PRO Production

Detect spectral change between baseline and change-date multispectral bundles with profile-based sensitivity.

workflow pro

## Workflow Narrative

Remote Sensing Change Detection

### Problem It Solves

Where is meaningful vegetation change occurring, and which detections are reliable enough for reporting?

### Who It Is For

- Environmental monitoring analysts and EO operations teams.

### Primary User

Environmental consultancies, forestry/conservation agencies, and compliance programs.

### What It Does

- Detects vegetation loss/gain between two dates using NDVI-style change logic.
- Uses bundle-native multiband inputs with explicit red/NIR band indices.
- Produces a signed change raster and a confidence raster for analyst triage.

### How It Works

- Computes NDVI-like indices per date from selected red and NIR bands.
- Calculates signed per-pixel delta between change-date and baseline NDVI-like response.
- Applies profile-dependent thresholds and local consistency checks to derive confidence.
- Indicative formula: NDVI = (NIR - Red) / (NIR + Red), then change = NDVI_change - NDVI_baseline.

### Why It Wins

- Bundle-native inputs reduce parameter mismatch errors and make cross-date processing more reproducible.

### Typical Buying Trigger

A client or regulator requires repeatable, confidence-scored vegetation change evidence for periodic reporting.

### Typical Presets

- aggressive: lower change threshold, more sensitive detection.
- balanced: default tradeoff for general monitoring.
- conservative: stricter thresholds, fewer false positives.

## Inputs

Parameter | Optional | Description
--- | --- | ---
baseline_bundle, baseline_red_band_index, baseline_nir_band_index | no | Baseline multispectral bundle and red/NIR band selectors used to compute baseline vegetation response.
change_bundle, change_red_band_index, change_nir_band_index | no | Change-date multispectral bundle and red/NIR band selectors used for signed change estimation.
optional intermediate_ndvi | yes | Intermediate-date NDVI raster used to strengthen temporal plausibility scoring.
profile: aggressive | balanced | conservative | yes | Processing profile controlling sensitivity, quality strictness, and runtime tradeoffs.
high_confidence_threshold | yes | Confidence threshold used for summary metrics (default `0.85`).

## Outputs

Parameter | Type | Description
--- | --- | ---
change_map | GeoTIFF | Primary change-intelligence raster showing direction and magnitude of detected change.
confidence | GeoTIFF | Confidence layer quantifying reliability of modeled outputs.
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")

    change_map, confidence, summary = wbe.remote_sensing_change_detection(
        baseline_bundle="data/baseline_bundle.tif",
        baseline_red_band_index=0,
        baseline_nir_band_index=1,
        change_bundle="data/change_bundle.tif",
        change_red_band_index=0,
        change_nir_band_index=1,
        profile="balanced",
        output="output/rs_change",
    )

    print(change_map)
    print(confidence)
    print(summary)

## 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 Support WbW