Workflow Narrative

Terrain-Corrected Optical Prep

Problem It Solves

Can we reduce terrain illumination bias so downstream indices and change products are defensible?

Who It Is For

Remote sensing practitioners working in high-relief terrain.

Primary User

EO analytics teams, natural resource agencies, and monitoring service providers.

What It Does

Applies terrain-aware optical correction (C-correction style) using DEM-derived geometry.
Builds cloud/shadow masks and quality confidence diagnostics alongside corrected bands.
Produces analysis-ready corrected optical outputs for downstream monitoring/classification.

How It Works

Derives slope/aspect illumination terms from the DEM and solar geometry parameters.
Applies per-band topographic normalization (C-correction style) to reduce relief-driven bias.
Generates cloud-shadow and quality layers from correction residual behavior and masking rules.
Indicative formula: L_corr ~= L_obs * (cos(theta_s) + C) / (cos(i) + C), where i is incidence angle from DEM slope/aspect.

Why It Wins

Integrates correction and QA/mask outputs in one workflow rather than forcing separate ad hoc preprocessing scripts.

Typical Buying Trigger

Teams see unstable index/change outputs across steep terrain and need a standardized correction stage.

Typical Presets

conservative: stricter correction and masking behavior.
balanced: default profile.
fast: quicker execution on large scenes.

Inputs

Parameter	Optional	Description
input_red, input_nir, input_dem	no	Core optical + terrain inputs used for topographic/reflectance normalization workflows.
optional input_green	yes	Optional green band used by workflows that include green-channel diagnostics.
solar_zenith_deg, solar_azimuth_deg	no	Solar geometry parameters used to model illumination and terrain incidence effects.
profile: conservative \| balanced \| fast	no	Processing profile controlling quality-vs-throughput behavior for correction workflow execution.

Outputs

Parameter	Type	Description
corrected optical bands	GeoTIFF	Terrain-corrected optical bands for downstream index and classification workflows.
cloud_shadow_mask	GeoTIFF	Cloud and shadow mask used to suppress unreliable optical pixels.
topographic_correction_factor	GeoTIFF	Per-pixel topographic correction factor used in radiometric normalization.
quality_confidence	GeoTIFF	Confidence surface indicating reliability of corrected optical values.
summary	JSON	Machine-readable summary report containing run metadata, QA diagnostics, and key metrics.
html_report	HTML	Human-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.terrain_corrected_optical_analytics(
    input_red="data/red.tif",
    input_nir="data/nir.tif",
    input_dem="data/dem.tif",
    solar_zenith_deg=40.0,
    solar_azimuth_deg=165.0,
    profile="balanced",
    output_prefix="output/tco",
)

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

WbW Homepage User Manual Learn More