SAR-COIN service specifications
This service takes as input a pair of Sentinel-1 SLC datasets, it computes the coherence and backscatter from the interferometric pair and produces a band composite of coherence and backscatter average. It also generates a red-cyan composite of backscatter from reference and secondary.
The tutorial of the SAR-COIN service is available in this section.
Service Description
The Coherence and Intensity Composite (SAR-COIN) processing service provides geocoded composites of coherence and intensity images from a pair of radar Single Look Complex (SLC) EO data.
In terms of single-band geophysical products, the SAR-COIN service generates from the input SLC datasets:
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the coherence asset
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and a pair of co-pol Sigma Nought assets in dB.
The coherence between the reference and the secondary indicates the quality of the interferometric phase. High coherence values highlight a strong similarity in the interferometric pair and create the better condition for processing (e.g. Displacement mapping in LOS). Instead, low coherence values result in poor interferometric results (e.g. over vegetation in C-band due to volumetric scattering).
This processor also provides a couple of multi-band visual assets:
- An RGB composite with Coherence and Backscatter average between reference and secondary SLC datasets. This visual product is showing urban areas in yellow, which have high coherence and intensity. Green can represent vegetated fields and forests. The reds and oranges represent unchanged features such as bare soil or rocks.
Figure 1 - Red-Green band composite using coherence and average sigma nought derived from Copernicus Sentinel-1 SLC data acquired over Iraq.
- A Red-Cyan band composite with post- and pre-event backscatter showing areas where the backscattering is decreasing in cyan, e.g. flooded bare soils, damaged buildings, while areas showing an increase of backscattering appear in red.
The COIN service relies on the ESA SNAP1,2 software which is a common architecture for all Sentinel Toolboxes and is ideal for Earth Observation processing and analysis. The flowchart in the next section describes the entire COIN workflow. In the Geocoding and Back Geocoding steps COIN uses the Copernicus DEM, COP-DEM3, at 30m resolution as Digital Elevation Model. After the radiometric calibration the Sigma Nought is speckle filtered using the Lee Sigma filter. In the geocoding of both coherence and backscatter single-band assets COIN employs an automatic UTM zone reprojection of results.
The Coherence and Intensity Composite service inherits the general workflow from the “COIN” service4 available in the GEP.
Workflow
The COIN service implements the workflow depicted below.
Input
Coherence Intensity Composite service requires as input a pair of SLC Datasets. Input SAR complex imagery must be a pair from the same mission, track, and polarization.
Note
This service supports only SAR complex imagery (Datasets from source SLC/L1A products).
Note
The service employs only co-pol assets from the given input SLC datasets (e.g. with dual-pol VV/VH SAR data only amplitude and phase in VV polarization are used).
Warning
SAR-COIN currently supports only SLC Datasets from the Sentinel-1 EO mission.
Service input parameters are listed and described below.
Parameters
The SAR-COIN service requires a specified number of mandatory and optional parameters. Table 1 describes the service parameters.
Parameter | Description | Required | Default value |
---|---|---|---|
Reference SLC dataset | Input reference SLC Dataset with intensity and phase recorded as complex numbers | YES | |
Secondary SLC dataset | Input secondary SLC Dataset with intensity and phase recorded as complex numbers | YES | |
Coherence Azimuth Window Size | Azimuth Window Size used for the coherence estimation | YES | 10 |
Coherence Range Window Size | Range Window Size used for the coherence estimation | YES | 40 |
Area of Interest | Area of interest expressed in WKT | NO |
Table 1 - Service parameters for the SAR-COIN processor.
Reference and secondary SAR SLC datasets
The reference
and secondary
SAR SLC datasets must come from the same sensor and shall have the same radar geometry (incident angle, orbit path).
Azimuth and range window size for coherence estimation
In the third and fourth parameters the user shall specify the size of the shifting window for the coherence estimation. The window size is defined, in both azimuth and range directions.
Being SAR-COIN designed for Sentinel-1, default values for Coherence Azimuth Window Size
and Coherence Range Window Size
are respectively 10 and 40.
Note
Coherence Azimuth Window Size shall be a positive integer contained within the (1, 90] range. Same applies for the Azimuth one.
Tip
For Sentinel-1 the Range coherence window size shall be 4 times the Azimuth one.
AOI (optional)
This last parameter (optional) may define the area of interest expressed as a Well-Known Text value.
Tip
In the definition of “Area of interest as Well Known Text” it is possible to apply as AOI the drawn polygon defined with the area filter. To do so, click on the button in the left side of the "Area of interest expressed as Well-known text" box and select the option AOI from the list. The platform will automatically fill the parameter value with the rectangular bounding box taken from the current search area in WKT format.
Output
The SAR-COIN service provides the following products:
- Product A: Coherence and Intensity Composite
- Product B: Red-Cyan composite from Sigma Nought Secondary and Reference
- Product C: Coherence
- Product D: Sigma Nought Reference
- Product E: Sigma Nought Secondary
The below tables provide Product Specifications for the SAR-COIN service.
Attribute | Value / description |
---|---|
Long Name | Coherence and Intensity Composite |
Short Name | overview-coin |
Description | RGBA Composite using Coherence and Sigma0 Average (R=Coherence, G=Sigma0 Average from Reference and Secondary, B=null) including alpha band (Multi-band Visual Asset) |
Data Type | Unsigned 8-bit Integer |
Band | 4 |
Format | COG |
Projection | UTM / WGS84 |
Valid Range | [1 - 255] |
Fill Value | 0 |
Attribute | Value / description |
---|---|
Long Name | Red-cyan composite for backscatter change from Reference and Secondary Sigma Nought |
Short Name | overview-sar-change |
Description | RGBA Composite using Sigma Nought from the pair (R=Sigma0 from Secondary, G=B=Sigma0 from Reference) including alpha band (Multi-band Visual Asset) |
Data Type | Unsigned 8-bit Integer |
Band | 4 |
Format | COG |
Projection | UTM / WGS84 |
Valid Range | [1 - 255] |
Fill Value | 0 |
Attribute | Value / description |
---|---|
Long Name | Coherence product |
Short Name | coh_b_pp_YYYYMMDD_YYYYMMDD (where b the SAR-band [x,c,l], pp is the polarization [hh, hv, vh, vv], YYYYMMDD is the date of Reference and Secondary Dataset) |
Description | Interferometric coherence computed on input SLC couple, it indicates where the phase information is coherent (Single-band Geophysical Asset) |
Data Type | Float 32 bit |
Band | 1 |
Format | COG |
Projection | UTM / WGS84 |
Valid Range | [0 - 1] |
Attribute | Value / description |
---|---|
Long Name | Sigma nought product from Reference SLC Dataset |
Short Name | s0_db_b_pp_ref (where b the SAR-band [x,c,l], and pp is the polarization [hh, hv, vh, vv]) |
Description | Single-band geophysical asset representing Sigma Nought in dB from calibrated and terrain corrected reference SLC dataset. |
Data Type | Float 32 bit |
Band | 1 |
Format | COG |
Projection | UTM / WGS84 |
Units | dB |
Attribute | Value / description |
---|---|
Long Name | Sigma nought product from Secondary SLC Dataset |
Short Name | s0_db_b_pp_sec (where b the SAR-band [x,c,l], and pp is the polarization [hh, hv, vh, vv]) |
Description | Single-band geophysical asset representing Sigma Nought in dB from calibrated and terrain corrected secondary SLC dataset. |
Data Type | Float 32 bit |
Band | 1 |
Format | COG |
Projection | UTM / WGS84 |
Units | dB |
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ESA Science Toolbox Exploitation Platform, SNAP Toolbox available at https://step.esa.int. ↩
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SNAPISTA, SNAP GPT Python wrapper documentation available at https://snap-contrib.github.io/snapista/. ↩
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Copernicus, "Copernicus DEM - Global and European Digital Elevation Model (COP-DEM)", available at: https://spacedata.copernicus.eu. ↩
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GEP, COIN Tutorial, available at https://terradue.github.io. ↩