FLATSIM: The ForM@Ter LArge-Scale Multi-Temporal Sentinel-1 InterferoMetry Service
2. The NSBAS Processing Chain Used in the FLATSIM Service
2.1. Main Steps
- Import all available S-1 data with VV polarization for a given track in a given region of interest defined by its maximum and minimum latitudes (ROI);
- Import and assemble the digital elevation model (DEM) encompassing the area covered by the downloaded S-1 data. We use the DEM from the Shuttle Radar Topography Mission (SRTM) ;
- Select bursts for each subswath independently and retain only complete acquisitions within the chosen latitude range;
- Download precise orbits, compute perpendicular, and temporal baselines, and choose a single primary date common for the three subswaths;
- For each subswath, assemble bursts into Single Look Complex data (SLC), transform the DEM in the primary date radar geometry, and compute the geometrical transformations of all secondary SLCs on the geometry of the primary acquisition, combining orbit, DEM, and correlation offsets information;
- For each subswath, reassemble secondary SLCs using the position of the burst limits from the primary image and an improved deramping function, and resample secondary SLCs on the primary geometry;
- Define the interferometric network and computes differential interferograms for each subswath;
- For each subswath, evaluate spectral diversity parameters and correct interferograms;
- Merge the subswaths of all interferograms and of some auxiliary images using available metadata and inverted phase jumps in subswath overlaps;
- Correct interferograms from stratified atmospheric effects, multi-look, filter, unwrap, remove phase ramps in range and azimuth and reference;
- Discard possible low quality interferograms based on their phase variance or unwrapping fraction;
- Invert interferograms into time series and provide quality indicators;
- Prepare products in tiff or geotiff format, together with metadata, previews, and text files.
2.2. Burst Selection
2.3. Coregistration and Interferometric Network Selection
2.4. Enhanced Spectral Diversity Correction
2.5. Stratified Atmospheric Correction
2.6. Interferogram Multi-Looking, Filtering, and Unwrapping
2.7. Time Series Inversion
3. FLATSIM Architecture
3.1. Architecture of the FLATSIM Project: Distributed and Scalable by Design
3.2. Architecture of the CNES HPC Infrastructure
3.3. Architecture of the FLATSIM Production Module
- The FLATSIM application server which includes catalog and orchestrator capabilities;
- The FLATSIM unitary treatments that integrate NSBAS as a library and run as unitary jobs on nodes of the HPC center.
3.4. Architecture of the FLATSIM Delivery Module
- Downloadable products on the GPFS part of the datalake;
- Visualization data on the network attached storage (NAS) part of the datalake;
- Metadata in the PostgreSQL database.
3.5. User Access Interface
- Request A: Geonetwork’s Q Search API is used for user searches among collections. These searches can be spatial, temporal, by data center, open term, variable, or platform. The requests are xhttp requests, invisible to the user;
- Request B: The meta-catalog‘s Opensearch API allows searches among the granules of a FLATSIM collection. The requests are xhttp requests, invisible to the user;
- Requests C1 and C2 (User authentication for the metacatalog):
- C1, the user authenticates with the Keycloack SSO and is redirected with a code to the meta-catalog page;
- C2, the Vuejs meta-catalog application queries the SSO with the code to obtain an access token and user information (invisible to the user),
- Requests D1 to D4 (Authentication with FLATSIM):
- D1, the user authorizes FLATSIM to access his user data and is redirected to the meta-catalog page with a code for FLATSIM authentication;
- D2, the meta-catalog application transmits the code to the FLATSIM authentication service (invisible to the user);
- D3, FLATSIM’s authentication service queries the SSO with the code, to get user data (invisible to the user);
- D4, the authentication service transmits a FLATSIM data access token to the meta-catalog application (invisible to the user);
- Request E: The user now has a FLATSIM access token, he can query the WMS Flatsim service by transmitting the token. The service checks that the token is valid with the FLATSIM authentication service and sends the images back (invisible to the user).
- Request F: The user now can request a download by transmitting the token. The service checks that the token is valid with the FLATSIM authentication service and then returns the archive (invisible to the user).
3.6. Service Access
4. Description of Products
4.1. General Description
- points toward the file type (i.e., wrapped interferograms, coherence, etc.). See hereafter for a more detailed description.
- is set either to radar for radar geometry or geo for ground geometry.
- (DATE2, respectively). These optional fields corresponds to the date at which the first (second or last, respectively) image has been taken.
- is the number of looks used to downsample the image (note there is a factor 4 between the number of range and azimuth looks, i.e., 2 looks means 8 looks in range and 2 looks in azimuth).
- is the extension of the file that defines its type:
- contains the data;
- a preview file. It comes with a legend file, typically a colorbar with the scale information.
- a file that contains additional metadata. It contains for example information about the parameters of the processing chain, or about the product itself like its DOI, or about the satellite geometry, like the orbit direction, the relative orbit number, etc.
4.2. Packages of Interferogram Products
- Wrapped/Unwrapped InterferogramInW (InU, respectively) is the wrapped (unwrapped, respectively) merged interferogram. Wrapped interferograms in radar geometry are provided both in 2 and 8 (or 16) looks. The initial number of looks of the interferograms before they are geocoded is given in their names and metadata. The ground pixel spacing is chosen according to the initial pixel spacing in radar geometry. The InWF and InU products are spatially filtered. All interferograms have been corrected using spectral diversity and the ERA5 atmospheric model.
- Spatial coherenceCoh is the spatial coherence of the wrapped interferogram. It can thus be considered as a proxy of the quality and reliability of the signal. Typically, the spatial coherence will be very low (close to zero) at points located on water—e.g., sea, lakes, rivers, snow—and close to one at locations with stable backscattering properties where there is no vegetation—e.g., deserts, rocky mountains without snow, roads, buildings, etc.
- Atmospheric phase screen
4.3. Time-Series Package
- DTs: time-seriesThis product is a data cube that contains the cumulated total phase delay images at each acquisition with respect to the first date. In practice, the reference is set to the origin of a linear fit through the time series for each pixel. This representation avoids for the APS of the first image to appear in negative on all other dates. Note, however, that it is not ideal in case of strongly non-linear deformation. The time series may be incomplete for some pixels and for some dates, and values are then replaced by NaN. We choose to deliver the total phase delay, that includes both residual atmospheric phase screens and displacement signals, without any attempt by us to separate both contributions. This allows the user to perform its own separation, possibly guided by his knowledge of the expected deformation signal properties.The geotiff file includes as many bands as time steps. The unit is in radians along LOS, positive away from satellite. Each band is named by the acquisition date. The associated preview file displays the cumulated displacement at the last time step.
- MV-LOS: LOS velocityThe mean LOS velocity is given in a geotiff product with two bands:
- Band 1 is the mean velocity in rad/yr, positive away from satellite;
- Band 2 is a shaded view of the topography, with an illumination simulated to match the radar backscatter amplitude.
- Net: Quality assessment productThis geotiff product gives various indicators of the quality of the time series inversion, provided in radar and in ground geometry.
- Band 1: RMS misclosure of the interferogram network for each pixel, in rad;
- Band 2: Number of interferograms used in the time series inversion for each pixel;
- Band 3: Number of images used in the time series inversion for each pixel;
- Band 4: Proxy for the temporal coherence, computed as the norm of the average of all successive interferometric triplets (between 0 and 1);
- Band 5: Proxy for a possible bias in the timeseries, computed as the argument of the average of all successive interferometric triplets (in rad).
- Stk-In: interferogram list productIt gives information on the timeseries, as for example the list of dates and interferograms used as input to the time serie inversion and the reference image that was selected.
- Additional txt filesThe “RMSinterfero.txt” and “RMSdate.txt” files, together with their png previews, are very useful to check possible problems on interferograms or on acquisitions. They provide the RMS interferometric network misclosure averaged either by interferogram or by date. For example, the RMS value for some interferograms will be large in case of uncorrected unwrapping errors. Specific errors associated with one image, for example in case of snow, strong atmospheric or ionospheric perturbations, or bad azimuth frequency modulation corrections, can also be detected.
4.4. Auxiliary Data Package
- CosENU: LOS unit vectorThe three-bands geotiff product in either radar or ground geometry gives the LOS unit vector , along the satellite to ground direction, such that the LOS velocity, , can be related to the ground velocity vector, , by
- LuT: Look-up tablesThe provided LuT tables allows to project 2-looks or 8-looks products in radar geometry in ground geometry and inversely.
- TCoh: Radar backscatter propertiesThis product assembles at about 40 m × 40 m resolution backscatter properties averaged over the complete data stack. It includes (1) the averaged SLC amplitude, (2) the amplitude dispersion index (, (3) the norm of the complex average of all successive interferogram triplets, (4) the argument of the complex average of all successive interferogram triplets.
- Auxiliary text filesNumerous text files are added in the package for users wanting to verify some crucial processing steps. They include perpendicular baseline information, parameters for enhanced spectral diversity corrections for each sub-swath, interferogram unwrapping fractions, and interferogram phase standard deviations.
5. Results and Products Qualification
5.1. First Processed Areas
- The Ozark aquifer project covers a region located in North America. It focuses on the study of the deformations associated with the Ozark aquifer (south of the Mississippi basin), subject to strong variations in groundwater level, and in neighboring regions where significant seismicity is observed, with a strong seasonal component (New Madrid), or related to wastewater injections (Oklahoma). The objective is to better understand the geodetic signature of the hydrological cycle;
- The Central Andes, Peru–Chile project aims at (1) better understanding the seismic cycle of the Andean subduction zone in Peru and Chile and of the crustal faults in the Andes, (2) monitoring the dynamics of the large active volcanoes in the region (and to detect possible precursors to eruptions), and (3) at studying the seismic, climatic, and anthropogenic forcing on the dynamics of landslides in the Andes;
- The Balkan region is one of the most seismically active zones in Europe, with intense industrial and demographic development. The purpose of the project is to better quantify the deformations of tectonic origin in this region (kinematics and localization of active faults, study of earthquakes). It also aims at quantifying the deformations of anthropogenic or climatic origin (linked to the exploitation of natural ressources or to variations in sea level);
- Turkey: The objective of this project is to characterize the seismic and aseismic behavior of the North Anatolian and East Anatolian faults, in order to better assess their seismic hazard and understand the physical processes governing the dynamics of a fault. It also includes the monitoring of deformations in the grabens of western Turkey, which are major geological structures with high seismic potential;
- The Afar project aims at characterizing the spatial and temporal distribution of the deformation in the region of the Afar depression. The purpose is to better understand the large-scale tectonics (localization of divergent borders, kinematics of the triple point), but also the dynamics of volcanic, seismic, and aseismic events, and the mechanics of active faults. The issue of landslides hazard will also be addressed;
- Okavango delta: This project aims at better understanding the deformations of tectonic origin in the area of the Okavango Delta (associated with the functioning of the Okavango rift and the East African rift), or of hydrological origin (linked in particular to the flood cycle), and the possible interactions between tectonics and hydrology in this region;
- The Tarim project focuses on the analysis of tectonic deformations along the Western Kunlun Range, on the northwestern edge of the Tibetan Plateau. This region is marked by the interaction between large strike-slip and thrust faults, with in particular the existence of one of the largest thrust sheet in the world, whose interseismic loading and capability to produce “mega-earthquakes” will be investigated;
- Eastern border of the Tibetan plateau: The objective of the project is to quantify and model the current deformations on the eastern edge of the Tibetan plateau. It focuses on deformations of tectonic origin, at the scale of active faults, as well as at the continental scale, to address issues of the seismic cycle and uplift mechanisms of the Tibetan plateau. This project is also interested in monitoring non-tectonic signals present in the time series (hydrological overloads in particular).
5.2. Result Discussion in Tibet Area
5.3. Discussion of Results in the Afar Area
- Following a major rifting episode that took place between 2005 and 2011 , the Dabbahu volcano (located North West of Manda Hararo in Figure 18) has experienced a steady re-inflation, inducing uplift at a rate of ≈3.5 cm/yr. The inflation is remarkably constant between 2014 and 2021, confirming the findings of ;
- In contrast, the volcano Erta ’Ale has shown a transient deflation that started in January 2017 following a lava lake overflow event, that produced long-lived lava flows ;
- Finally, a very small signal is detected in the Dergaha graben, coinciding with a cluster of seismicity detected in 2008 . The time-series shows a clear step around March 2018, which corresponds well with the time of occurrence of the largest event of the seismic sequence.
6. Conclusions and Future Work
Conflicts of Interest
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|APS||Interferogram Atmospheric Phase Screen from Global Atmospheric Model|
|InW/InU||Wrapped/Unwrapped Differential Interferograms|
|InWF||Wrapped Differential Filtered Interferograms|
|DTs||Time series of total LOS phase delay (data cube)|
|MV-LOS||Mean LOS Velocity|
|Net||Auxiliary maps for the assessment of the time series quality|
|Stk-In||List of the interferograms file names|
|CosENU||LOS unit vector expressed in local reference frame|
|(East, North, Up components).|
|DEM||Elevation in meter in radar geometry. Comes in two resolutions.|
|LuT||Lookup Tables used to do the mapping between radar and ground geometry.|
|TCoh||Backscatter properties in 2 looks.|
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Thollard, F.; Clesse, D.; Doin, M.-P.; Donadieu, J.; Durand, P.; Grandin, R.; Lasserre, C.; Laurent, C.; Deschamps-Ostanciaux, E.; Pathier, E.; et al. FLATSIM: The ForM@Ter LArge-Scale Multi-Temporal Sentinel-1 InterferoMetry Service. Remote Sens. 2021, 13, 3734. https://doi.org/10.3390/rs13183734
Thollard F, Clesse D, Doin M-P, Donadieu J, Durand P, Grandin R, Lasserre C, Laurent C, Deschamps-Ostanciaux E, Pathier E, et al. FLATSIM: The ForM@Ter LArge-Scale Multi-Temporal Sentinel-1 InterferoMetry Service. Remote Sensing. 2021; 13(18):3734. https://doi.org/10.3390/rs13183734Chicago/Turabian Style
Thollard, Franck, Dominique Clesse, Marie-Pierre Doin, Joëlle Donadieu, Philippe Durand, Raphaël Grandin, Cécile Lasserre, Christophe Laurent, Emilie Deschamps-Ostanciaux, Erwan Pathier, and et al. 2021. "FLATSIM: The ForM@Ter LArge-Scale Multi-Temporal Sentinel-1 InterferoMetry Service" Remote Sensing 13, no. 18: 3734. https://doi.org/10.3390/rs13183734