scholarly journals Building a SAR-Enabled Data Cube Capability in Australia Using SAR Analysis Ready Data

Data ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 100 ◽  
Author(s):  
Catherine Ticehurst ◽  
Zheng-Shu Zhou ◽  
Eric Lehmann ◽  
Fang Yuan ◽  
Medhavy Thankappan ◽  
...  
Keyword(s):  
European Space Agency ◽  
Shuttle Radar Topography Mission ◽  
Data Cube ◽  
Srtm Dem ◽  
Space Agency ◽  
Industrial Research Organization ◽  
The Difference ◽  
Research Alliance ◽  
Sar Analysis ◽  
Wide Swath

A research alliance between the Commonwealth Scientific and Industrial Research Organization and Geoscience Australia was established in relation to Digital Earth Australia, to develop a Synthetic Aperture Radar (SAR)-enabled Data Cube capability for Australia. This project has been developing SAR analysis ready data (ARD) products, including normalized radar backscatter (gamma nought, γ0), eigenvector-based dual-polarization decomposition and interferometric coherence, all generated from the European Space Agency (ESA) Sentinel-1 interferometric wide swath mode data available on the Copernicus Australasia Regional Data Hub. These are produced using the open source ESA SNAP toolbox. The processing workflows are described, along with a comparison of the γ0 backscatter and interferometric coherence ARD produced using SNAP and the proprietary software GAMMA. This comparison also evaluates the effects on γ0 backscatter due to variations related to: Near- and far-range look angles; SNAP’s default Shuttle Radar Topography Mission (SRTM) DEM and a refined Australia-wide DEM; as well as terrain. The agreement between SNAP and GAMMA is generally good, but also presents some systematic geometric and radiometric differences. The difference between SNAP’s default SRTM DEM and the refined DEM showed a small geometric shift along the radar view direction. The systematic geometric and radiometric issues detected can however be expected to have negligible effects on analysis, provided products from the two processors and two DEMs are used separately and not mixed within the same analysis. The results lead to the conclusion that the SNAP toolbox is suitable for producing the Sentinel-1 ARD products.

scholarly journals Mapping Snow for Area Where was Detected Ground Deplacement: A Case Studi of Iaşi County

2018 ◽  
Vol 12 (2) ◽  
pp. 167-174
Author(s):  
Paul Macarof ◽  
Cezarina Georgiana Bartic Lazăr ◽  
Florian Statescu
Keyword(s):  
Ground Deformation ◽  
European Space Agency ◽  
Vertical Displacement ◽  
Landsat 8 ◽  
Ground Displacement ◽  
Space Agency ◽  
Numerical Indicator ◽  
Normalized Difference Snow Index ◽  
Differential Radar Interferometry ◽  
Wide Swath

Abstract The main goal of this paper is to detect snow in areas where was detecting and mapping, using Differential Radar Interferometry (DInSAR) technique, ground displacement. DInSAR is a powerful tool to detect and monitor ground deformation. Iaşi county is considered as study area in this research. Study area is geographically situated on latitude 46°48’N to 47°35’N and longitude 26°29’E to 28°07’E. For this paper, to detect and mapping grond displacement, was used Sentinel – 1 images, provided free by The European Space Agency (ESA), for January 2018, with vertical polarization (VV), ascending orbit and Interferometric Wide swath (IW) mode operated. SNAP was used to process the Sentinel – 1 images. Landsat-8 OLI was taken to detect areas cover with snow using Normalized Difference Snow Index (NDSI) - a numerical indicator that shows snow cover over land areas. ArcMap was used to create NDSI map after Landsat-8 data was preprocessed. The presence of snow has been observed both in the areas where it exists vertical displacement positive and negative.

scholarly journals Soil Moisture in the Biebrza Wetlands Retrieved from Sentinel-1 Imagery

2018 ◽  
Author(s):  
Katarzyna Dabrowska-Zielinska ◽  
Jan Musial ◽  
Alicja Malinska ◽  
Maria Budzynska ◽  
Radoslaw Gurdak ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Incidence Angle ◽  
Temporal Frequency ◽  
European Space Agency ◽  
Wetland Ecosystems ◽  
Space Agency ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference

Soil moisture (SM) plays an essential role in environmental studies related to wetlands, an ecosystem sensitive to climate change. Hence, there is the need for its constant monitoring. SAR (Synthetic Aperture Radar) satellite imagery is the only mean to fulfill this objective regardless of the weather. The objective of the study was to develop the methodology for SM retrieval under wetland vegetation using Sentinel-1 (S-1) satellite data. The study was carried out during the years 2015–2017 in the Biebrza Wetlands, situated in northeastern Poland. At the Biebrza Wetlands, two Sentinel-1 validation sites were established, covering grassland and marshland biomes, where a network of 18 stations for soil moisture measurement was deployed. The sites were funded by the European Space Agency (ESA), and the collected measurements are available through the International Soil Moisture Network (ISMN). The NDVI (Normalized Difference Vegetation Index) was derived from the optical imagery of a MODIS (Moderate Resolution Imaging Spectroradiometer) sensor onboard the Terra satellite. The SAR data of the Sentinel-1 satellite with VH (vertical transmit and horizontal receive) and VV (vertical transmit and vertical receive) polarization were applied to soil moisture retrieval for a broad range of NDVI values and soil moisture conditions. The new methodology is based on research into the effect of vegetation on backscatter () changes under different soil moisture and vegetation (NDVI) conditions. It was found that the state of the vegetation may be described by the difference between  VH and  VV, or the ratio of  VV/VH, as calculated from the Sentinel-1 images. The most significant correlation coefficient for soil moisture was found for data that was acquired from the ascending tracks of the Sentinel-1 satellite, characterized by the lowest incidence angle, and SM at a depth of 5 cm. The study demonstrated that the use of the inversion approach, which was applied to the new developed models and includes the derived indices based on S-1, allowed the estimation of SM for peatlands with reasonable accuracy (RMSE ~ 10 vol. %). Due to the temporal frequency of the two S-1 satellites’ (S-1A and S-1B) acquisitions, it is possible to monitor SM changes every six days. The conclusion drawn from the study emphasizes a demand for the derivation of specific soil moisture retrieval algorithms that are suited for wetland ecosystems, where soil moisture is several times higher than in agricultural areas.

scholarly journals Soil Moisture in the Biebrza Wetlands Retrieved from Sentinel-1 Imagery

2018 ◽  
Vol 10 (12) ◽  
pp. 1979 ◽  
Author(s):  
Katarzyna Dabrowska-Zielinska ◽  
Jan Musial ◽  
Alicja Malinska ◽  
Maria Budzynska ◽  
Radoslaw Gurdak ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cloud Model ◽  
Incidence Angle ◽  
European Space Agency ◽  
Wetland Ecosystems ◽  
Space Agency ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference

The objective of the study was to estimate soil moisture (SM) from Sentinel-1 (S-1) satellite images acquired over wetlands. The study was carried out during the years 2015–2017 in the Biebrza Wetlands, situated in north-eastern Poland. At the Biebrza Wetlands, two Sentinel-1 validation sites were established, covering grassland and marshland biomes, where a network of 18 stations for soil moisture measurement was deployed. The sites were funded by the European Space Agency (ESA), and the collected measurements are available through the International Soil Moisture Network (ISMN). The SAR data of the Sentinel-1 satellite with VH (vertical transmit and horizontal receive) and VV (vertical transmit and vertical receive) polarization were applied to SM retrieval for a broad range of vegetation and soil moisture conditions. The methodology is based on research into the effect of vegetation on backscatter (σ°) changes under different soil moisture and Normalized Difference Vegetation Index (NDVI) values. The NDVI was derived from the optical imagery of a MODIS (Moderate Resolution Imaging Spectroradiometer) sensor onboard the Terra satellite. It was found that the state of the vegetation expressed by NDVI can be described by the indices such as the difference between σ° VH and VV, or the ratio of σ° VV/VH, as calculated from the Sentinel-1 images in the logarithmic domain. The most significant correlation coefficient for soil moisture was found for data that was acquired from the ascending tracks of the Sentinel-1 satellite, characterized by the lowest incidence angle, and SM at a depth of 5 cm. The study demonstrated that the use of the inversion approach, which was applied to the newly developed models using Water Cloud Model (WCM) that includes the derived indices based on S-1, allowed the estimation of SM for wetlands with reasonable accuracy (10 vol. %). The developed soil moisture retrieval algorithms based on S-1 data are suited for wetland ecosystems, where soil moisture values are several times higher than in agricultural areas.

scholarly journals Detecting land cover change using Sentinel-2

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Koji Osumi
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Satellite Imagery ◽  
Near Infrared ◽  
European Space Agency ◽  
Open Data ◽  
Land Cover Changes ◽  
Space Agency ◽  
The Difference ◽  
Sentinel 2

<p><strong>Abstract.</strong> As many studies which detect land cover changes using satellite imagery have been conducted previously; this study uses satellite imagery from Sentinel-2, which was launched by European Space Agency (ESA) in 2015. The main characteristics of Sentinel-2 are: a 10&amp;thinsp;m spatial resolution in visible and Near-infrared (NIR) bands, a revisit frequency of 5 days based on combining Sentinel-2A and Sentinel-2B, and a free and open data policy. Using bands 4 and 8 of Sentinel-2, NDVI is calculated to assess whether the target being observed contains live green vegetation. The difference was calculated by subtracting NDVI of one day from another. Changes from vegetation to built-up areas can be detected via the changes in NDVI. However, automatically computing land cover changes generates errors under present circumstances. In order to detect land cover change accurately, human review is required. This study focuses on how NDVI can assist analysts in quantifying land cover change. As a result of the analysis, land cover changes were extracted by differencing NDVI images of 2 periods, but some errors arose in the places where land cover did not change but NDVI fluctuated owing to other reasons. I show the land cover changes which were detected, the places where it is difficult to detect the change, and methods to reduce the errors. Abstracts</p>

scholarly journals SMOS near real time soil moisture product: processor overview and first validation results

2017 ◽  
Author(s):  
Nemesio Rodríguez-Fernández ◽  
Joaquin Muñoz Sabater ◽  
Philippe Richaume ◽  
Patricia de Rosnay ◽  
Yann Kerr ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Surface Soil ◽  
Weather Prediction ◽  
European Space Agency ◽  
Retrieval Algorithm ◽  
Space Agency ◽  
Wide Range ◽  
The Difference ◽  
Level 2

Abstract. Measurements of the surface soil moisture (SM) content are important for a wide range of applications. Among them, operational hydrology and numerical weather prediction, for instance, need soil moisture information in near-real-time (NRT), typically not later than 3 hours after sensing. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite is the first mission specifically designed to measure soil moisture from space. The ESA level 2 SM retrieval algorithm is based on a detailed geophysical modelling and cannot provide SM in NRT. This paper presents the new ESA SMOS NRT SM product. It uses a neural network (NN) to provide SM in NRT. The NN inputs are SMOS brightness temperatures for horizontal and vertical polarizations and incidence angles from 30º to 45º. In addition, the NN uses surface soil temperature from the European Centre for Medium Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS). The NN was trained on SMOS Level 2 SM. The swath of the NRT SM retrieval is somewhat narrower (~ 915 km) than that of the L2 SM dataset (~ 1150 km), which implies a slightly lower revisit time. The new SMOS NRT SM product was compared to the SMOS Level 2 SM product. The NRT SM data shows a standard deviation of the difference with respect to the L2 data of

scholarly journals Evaluation of SCIAMACHY Oxygen A band cloud heights using Cloudnet measurements

2014 ◽  
Vol 7 (5) ◽  
pp. 1331-1350 ◽  
Author(s):  
P. Wang ◽  
P. Stammes
Keyword(s):  
Standard Deviation ◽  
European Space Agency ◽  
Single Layer ◽  
Middle Level ◽  
Cloud Height ◽  
Space Agency ◽  
Lidar Measurements ◽  
Retrieval Scheme ◽  
The Difference ◽  
Scanning Imaging

Abstract. Two SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) O2 A band cloud height products are evaluated using ground-based radar/lidar measurements between January 2003 and December 2011. The products are the ESA (European Space Agency) Level 2 (L2) version 5.02 cloud top height and the FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A band) version 6 cloud height. The radar/lidar profiles are obtained at the Cloudnet sites of Cabauw and Lindenberg, and are averaged for 1 h centered at the SCIAMACHY overpass time. In total we have 217 cases of single-layer clouds and 204 cases of multilayer clouds. We find that the ESA L2 cloud top height has a better agreement with the Cloudnet cloud top height than the Cloudnet cloud middle height. The ESA L2 cloud top height is on average 0.4 km higher than the Cloudnet cloud top height, with a standard deviation of 3.1 km. The FRESCO cloud height is closer to the Cloudnet cloud middle height than the Cloudnet cloud top height. The mean difference between the FRESCO cloud height and the Cloudnet cloud middle height is −0.1 km with a standard deviation of 1.9 km. The ESA L2 cloud top height is higher than the FRESCO cloud height. The differences between the SCIAMACHY cloud (top) height and the Cloudnet cloud top height are linked to cloud optical thickness. The SCIAMACHY cloud height products are further compared to the Cloudnet cloud top height and the Cloudnet cloud middle height in 1 km bins. For single-layer clouds, the difference between the ESA L2 cloud top height and the Cloudnet cloud top height is less than 1 km for each cloud bin at 3–7 km. The difference between the FRESCO cloud height and the Cloudnet cloud middle height is less than 1 km for each cloud bin at 0–6 km. The results are similar for multilayer clouds, but the percentage of cases having a bias within 1 km is smaller than for single-layer clouds. We may conclude that the FRESCO cloud height is accurate for low and middle level clouds, whereas the ESA L2 cloud top height is more accurate for middle level clouds. Both products are less accurate for high clouds.

scholarly journals Glacier Monitoring Using Frequency Domain Offset Tracking Applied to Sentinel-1 Images: A Product Performance Comparison

2019 ◽  
Vol 11 (11) ◽  
pp. 1322 ◽  
Author(s):  
Donato Amitrano ◽  
Raffaella Guida ◽  
Gerardo Di Martino ◽  
Antonio Iodice
Keyword(s):  
High Resolution ◽  
Synthetic Aperture Radar ◽  
European Space Agency ◽  
Performance Comparison ◽  
Synthetic Aperture ◽  
Space Agency ◽  
Medium Resolution ◽  
Offset Tracking ◽  
Wide Swath ◽  
Aperture Radar

The Sentinel-1 mission has now reached its maturity, and is acquiring high-quality images with a high revisit time, allowing for effective continuous monitoring of our rapidly changing planet. The purpose of this work is to assess the performance of the different synthetic aperture radar products made available by the European Space Agency through the Sentinels Data Hub against glacier displacement monitoring with offset tracking methodology. In particular, four classes of products have been tested: the medium resolution ground range detected, the high-resolution ground range detected, acquired in both interferometric wide and extra-wide swath, and the single look complex. The first are detected pre-processed images with about 40, 25, and 10-m pixel spacing, respectively. The last category, the most commonly adopted for the application at issue, represents the standard coherent synthetic aperture radar product, delivered in unprocessed focused complex format with pixel spacing ranging from 14 to 20 m in azimuth and from approximately 2 to 6 m in range, depending on the acquisition area and mode. Tests have been performed on data acquired over four glaciers, i.e., the Petermann Glacier, the Nioghalvfjerdsfjorden, the Jackobshavn Isbræ and the Thwaites Glacier. They revealed that the displacements estimated using interferometric wide swath single look complex and high-resolution ground range detected products are fully comparable, even at computational level. As a result, considering the differences in memory consumption and pre-processing requirements presented by these two kinds of product, detected formats should be preferred for facing the application.

scholarly journals Detailed Modeling of Cork-Phenolic Ablators in Preparation for the Post-flight Analysis of the QARMAN Re-entry CubeSat

2021 ◽  
Author(s):  
Claudio Miccoli ◽  
Alessandro Turchi ◽  
Pierre Schrooyen ◽  
Domenic D’Ambrosio ◽  
Thierry Magin
Keyword(s):  
Fluid Dynamics ◽  
Thermal Protection ◽  
A Priori ◽  
European Space Agency ◽  
Thermal Response ◽  
Accurate Method ◽  
Navier Stokes ◽  
Advection Equation ◽  
High Enthalpy ◽  
Space Agency

AbstractThis work deals with the analysis of the cork P50, an ablative thermal protection material (TPM) used for the heat shield of the qarman Re-entry CubeSat. Developed for the European Space Agency (ESA) at the von Karman Institute (VKI) for Fluid Dynamics, qarman is a scientific demonstrator for Aerothermodynamic Research. The ability to model and predict the atypical behavior of the new cork-based materials is considered a critical research topic. Therefore, this work is motivated by the need to develop a numerical model able to respond to this demand, in preparation to the post-flight analysis of qarman. This study is focused on the main thermal response phenomena of the cork P50: pyrolysis and swelling. Pyrolysis was analyzed by means of the multi-physics Computational Fluid Dynamics (CFD) code argo, developed at Cenaero. Based on a unified flow-material solver, the Volume Averaged Navier–Stokes (VANS) equations were numerically solved to describe the interaction between a multi-species high enthalpy flow and a reactive porous medium, by means of a high-order Discontinuous Galerkin Method (DGM). Specifically, an accurate method to compute the pyrolysis production rate was implemented. The modeling of swelling was the most ambitious task, requiring the development of a physical model accounting for this phenomenon, for the purpose of a future implementation within argo. A 1D model was proposed, mainly based on an a priori assumption on the swelling velocity and the resolution of a nonlinear advection equation, by means of a Finite Difference Method (FDM). Once developed, the model was successfully tested through a matlab code, showing that the approach is promising and thus opening the way to further developments.

scholarly journals Applicability of NGGM near-real time simulations in flood detection

2019 ◽  
Vol 9 (1) ◽  
pp. 111-126
Author(s):  
A. F. Purkhauser ◽  
J. A. Koch ◽  
R. Pail
Keyword(s):  
European Space Agency ◽  
Earth System ◽  
The Earth ◽  
Future Mission ◽  
Space Agency ◽  
Flood Detection ◽  
The One ◽  
Real Time Simulations ◽  
Grace Mission ◽  
Gravity Mission

Abstract The GRACE mission has demonstrated a tremendous potential for observing mass changes in the Earth system from space for climate research and the observation of climate change. Future mission should on the one hand extend the already existing time series and also provide higher spatial and temporal resolution that is required to fulfil all needs placed on a future mission. To analyse the applicability of such a Next Generation Gravity Mission (NGGM) concept regarding hydrological applications, two GRACE-FO-type pairs in Bender formation are analysed. The numerical closed loop simulations with a realistic noise assumption are based on the short arc approach and make use of the Wiese approach, enabling a self-de-aliasing of high-frequency atmospheric and oceanic signals, and a NRT approach for a short latency. Numerical simulations for future gravity mission concepts are based on geophysical models, representing the time-variable gravity field. First tests regarding the usability of the hydrology component contained in the Earth System Model (ESM) by the European Space Agency (ESA) for the analysis regarding a possible flood monitoring and detection showed a clear signal in a third of the analysed flood cases. Our analysis of selected cases found that detection of floods was clearly possible with the reconstructed AOHIS/HIS signal in 20% of the tested examples, while in 40% of the cases a peak was visible but not clearly recognisable.

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