Spectral Preprocessing

Prepare multispectral or hyperspectral imagery before spectral analysis. The feature can apply radiometric scaling, optional scene-based atmospheric correction, and band selection while preserving the geospatial raster structure.

Remote Sensing CoreEnd-User DocumentationTheory + Formula + Parameters

1. What This Feature Does

Cloud workflow: choose data → configure the scientific method → run → review the resulting layer/report. No programming is required.

2. Recommended Workflow

Choose the input raster and reflective bands. ↓ Apply radiometric calibration when the stored values require scale/offset conversion. ↓ Optionally apply atmospheric correction. ↓ Review the output as an analysis-ready spectral raster.

3. Theory, Methods & Equations

Radiometric Calibration

Converts stored digital values into a physically meaningful radiometric scale using calibration scale and offset metadata when available.

L or R = Gain × DN + OffsetThe exact physical quantity depends on the source product.

Best used when: the input contains DN or scaled integer values rather than analysis-ready reflectance.

Dark Object Subtraction (DOS)

A scene-based atmospheric correction that estimates a dark-object contribution and subtracts it from the visible/reflective signal.

R_corrected(λ) = R(λ) − R_dark(λ)Rdark is estimated from a low scene percentile.

Best used when: a simple image-based haze correction is appropriate and a full radiative-transfer solution is not required.

4. Input Data

Input	Type	Requirement	Description
Input Raster	raster	Required	Use imagery with radiometric metadata or imagery downloaded through the platform so sensor/product metadata can be detected.

5. Parameters Available in the Application

Parameter	Default	Choices / Range	How to Use It
Radiometric Calibration	On	—	Convert supported DN/scaled products to physical reflectance. For Landsat/Sentinel Level-2 this normalizes the existing Surface Reflectance scaling.
Atmospheric Correction	Off	—	Apply atmospheric correction after reflectance conversion. Already-corrected Level-2 Surface Reflectance is preserved.
Atmospheric Method	auto	auto, dos	Auto preserves Level-2 Surface Reflectance and uses scene-based Dark Object Subtraction for TOA reflectance. DOS is a practical scene correction and is not FLAASH/6S. Shown for: True
Dark Object Percentile	1.0	0.1 to 10.0	Low-reflectance percentile used by DOS. Shown for: True
Select Input Bands	—	—	Default: all supported reflective bands. Select specific bands when only part of the spectrum is required.
Output Nodata	-9999	—

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.

Important: For a product that is already Surface Reflectance, avoid applying a second unnecessary atmospheric correction. Small values below 0 or above 1 can occur in corrected products and should not automatically be interpreted as corrupt 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.

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