SNAP ThermalNoiseRemoval Bug

Hi there,
i am experiencing bugs when calling the thermal noise removal node with snap.
I tried to create a comprehensive markdown report below. I am happy for any help.

The report is here:

SNAP_ThermalNoiseRemoval_Bug_Report.pdf (540.2 KB)

also as pdf available (markdown rendering does not seem to be supported on this page)

# SNAP ThermalNoiseRemoval Operator Bug Report

## Summary

The SNAP `ThermalNoiseRemoval` operator produces severely corrupted output for certain Sentinel-1 GRD products acquired between late March and mid-April 2026. The `removeThermalNoise` parameter is ignored β€” setting it to `false` has no effect. Data corruption only ceases when the `ThermalNoiseRemoval` node is entirely removed from the processing graph.

## Environment

| Component | Version |

|β€”|β€”|

| SNAP Desktop / Engine | 13.0.0 |

| Java | 21.0.6 |

| ESA IPF (all affected products) | 004.03 |

## Affected Product

`S1A_IW_GRDH_1SDV_20260322T040426_20260322T040451_063735_08035B_7DD0`

- **Footprint:** `POLYGON ((32.99 46.81, 33.43 48.31, 29.97 48.71, 29.63 47.22, 32.99 46.81))` (approx. lat 46.8°–48.7Β° N, lon 29.6°–33.4Β° E)

Further images intersecting this footprint:

- At least 3 consecutive acquisition dates on orbit D138 are affected (2026-03-22, 2026-04-03, 2026-04-15). Most neighbouring dates (2026-02-02, 2026-02-14, 2026-03-10 and 2026-04-27) on the same orbit are healthy.

- 2026-02-26 is also corrupt, but with different signature (just skewed values. not further investigated here, root cause is probably the same.)

## Reproduction

**Minimum corrupt graph** (Read β†’ TNR β†’ Calibration β†’ TC β†’ dB β†’ Write):

```xml

1.0

Read${source}

ThermalNoiseRemovaltrue

Calibrationtrue

Terrain-CorrectionSigma0_VH,Sigma0_VVCopernicus 30m Global DEM10.0EPSG:32636

LinearToFromdB

Write${output}ENVI

```

**Minimum working graph** β€” remove the `ThermalNoiseRemoval` node (Read β†’ Calibration β†’ TC β†’ dB β†’ Write):

```xml

1.0

Read${source}

Calibrationtrue

Terrain-CorrectionSigma0_VH,Sigma0_VVCopernicus 30m Global DEM10.0EPSG:32636

LinearToFromdB

Write${output}ENVI

```

## Visual Comparison

**With ThermalNoiseRemoval node (corrupt):**

**Without ThermalNoiseRemoval node (healthy):**

## Additional Notes

- The `removeThermalNoise=false` parameter is ignored β€” the operator produces identical (corrupted) output regardless of this flag.

- The raw GRD measurement data (uint16 DN) is healthy and uniform across all subswaths, confirming the corruption is introduced by SNAP.

- The artifact is subswath-dependent (IW1/IW2 affected, IW3 not), suggesting the operator reads corrupted noise annotation vectors from the SAFE product.

1 Like

Any suggestions? Is this a known issue? Is there a way to flag such images?

Jira ticket SNAP-4207 created. @lveci

1 Like

This issue for this product comes from the SAR product itself with invalid annotated denoising vectors. SNAP is not the root cause of the issue.

In fact the full datatake is impacted.

This can be observed for instance on Copernicus Data Space Ecosystem browser here:

The root cause of this is a main RFI (Radio Frequency Interference) occurring at the very beginning of the datatake (close to the city of Smolensk).

The RFI is impacting directly the signal at the beginning of the datatake. The SAR Processor (IPF) contains an RFI mitigation process which was not effective here.

This RFI is as well impacting the noise measurements. The SAR Processor (IPF) is using those noise measurement along the datatake to reconstruct noise for all slices to be processed. The process includes a discarding of noise measurement contaminated by RFI. This was not effective here.

The conclusion is that the for the full datatake the denoising vectors are over estimated.

This leads to over compensation of the noise when applying the denoising.

The SAR-MPC is preparing a quality disclaimer for this.

Kind Regards

(on behalf of SAR-MPC)

2 Likes

Quality disclaimers are available here.

This issue will be tracked under QD-374 (for this specific datatake) that will be published soon.

2 Likes

Thanks a lot for the info and for pointing out the Sentinel-1 MPC | Quality Disclaimers page.

Currently I am looking for a process to exclude images with a known quality disclaimer from our pipeline. There is no api or such where the disclaimer info is provided with matching product ids? I saw them in the pdf reports, but scraping them seems a bit unnecessary.

For now there is no API to request Quality Disclaimer.
We are investigating the possibility to make one available, but we don’t have a planning for it right now.