A fusion algorithm that upsamples the image to the resolution of the panchromatic band.


The process fuses the higher-resolution panchromatic band with lower-resolution multispectral bands of a STAC item from an optical collection, using the Brovey method. As a result, it produces a new STAC item with an upsampled spatial resolution.

Use cases

Most often, optical collections produce the following:

  • A panchromatic band with a high spatial resolution but a low spectral resolution
  • Several multispectral bands with a low spatial resolution but a high spectral resolution

The fusion that pansharpening provides allows you to benefit from the complementary qualities of panchromatic and multispectral bands. The result is a pansharpened reflectance product.

Before pansharpening

After pansharpening

Requirements for input imagery

Checkmark inline-icon The STAC item should be CNAM-compatible. CNAM-compatible data meets both criteria:

Checkmark inline-icon The STAC item should come from an optical collection. The following categories of collections are compatible:

  • Tasking:
    • Optical satellite imagery
    • Optical aerial imagery
  • Catalog:
    • Optical satellite imagery
    • Optical aerial imagery

Checkmark inline-icon The STAC item should have panchromatic and multispectral bands. To check, whether the chosen collection provides the necessary bands, see Spectral bands.

Input parameters

Required parameters

Input imagery

You need to specify the STAC items you want to apply the process to.

Output title

You need to specify the title of the output objects. This title will be assigned to the resulting STAC item and STAC collection.

Optional parameters

Grey weights

You can specify the weights for multispectral bands or use automatically optimized weights by not defining them. Depending on the input STAC item, the algorithm either uses sensor-optimized weights or, if this data is not available, generates new optimal weights.

The weighted Brovey method, applied for this algorithm, uses the following values:

  • The pseudo panchromatic intensity. It is derived from a weighted average of the multispectral bands. Each multispectral band may contribute differently to this average, and the weights reflect their importance in approximating the panchromatic data.
  • The real panchromatic intensity. It is the actual panchromatic intensity data that serves as a reference value.

The output value of a multispectral band is computed as follows:

Band output value=Band input value×Real panchromatic intensityPseudo panchromatic intensity\text{Band output value} = \text{Band input value} \times \frac{\text{Real panchromatic intensity}}{\text{Pseudo panchromatic intensity}}

API input

A sample input payload for the process


  "inputs": {
    "title": "Pansharpened SPOT imagery over Germany",
    "item": "",
    "greyWeights": [
        "band": "blue",
        "weight": 0.2
        "band": "green",
        "weight": 0.34
        "band": "red",
        "weight": 0.23
inputs.titleobject / required
The title of the output objects: STAC item and STAC collection.
inputs.itemobject / required
The STAC item link in the following format:{collection-id}/items/{item-id}
inputs.greyWeightsarray of objects
The weight factors by which spatial details of multispectral bands are scaled.
  • If not specified, either sensor-optimized weights or optimal generated weights are used.
  • If you specify the weights yourself, you must define a minimum of 3 bands.
inputs.greyWeights.bandstring / required if
Required if greyWeights is used.

The name of the band from the STAC asset with the ["data", "multispectral"] roles.
inputs.greyWeights.weightfloat / required if
Required if greyWeights is used.

The multiplication value that lets you modulate the influence of multispectral bands on the final image.

Learn more