Product > Satellite Imagery

High-Resolution Archive
50-80 cm, 4-band Optical Satellite Imagery

Pleiades 1A, 1B
Kompsat 2, 3, 3A
TripleSat
SkySat

High-Resolution Tasking
50-80 cm, 4-band Optical Satellite Imagery

Kompsat 3, 3A
TripleSat
SkySat

Medium Resolution Archive
1.5-5 m, 4-band Optical Satellite Imagery

PlanetScope* and Spot 6, 7

Low-Resolution Archive (Free)
10-30 m, Multispectral Optical, and SAR Imagery

Sentinel 1, 2

True Colour Composites

Regular Monitoring to Detect Changes

True-color composite images use the red, green, and blue bands gathered by satellites to mimic the range of vision for the human eye, showing us images closer to what we would expect to see in a normal photograph.

  • Monitoring the progress of a construction site over time
  • Assessing urban sprawl as a measure of economic progress
  • Estimating oil reserves based on the shape and size of cylinders (by looking at shadows)
  • Monitoring assets for compliance and ESG reporting
  • Insurance fraud detection (pool detection, solar panel detection on roof, damage assessment)
  • Track fuel composition and volumes for forest fire mitigation
  • Track third-party interference or vegetation encroachment along with linear infrastructure (pipelines, electricity line corridors, telecommunications lines)

False Colour Composites

Display Features Invisible to the Human Eye such as Minerals, Healthy Vegetation, Burned Ground, and Soil Moisture

False-color composite images substitute one or more of the RGB bands used for true-color composites for other bands such as infrared, or near-infrared to highlight specific features.

  • Monitoring the health of crops using the near-infrared bands
  • Showing vegetation regrowth overtime after a wildfire
  • Detecting pollution in the soil from a nearby power plant or mining facility
  • Estimating crop outputs for hard-to-reach regions of the world
  • Helping cattle herders better plan their migrations based on biomass and drought information

Indexes

Highlight Differences in Spectral Reflectance over Time with Mathematical Equations

Indexes are used to better discriminate between features and highlight changes in time. The most common index is the Normalized Vegetation Differential Index (NDVI). Low NDVI values (in red here) correspond to areas where vegetation is suffering. Moderate values (yellow, orange) represent moderately healthy vegetation, while very high values (green) indicate extremely healthy plants.

  • Monitoring the health of crops to optimize fertilizer and water usage
  • Identify crops that have been attacked by pests and diseases
  • Assessing the impact of a wildfire using the Normalized Burn Ratio Index
  • Quantify forest supply and leaf area index and identify tree species and density
  • Map soil-moisture variations over time to optimize planting timelines

Synthetic Aperture Radar (SAR)

Radar can Penetrate all Clouds

SAR provides low-resolution, day-and-night, and weather-independent images. Radar satellites are particularly well-suited for surveillance of vast lands with limited above-ground distinct features, such as glaciers and deserts. It is also used extensively for areas optical satellites have trouble covering, such as cloud-covered areas, or areas shrouded in darkness.

  • Monitoring floods in near-real-time in areas covered by clouds
  • Track ground deformation and map volcanic eruptions and earthquake hazards
  • Help predict landslides and avalanches
  • Detect underground features and help identify new potential dig sites for archeologists
  • Detect and map ship wakes to look at maritime travel patterns
  • Map the extent and frequency of oil spills in the ocean