PRO Production

Workflow-grade Pro analysis with audit-ready outputs.

workflow pro

## Workflow Narrative

In-Season Crop Stress Intervention Planning

### Problem It Solves

Where should interventions be prioritized this week to limit stress-driven yield loss?

### Who It Is For

- Agronomy advisors and farm operations teams managing in-season response.

### Primary User

Precision agronomy service providers and large production farms.

### What It Does

- Prioritizes intervention zones from in-season crop stress indicators.
- Combines vigor decline with optional thermal and moisture stress context.

### How It Works

- Uses NDVI/vigor deficit as the primary stress signal.
- Harmonizes optional canopy-temperature and soil-moisture rasters to the NDVI grid.
- Produces intervention-priority and intervention-class surfaces.
- QA acceptance guidance:
- `status=pass` indicates intervention burden is below review threshold.
- `diagnostics.acceptance_thresholds.high_priority_fraction_review` defines escalation threshold for broad intervention risk.
- High `summary.high_priority_fraction` should trigger stress-source verification before large-scale treatment rollout.
- MVP hardening assets:
- Benchmark scaffold: `tests/fixtures/precision_ag_ops_benchmark/`
- Promotion guide: `docs/internal/development/TERRAIN_PRECISION_AG_BENCHMARK_PROMOTION_GUIDE_2026_04_14.md`

## Inputs

Parameter | Optional | Description
--- | --- | ---
ndvi | no | NDVI/vigor raster normalized to [0,1].
canopy_temperature | yes | Optional thermal-stress raster normalized to [0,1].
soil_moisture | yes | Optional moisture-deficit raster normalized to [0,1].

## Outputs

Parameter | Type | Description
--- | --- | ---
intervention_priority | GeoTIFF | Continuous intervention-priority score [0,1].
intervention_class | GeoTIFF | Discrete intervention class raster (1 low to 4 urgent).
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")

    priority, classes, summary = wbe.in_season_crop_stress_intervention_planning(
        ndvi="data/ndvi_current.tif",
        canopy_temperature="data/canopy_temp_stress.tif",
        soil_moisture="data/moisture_deficit.tif",
        output_prefix="output/in_season_stress",
    )

    print(priority)
    print(classes)
    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