Satellite Imagery Analysis Software Development

Satellite imagery analysis software reads satellite pictures and automatically classifies, detects change in, or counts objects within them, so a team does not have to scroll through thousands of images by eye.

Optical satellites like Sentinel-2 and Landsat capture visible and infrared light, but clouds block the view. SAR satellites send their own radar signal and can see through cloud cover, day or night, which makes them useful for flood mapping and all-weather monitoring.

Land cover classification models typically reach 85 to 95 percent accuracy, depending on image resolution, the number of land cover classes, and how much labeled training data is available for the specific region.

Close to it, for public satellites. Sentinel-2 revisits most locations every 5 days, so a change-detection pipeline can flag an update within days of a new image becoming available, not in true real time.

Comfygen works with Sentinel-1 and Sentinel-2, Landsat, NASA FIRMS, and commercial providers like Planet and Maxar for higher-resolution imagery.

A focused tool typically takes 12 to 20 weeks, depending on how many models it runs and how much historical imagery needs processing.

Yes. A satellite monitoring layer can check a commodity's geolocation against deforestation data and feed directly into an EUDR compliance platform.

Yes. Drone imagery fills in detail between satellite passes, and the two data sources combine well for change detection at both a wide and a close-up scale.