scholarly journals Discrimination of glacier facies using multi-temporal SAR data

1998 ◽  
Vol 44 (146) ◽  
pp. 42-53 ◽  
Author(s):  
K. C. Partington
Keyword(s):  
European Space Agency ◽  
Greenland Ice Sheet ◽  
Sensor Calibration ◽  
Lower Altitude ◽  
Mount Pinatubo ◽  
South Central ◽  
Space Agency ◽  
Wet Snow ◽  
Multi Temporal ◽  
Sar Data

AbstractGlacier facies from the Greenland ice sheet and the Wrangell-St Elias Mountains, Alaska, are analyzed using multi-temporal synthetic aperture radar (SAR) data from the European Space Agency ERS-1 satellite. Distinct zones and facies are visible in multi-temporal SAR data, including the dry-snow facies, the combined percolation and wet-snow facies, the ice facies, transient melt areas and moraine. In Greenland and south-central Alaska, very similar multi-temporal signatures are evident for the same facies, although these facies are found at lower altitude in West Greenland where the equilibrium line appears to be found at sea level at 71°30?N during the year analyzed (1992-93), probably because of the cooling effect of the eruption of Mount Pinatubo. In Greenland, both the percolation and dry-snow facies are excellent distributed targets for sensor calibration, with backscatter coefficients stable to within 0.2 dB. However, the percolation facies near the top of Mount Wrangell are more complex and less easily delineated than in Greenland, and at high altitude the glacier facies have a multi-temporal signature which depends sensitively on slope orientation.

scholarly journals Discrimination of glacier facies using multi-temporal SAR data

1998 ◽  
Vol 44 (146) ◽  
pp. 42-53 ◽  
Author(s):  
K. C. Partington
Keyword(s):  
European Space Agency ◽  
Greenland Ice Sheet ◽  
Sensor Calibration ◽  
Lower Altitude ◽  
Mount Pinatubo ◽  
South Central ◽  
Space Agency ◽  
Wet Snow ◽  
Multi Temporal ◽  
Sar Data

AbstractGlacier facies from the Greenland ice sheet and the Wrangell-St Elias Mountains, Alaska, are analyzed using multi-temporal synthetic aperture radar (SAR) data from the European Space Agency ERS-1 satellite. Distinct zones and facies are visible in multi-temporal SAR data, including the dry-snow facies, the combined percolation and wet-snow facies, the ice facies, transient melt areas and moraine. In Greenland and south-central Alaska, very similar multi-temporal signatures are evident for the same facies, although these facies are found at lower altitude in West Greenland where the equilibrium line appears to be found at sea level at 71°30?N during the year analyzed (1992-93), probably because of the cooling effect of the eruption of Mount Pinatubo. In Greenland, both the percolation and dry-snow facies are excellent distributed targets for sensor calibration, with backscatter coefficients stable to within 0.2 dB. However, the percolation facies near the top of Mount Wrangell are more complex and less easily delineated than in Greenland, and at high altitude the glacier facies have a multi-temporal signature which depends sensitively on slope orientation.

scholarly journals EXPLORING CLOUD-BASED PLATFORMS FOR RAPID INSAR TIME SERIES ANALYSIS

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 171-176
Author(s):  
A. Piter ◽  
M. Vassileva ◽  
M. Haghshenas Haghighi ◽  
M. Motagh
Keyword(s):  
European Space Agency ◽  
Global Scale ◽  
Synthetic Aperture ◽  
Deformation Analysis ◽  
Limiting Factor ◽  
Time Deformation ◽  
Space Agency ◽  
Multi Temporal ◽  
Sar Data ◽  
Interferometric Sar

Abstract. The idea of near real-time deformation analysis using Synthetic Aperture Radar (SAR) data as a response to natural and anthropogenic disasters has been an interesting topic in the last years. A major limiting factor for this purpose has been the non-availability of both spatially and temporally homogeneous SAR datasets. This has now been resolved thanks to the SAR data provided by the Sentinel-1A/B missions, freely available at a global scale via the Copernicus program of the European Space Agency (ESA). Efficient InSAR analysis in the era of Sentinel demands working with cloud-based platforms to tackle problems posed by large volumes of data. In this study, we explore a variety of existing cloud-based platforms for Multi-Temporal Interferometric SAR (MTI) analysis and discuss their opportunities and limitations.

scholarly journals Using airborne Ku-band altimeter waveforms to investigate winter accumulation and glacier facies on Austfonna, Svalbard

2013 ◽  
Vol 59 (217) ◽  
pp. 893-899 ◽  
Author(s):  
Robert L. Hawley ◽  
Ola Brandt ◽  
Thorben Dunse ◽  
Jon Ove Hagen ◽  
Veit Helm ◽  
...  
Keyword(s):  
Snow Depth ◽  
European Space Agency ◽  
Synthetic Aperture Radar Image ◽  
Altimeter Data ◽  
Radar Altimeter ◽  
Ice Caps ◽  
Ice Cap ◽  
Space Agency ◽  
Wet Snow ◽  
Airborne Sar

AbstractWinter balance is an important metric for assessing the change on glaciers and ice caps, yet measuring it using ground-based techniques can be challenging. We use the European Space Agency prototype Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) to extract snow depths from the received altimeter waveforms over Austfonna ice cap, Svalbard. Additionally, we attempt to distinguish the long-term firn area from other glacier facies. We validate our results using snow depth and glacier facies characterizations determined from ground-based radar profiles, snow pits and a multi-look satellite synthetic aperture radar image. We show that the depth of the winter snowpack can be extracted from the altimeter data over most of the accumulation zone, comprising wet snow zone and a superimposed ice zone. The method struggles at lower elevations where internal reflections within the winter snowpack are strong and the winter snow depth is less than ∼1 m. We use the abruptness of the reflection from the last summer surface (LSS) to attempt to distinguish glacier facies. While there is a general correlation between LSS abruptness and glacier facies, we do not find a relationship that warrants a distinct classification based on ASIRAS waveforms alone.

scholarly journals Impact of MODIS sensor calibration updates on Greenland ice sheet surface reflectance and albedo trends

2017 ◽  
Author(s):  
Kimberly A. Casey ◽  
Chris M. Polashenski ◽  
Justin Chen ◽  
Marco Tedesco
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Sensor Calibration ◽  
Surface Reflectance ◽  
Product Analysis ◽  
Modis Data ◽  
Albedo Change ◽  
Wet Snow ◽  
Sensor Degradation ◽  
Lower Magnitude

Abstract. We evaluate Greenland Ice Sheet (GrIS) surface reflectance and albedo trends using the newly released Collection 6 (C6) MODIS products over the period 2001–2016. We find that the correction of MODIS sensor degradation provided in the new C6 data products reduces the magnitude of the surface reflectance and albedo decline trends obtained from previous MODIS data (i.e. Collection 5, C5). Collection 5 and 6 data product analysis over GrIS is characterized by surface (i.e. wet vs. dry) and elevation (i.e. 500 m–2000 m, 2000 m and greater) conditions over the summer season from June 1–August 31. Notably, the visible-wavelength declining reflectance trends identified in several bands MODIS C5 data from previous studies are only slightly detected, at reduced magnitude in the C6 versions over the dry snow zone. Wet snow albedo decline over the MODIS record remains in the C6 product, albeit at a lower magnitude than obtained using C5 data. Further analysis of C6 spectral reflectance trends show both reflectance increases and decreases in select bands and regions, suggesting that several competing processes are contributing to ice sheet albedo change. Investigators using MODIS data in other fields may consider similar re-examinations of trends previously established using C5 data.

scholarly journals MARRYING DEEP LEARNING AND DATA FUSION FOR ACCURATE SEMANTIC LABELING OF SENTINEL-2 IMAGES

2021 ◽  
Vol V-3-2021 ◽  
pp. 101-107
Author(s):  
G. Fonteix ◽  
M. Swaine ◽  
M. Leras ◽  
Y. Tarabalka ◽  
S. Tripodi ◽  
...  
Keyword(s):  
Deep Learning ◽  
European Space Agency ◽  
External Source ◽  
Convolutional Network ◽  
Spectral Bands ◽  
Space Agency ◽  
Semantic Labeling ◽  
Multi Temporal ◽  
Correction Step ◽  
Sentinel 2

Abstract. The understanding of the Earth through global land monitoring from satellite images paves the way towards many applications including flight simulations, urban management and telecommunications. The twin satellites from the Sentinel-2 mission developed by the European Space Agency (ESA) provide 13 spectral bands with a high observation frequency worldwide. In this paper, we present a novel multi-temporal approach for land-cover classification of Sentinel-2 images whereby a time-series of images is classified using fully convolutional network U-Net models and then coupled by a developed probabilistic algorithm. The proposed pipeline further includes an automatic quality control and correction step whereby an external source can be introduced in order to validate and correct the deep learning classification. The final step consists of adjusting the combined predictions to the cloud-free mosaic built from Sentinel-2 L2A images in order for the classification to more closely match the reference mosaic image.

The 4DGreenland project: Greenland hydrology assessment from remote sensing

2021 ◽  
Author(s):  
Louise Sandberg Sørensen ◽  
Keyword(s):  
European Space Agency ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Regional Warming ◽  
Supraglacial Lakes ◽  
Space Agency ◽  
Subglacial Lakes ◽  
Global Sea Level ◽  
Project Objectives ◽  
Response To Temperature

<p>The high latitudes of the Northern Hemisphere have experienced the largest regional warming over the last decades. On the Greenland ice sheet, rapid changes are observed in response to temperature increase, with the amount of liquid water at the surface particularly increasing. Understanding Greenland’s ice sheet hydrology is essential to assess  its contribution to global sea-level rise in a future warming climate.</p><p>With the objective of maximizing the use of Earth Observation (EO) data, the European Space Agency (ESA) has funded the 2-year project 4DGreenland (https://4dgreenland.eo4cryo.dk/) to assess and quantify the hydrology of the Greenland ice sheet. The project is focused on dynamic variations in the hydrological components of the ice sheet, and on quantifying the water fluxes between reservoirs including surface melt, supraglacial lakes and rivers, and subglacial melt and lakes. Efforts will focus on a thorough analysis of various components of the hydrological network in selected test regions and their impact on ice sheet flow. 4DGreenland started in September 2020. Here, we will present the project objectives, methods, and show initial results obtained within the project such as a comparison of supraglacial lake depths from optical imagery and ICESat-2 altimetry data, estimation of basal melt water production, and identification and mapping of surface meltwater presence and subglacial lakes from EO data.</p><p> </p>

Assessing the RST_VOLC algorithm implementation on infrared Sentinel 3 SLSTR data

2020 ◽  
Author(s):  
Alfredo Falconieri ◽  
Francesco Marchese ◽  
Giuseppe Mazzeo ◽  
Nicola Pergola ◽  
Valerio Tramutoli
Keyword(s):  
Land Surface ◽  
European Space Agency ◽  
Space Agency ◽  
Mt Etna ◽  
Multi Temporal ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
New Generation ◽  
Algorithm Implementation

<p>RSTVOLC is a multi-temporal algorithm developed for detecting volcanic hotspots that was successfully used to monitor active volcanoes located in different geographic areas exploiting both polar and geostationary satellite data. The algorithm runs operationally at the Institute of Methodologies for Environmental Analysis (IMAA) to monitor Italian volcanoes in near-real time by means of Advanced Very-High-Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data. In this study, we assess the possible RSTVOLC implementation on data from the Sea and Land Surface Temperature Radiometer (SLSTR). The latter is a new generation sensor flying onboard the ESA (European Space Agency) Sentinel-3 mission, offering some spectral channels in the infrared bands particularly suited to identify high temperature surfaces such as lava flows. Here, we verify the RSTVOLC implementation on SLSTR data despite the absence of a multiannual time series of satellite records, by using synthetic spectral reference fields. Results achieved by investigating recent eruptions of Mt. Etna and Stromboli (Italy) volcanoes are presented and discussed.</p>

scholarly journals SBAS-DlnSAR monitoring of subsidence induced by extracting brine from an underground salt deposit in Tuzla, Bosnia and Herzegovina

2020 ◽  
Vol 153 ◽  
pp. 03007
Author(s):  
I Nyoman Sudi Parwata ◽  
Norikazu Shimizu ◽  
Bojana Grujić ◽  
Sabid Zekan ◽  
Ruža Čeliković ◽  
...  
Keyword(s):  
Bosnia And Herzegovina ◽  
European Space Agency ◽  
Salt Deposit ◽  
Underground Brine ◽  
Space Agency ◽  
Multi Temporal ◽  
Small Baseline Subset ◽  
Small Baseline ◽  
Subsidence Monitoring ◽  
The City

Tuzla City, Bosnia and Herzegovina, is very famous for salt mining. The intensive extraction of brine from the underground salt deposit caused accumulative subsidence of up to -12 m from 1956 to 2003. It induced serious damage to residences, buildings, and infrastructures. Although the activity of brine extraction was officially stopped in 2007, reports of subsidence are still on-going for some areas of Tuzla City according to a previous study. In the present study, a satellite-based method, i.e., Differential Synthetic Aperture Radar (DInSAR), is applied for the subsidence monitoring of the induced underground brine extraction. Since October 2014, SAR data obtained by the Sentinel-1A and -1B satellites (European Space Agency: ESA) and Small Baseline Subset (SBAS) multi-temporal analyses have been employed to obtain the spatial distribution and the temporal transition of the land subsidence. The accuracy and effectiveness of the SBAS-DInSAR method are assessed and evaluated by using the real-time kinematic GNSS monitoring system. DInSAR detected that the subsidence is still on-going at a velocity of -36.4 mm/year in some areas, especially in an area northeast of the center of the city. This study presents the validity and effectiveness of SBAS-DInSAR as a useful subsidence monitoring tool.

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 PERSISTENT SCATTERER INTERFEROMETRY USING SENTINEL-1 DATA

2016 ◽  
Vol XLI-B7 ◽  
pp. 835-839 ◽  
Author(s):  
M. Crosetto ◽  
O. Monserrat ◽  
N. Devanthéry ◽  
M. Cuevas-González ◽  
A. Barra ◽  
...  
Keyword(s):  
Case Studies ◽  
Urban Area ◽  
European Space Agency ◽  
Deformation Monitoring ◽  
Persistent Scatterer Interferometry ◽  
Space Agency ◽  
Persistent Scatterer ◽  
Sar Data ◽  
Interferometric Sar ◽  
High Coherence

This paper is focused on deformation monitoring using a Persistent Scatterer Interferometry technique and the interferometric SAR data acquired by the Sentinel-1 satellite of the European Space Agency. The first part of the paper describes the procedure used to process and analyze Sentinel-1 interferometric SAR data. Two main approaches are described. The first one is a simplified Persistent Scatterer Interferometry approach that exploits two key properties of the Sentinel-1 data: the high coherence of the 12-day interferograms and the reduced orbital tube. The second approach is a full Persistent Scatterer Interferometry approach, where a more sophisticate data treatment is employed. The second part of the paper illustrates the results obtained with the two processing approaches. Two case studies are described. The first one concerns landslide detection and monitoring. In this case, the simplified Persistent Scatterer Interferometry approach was used. The second one regards the deformation monitoring of an urban area. In this case, a full Persistent Scatterer Interferometry approach was used.

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