Super-Resolution
Proprietary super-resolution transforms lower-resolution multispectral satellite imagery into sharper, 1 metre-equivalent intelligence layers at scale.
Each XSensee workflow is built on a focused set of technologies that turn lower-cost satellite data into operational intelligence for infrastructure, agriculture and large-area monitoring.
The value comes from combining imaging, detection, spectral analytics and SAR-driven monitoring inside one delivery layer, not from isolated models.
Proprietary super-resolution transforms lower-resolution multispectral satellite imagery into sharper, 1 metre-equivalent intelligence layers at scale.
Proprietary detection models convert enhanced satellite imagery into actionable objects, geometries, counts and classifications across multiple verticals.
Spectral and temporal analytics extract crop, vegetation, soil and land-use signals that are not visible in RGB imagery alone.
Interferometric SAR measures ground deformation and structural stability over time, even in cloudy conditions and across wide territories.
Tomographic SAR resolves complex vertical structures and corridor interactions in 3D, enabling advanced monitoring of power lines and other critical assets.
XSensee links complementary sensing methods so teams can move from acquisition to insight without stitching together separate vendors or fragmented outputs.
Combine multispectral, temporal and radar signals so each workflow uses the sensing mode that best matches the terrain, asset and decision horizon.
Proprietary enhancement and recognition models are designed to recover finer structure, detect meaningful features and keep outputs consistent at area scale.
The final output is not just a model score: it can be delivered as imagery, GeoJSON layers, reports, dashboards or API-ready services for operational teams.
Tell us the territory, assets and decision problem you need to solve. We will map the right sensing and analytics workflow for your team.