Pixel-Center Conversion
Maps row/column indices to map coordinates using the raster affine transform.
x = a(c+½)+b(r+½)+c0
y = d(c+½)+e(r+½)+f0
Best used when: each raster cell needs an explicit vector sample location.
Raster to Point
Convert raster cells into point features, normally using pixel-center coordinates and carrying the selected raster value(s) as attributes.
Shared Raster ToolsEnd-User DocumentationTheory + Formula + Parameters1. What This Feature Does
Convert raster cells into point features, normally using pixel-center coordinates and carrying the selected raster value(s) as attributes.
Cloud workflow: choose data → configure the scientific method → run → review the resulting layer/report. No programming is required.
2. Recommended Workflow
Choose the raster and band/value selection.
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Choose whether nodata cells are skipped.
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Generate points.
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Use the point layer for sampling, interpolation, statistics, or vector workflows.
3. Theory, Methods & Equations
4. Input Data
| Input | Type | Requirement | Description |
|---|---|---|---|
| Input Raster | raster | Required | Raster layer whose cells will be converted to point features. |
5. Parameters Available in the Application
| Parameter | Default | Choices / Range | How to Use It |
|---|---|---|---|
| Raster Band | — | — | Select one band from the selected raster. Available bands are loaded from the Raster Info application. |
| Pixel Step | 1 | 1 to 1000 | Sampling interval in rows and columns. 1 creates one point for every valid pixel; 2 samples every second pixel; 5 samples every fifth pixel. Increase this for large DEM rasters. |
| Exclude Nodata | On | — | Do not create points for raster nodata or masked cells. |
| Exclude Zero | Off | — | Ignore raster cells with value 0. Useful when zero represents background in a classified raster. |
| Maximum Point Features | 250000 | 1 to 1000000 | Safety limit for output size. If the selected raster would create more points than this limit, increase Pixel Step or increase the limit. |
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.