The algorithm detects changes in infrastructure across two SPOT images. The result is a GeoJSON file with polygons drawn around the detected changes.
Infrastructure change detection can be used for urban planning, construction, fire risk estimation, land use management, and infrastructure monitoring.
Detected change polygons drawn on input SPOT images of JFK Airport (USA)
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The algorithm has been developed using SPOT and Pléiades imagery.
For optimal results, the algorithm must be applied to imagery over urban areas with man-made infrastructure.
Both data items must be the same supported data product:
- SPOT catalog: Display
Both data items must be CNAM-compatible. Check that the data items have been added to storage in 2023 or later.
The geometries of the data items must overlap by at least 30%.
You must specify the data items you want to apply the process to.
You must specify the title of the output data item.
Use the detection-change-spot-hyperverge name ID for the processing API.
{ "inputs": { "title": "Processing imagery over Berlin", "items": [ "https://api.up42.com/v2/assets/stac/collections/68567134-27ad-7bd7-4b65-d61adb11fc78/items/23e4567-e89b-12d3-a456-426614174000", "https://api.up42.com/v2/assets/stac/collections/21c0b14e-3434-4675-98d1-f225507ded99/items/edeb6310-ea9a-4d8e-943d-11a5f3757824" ] }}| Parameter | Overview |
|---|---|
inputs.title | object | required The title of the output data item. |
inputs.items | array of strings | required Links to the data items in the following format: |