates in detail about the method of processing SAR dataset and estimating the quantity of oil lost from the vessel using SAR datasets.

scholarly journals Detection and Characterization of Active Landslides with Multisource SAR Data and Remote Sensing in Western Guizhou, China

2021 ◽  
Author(s):  
Yifei Zhu ◽  
Xin YAO ◽  
Leihua Yao ◽  
Chuangchuang Yao
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Large Scale ◽  
Slope Failure ◽  
Surface Deformation ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Data ◽  
Developmental Patterns ◽  
Mining Disturbance ◽  
Aperture Radar

Abstract The western part of Guizhou is located in the second step of East Asia. Although the area is stratigraphically continuous and the surface is dominated by hard limestone and sandstone, catastrophic landslides often occur, seriously threatening residents' lives and the safety of property. Accurate identification of landslides and analysis of their developmental patterns are vital to prevent and reduce the threat of geological disasters. No active landslide survey data cover this region, so this paper identifies the active landslides in the western part of Guizhou by combining surface deformation information, multitemporal optical remote sensing images, geological lithology, and geomorphic features to obtain deformation information from multisource synthetic aperture radar surface data. This process increases the accuracy and reliability of identifying unstable slopes in areas with dense vegetation and steep terrain. By processing 283 Sentinel-1 and PALSAR-2 synthetic aperture radar data, 588 active landslides, 18 of which are high-risk large-scale landslides (landslide groups), are delineated for the first time in a range of 4.64x104 km2 in the study area. The active landslides mainly include resurrected ancient landslides, reservoir/riverbank landslides, and mining-induced landslides, accounting for 2.4%, 4.1%, and 91.8%, respectively. The spatial distribution of landslides is banded along the cuesta at the edge of an outcrop of coal strata. Landslides are mainly distributed at elevations of 1800–2000 m, with an elevation difference of 50 ~ 100 m and a slope range of 35°~40°. The landslides are characterized by steep slopes, small scales, mass occurrences, and no dominant slope direction, classifying them as cuesta landslides induced by mining disturbance. Furthermore, nuanced remote sensing interpretation of the disaster elements, such as cuesta cliff, tensile cracks, deep and sizeable tensile channels, isolated rock masses, and collapse debris, and their processes of change, reveals that coal mining-disturbed landslides in this region have experienced four primary stages: natural unloading, mining disturbance, displacement acceleration, and slope failure. This is of great significance for understanding the genetic mechanism and developmental patterns, as well as the risk assessment, of this region.

scholarly journals Automatic delineation of glacier grounding lines in differential interferometric synthetic-aperture radar data using deep learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yara Mohajerani ◽  
Seongsu Jeong ◽  
Bernd Scheuchl ◽  
Isabella Velicogna ◽  
Eric Rignot ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Large Scale ◽  
Numerical Models ◽  
Radar Data ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Synthetic Aperture Radar Data ◽  
Uncertainty Estimates ◽  
Grounding Line ◽  
Aperture Radar

AbstractDelineating the grounding line of marine-terminating glaciers—where ice starts to become afloat in ocean waters—is crucial for measuring and understanding ice sheet mass balance, glacier dynamics, and their contributions to sea level rise. This task has been previously done using time-consuming, mostly-manual digitizations of differential interferometric synthetic-aperture radar interferograms by human experts. This approach is no longer viable with a fast-growing set of satellite observations and the need to establish time series over entire continents with quantified uncertainties. We present a fully-convolutional neural network with parallel atrous convolutional layers and asymmetric encoder/decoder components that automatically delineates grounding lines at a large scale, efficiently, and accompanied by uncertainty estimates. Our procedure detects grounding lines within 232 m in 100-m posting interferograms, which is comparable to the performance achieved by human experts. We also find value in the machine learning approach in situations that even challenge human experts. We use this approach to map the tidal-induced variability in grounding line position around Antarctica in 22,935 interferograms from year 2018. Along the Getz Ice Shelf, in West Antarctica, we demonstrate that grounding zones are one order magnitude (13.3 ± 3.9) wider than expected from hydrostatic equilibrium, which justifies the need to map grounding lines repeatedly and comprehensively to inform numerical models.

scholarly journals EXTENT MAPPING OF A MAJOR FLOODING EVENT ON THE ISLAND OF TRINIDAD USING SPACE-BORNE SYNTHETIC APERTURE RADAR

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 527-530
Author(s):  
D. Ramsewak ◽  
B. Maharaj
Keyword(s):  
Synthetic Aperture Radar ◽  
Large Scale ◽  
Anthropogenic Activities ◽  
Synthetic Aperture ◽  
Remotely Sensed Data ◽  
Threshold Method ◽  
Flooding Event ◽  
Sar Data ◽  
Flooding Events ◽  
Aperture Radar

Abstract. Flooding events around the world have been increasing both in their occurrence and their intensities within recent decades. Studies have shown that this is most likely linked to climate change effects and anthropogenic activities that lead to pollution. Irrespective of the cause, floods incur massive economic and human losses. Synoptic data on flooding events help to support the planning and management efforts during this disaster event. Remotely sensed data, particularly from satellites is useful for mapping and monitoring large scale flooding events. More specifically, synthetic aperture radar (SAR) allows for data acquisition despite the interference of clouds and other atmospheric elements such as fog, light rain and mist. This study utilized SAR data from the Sentinel–1 satellite to map a major flooding event on the island of Trinidad which occurred during October 18–21, 2018. The peak of the flooding was estimated to have occurred on October 20, 2018. The SAR images were first calibrated then geometrically corrected and filtered. A threshold method was then applied to extract the inundated areas. A proprietary algorithm implemented by Geospatial Enabling Technologies (GET) and based on SNAP software, was used for processing Sentinel-1 imagery to separate the open water and non-water (land) areas from the images. Outputs were then integrated into ArcGIS 10.6 mapping software and the extents of the flooded areas were delineated based on the available data. By applying this method to a Sentinel–1 image captured on October 19, 2018 it was revealed that the total flooded area on that date was 9.94 square kilometres. This study provides a brief illustration of the value of SAR data for flood delineation and mapping but also highlights some of the limitations that can be involved when using such technology.

scholarly journals An analysis of balance velocities over the Greenland ice sheet and comparison with synthetic aperture radar interferometry

2000 ◽  
Vol 46 (152) ◽  
pp. 67-74 ◽  
Author(s):  
J. L. Bamber ◽  
R. J. Hardy ◽  
I. Joughin
Keyword(s):  
Synthetic Aperture Radar ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ablation Rate ◽  
Sar Interferometry ◽  
Synthetic Aperture ◽  
Ice Thickness ◽  
Good Representation ◽  
Elevation Model ◽  
Aperture Radar

AbstractBalance velocities for the Greenland ice sheet have been calculated from a new digital elevation model (DEM), accumulation rates and an existing ice-thickness grid, using a fully two-dimensional finite-difference scheme. The pattern of velocities is compared with velocities derived from synthetic-aperture radar (SAR) interferometry for three different regions of the ice sheet. Differences between the two estimates of velocity highlight the respective strengths and weaknesses of the datasets and techniques used. A comparison with ten global positioning system-derived velocities indicates that the balance-velocity scheme and input datasets used here provide a remarkably good representation of the velocity distribution inland from the margins. These balance-velocity data, therefore, could help constrain numerical ice-sheet models. The balance velocities were found to be unreliable close to the ice-sheet margins due to larger errors in ice thickness, surface slope and ablation rate in this region. Comparison of the balance velocities with SAR interferometry in the region of the “Northeast Greenland Ice Stream” indicates the importance of the smoothing distance that must be applied to the DEM before calculating balance velocities. A smoothing distance of 20 times the ice thickness gave good agreement between the two measures of velocity.

Monitoring the Greenland Ice Sheet: A comparison between Sentinel-3 and CryoSat-2 radar altimeters

2020 ◽  
Author(s):  
Jennifer Maddalena ◽  
Geoffrey Dawson ◽  
Stephen Chuter ◽  
Jack Landy ◽  
Jonathan Bamber
Keyword(s):  
Synthetic Aperture Radar ◽  
Volume Change ◽  
Interpolation Method ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Synthetic Aperture ◽  
Radar Altimeter ◽  
Elevation Change ◽  
Crossover Analysis ◽  
Aperture Radar

<p>Since 1992, satellite-borne radar altimetry has been used to record surface elevation change over the Greenland ice sheet (GrIS). Until the launch of CryoSat-2 in 2010, conventional radar altimeters performed poorly over high sloping terrain with heterogenous topography. The novel synthetic aperture radar interferometric (SARIn) mode of CryoSat-2 has improved capability in these regions over the margins of the GrIS, which have been experiencing the largest mass loss. ESA’s Sentinel-3 mission is the latest radar-altimeter to be launched. The first satellite, Sentinel-3A, was launched in February 2016 followed by Sentinel-3B April 2018. The Sentinel-3 satellites are the first to use synthetic aperture radar (SAR) across the interior of the GrIS. This has improved the along-track resolution to approximately 300m compared to CryoSat-2’s Low Resolution Mode (LRM) footprint which has a diameter of ~1.65km.</p><p>Here we assess the performance of Sentinel’s SAR mode compared to the LRM mode of CryoSat-2 over the interior of the ice sheet and the SARIn mode over the margins of the GrIS, through crossover analysis and a point-to-point comparison. We then assess the implications of this comparison for monitoring elevation changes over the ice sheet and we present rates of elevation change for June 2016 - June 2019 for both radar altimeter missions. To calculate rates of volume change from elevation change we use a statistical interpolation method, universal kriging, and present volume changes per basin over Greenland before comparing volume change estimates between CryoSat-2 and Sentinel-3.</p>

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