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)
See more on the marketplace.
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 STAC items must be a display data product from SPOT.
Both STAC items must be CNAM-compatible. Check that the STAC items have been added to storage in 2023 or later.
The geometries of the STAC items must overlap by at least 30%.
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 object. This title will be assigned to the resulting STAC item and STAC collection.
Use the detection-change-spot-hyperverge name ID for the processing API.
A sample input payload for the process
JSON
{
"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 objects: STAC item and STAC collection. |
inputs.items | array of strings / required The STAC item links in the following format: https://api.up42.com/v2/assets/stac/collections/{collection-id}/items/{item-id} |