Euclidean Distance Transform
For every cell, finds the nearest target cell and computes straight-line distance.
D(p)=minq∈T ||p−q||2
Best used when: distance from raster-defined targets is needed.
Raster Proximity / Distance
Calculate distance from each pixel to the nearest target pixel defined by nonzero values, a specific value, or a value range.
Raster AnalysisEnd-User DocumentationTheory + Formula + Parameters1. What This Feature Does
Calculate distance from each pixel to the nearest target pixel defined by nonzero values, a specific value, or a value range.
Cloud workflow: choose data → configure the scientific method → run → review the resulting layer/report. No programming is required.
2. Recommended Workflow
Choose source band.
↓
Define target pixels.
↓
Choose pixels or map-distance units.
↓
Run the proximity transform.
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Use the result as distance-to-feature raster.
3. Theory, Methods & Equations
4. Input Data
| Input | Type | Requirement | Description |
|---|---|---|---|
| Input Raster | raster | Required |
5. Parameters Available in the Application
| Parameter | Default | Choices / Range | How to Use It |
|---|---|---|---|
| Raster Band | — | — | |
| Target Definition | nonzero | nonzero, value, range | |
| Target Value | 1 | — | Shown for: value |
| Minimum Target Value | 1 | — | Shown for: range |
| Maximum Target Value | 1 | — | Shown for: range |
| Distance Unit | meters | meters, pixels |
6. Output & Interpretation
The result should be interpreted according to the selected method and the physical meaning of the input data. Preserve source units, coordinate reference information, NoData meaning, acquisition date, and preprocessing level when comparing results.
Scientific interpretation: an algorithm can produce a numerically valid result even when the input data are unsuitable. Always check masks, units, sensor characteristics, spatial resolution and reference data.
7. Best Practices
- Use analysis-ready inputs and remove invalid/cloud/noise artifacts that are not part of the target phenomenon.
- Choose parameters from the physical scale of the data, not only from visual appearance.
- Keep categorical and continuous rasters conceptually separate when selecting interpolation/resampling methods.
- Compare the result with the source image and independent reference information.
- Document the settings used when results will be compared across dates, sensors or study areas.