PROProduction

Evaluate SAR scene readiness for downstream analysis, including optional terrain and pairwise coherence-proxy checks.

workflow pro

Workflow Narrative

SAR Readiness QA

Problem It Solves

Are SAR scenes normalized enough for robust multi-scene comparison and downstream analytics?

Who It Is For

Primary User

Disaster/hazard monitoring units, remote sensing service firms, and infrastructure monitoring groups.

What It Does

How It Works

Why It Wins

Typical Buying Trigger

An organization needs dependable all-weather monitoring where optical imagery is frequently unavailable.

Typical Presets

Inputs

ParameterOptionalDescription
input_sar or input_sar_bundle, input_demnoPrimary SAR source plus terrain model used for radiometric terrain correction and readiness metrics.
input_measurement_keyyesOptional bundle measurement selector when the input SAR bundle contains multiple assets.
optional pair_sar or pair_sar_bundle and look-angle controlsyesOptional secondary SAR source and geometry controls used for pair-based coherence-proxy diagnostics.
pair_measurement_keyyesOptional bundle measurement selector when the pair SAR bundle contains multiple assets.
auto_coregister_pair, coreg_max_offset_px, coreg_decimation, coreg_min_overlap_fractionyesOptional opt-in handoff to translation-mode pair alignment before coherence-proxy estimation when CRS/grid do not already match.
speckle_window, z_factornoNoise-filter window and vertical scaling controls used in SAR preprocessing.

Outputs

ParameterTypeDescription
sar_backscatter_calibratedGeoTIFFCalibrated SAR backscatter raster suitable for quantitative comparison.
speckle_filteredGeoTIFFSpeckle-reduced SAR raster for improved interpretability and downstream analysis.
rtc_factorGeoTIFFRadiometric terrain correction factor raster used to normalize SAR signal.
coherence_proxyoptional GeoTIFFOptional pair-based amplitude-domain coherence proxy raster when a compatible SAR pair is provided.
summaryJSONMachine-readable summary report containing run metadata, QA diagnostics, and key metrics.
html_reportHTMLHuman-readable customer-facing report generated from the summary contract for stakeholder review and QA traceability.

Python Example

import whitebox_workflows as wbw

wbe = wbw.WbEnvironment(include_pro=True, tier="pro")

result = wbe.sar_analysis_readiness(
    input_sar_bundle="data/S1_reference.SAFE",
    input_measurement_key="vv",
    input_dem="data/dem.tif",
    pair_sar_bundle="data/S1_pair.SAFE",
    pair_measurement_key="vv",
    auto_coregister_pair=True,
    coreg_max_offset_px=24,
    speckle_window=5,
    output_prefix="output/sar_ready",
)

print(result)

License Notice

Use of this function requires a license for Whitebox Workflows Professional (WbW-Pro). Please visit www.whiteboxgeo.com to purchase a license.

Project Links

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