Global-scene Architecture for Integrated atmosphere, terrain, and cloud Analysis (GAIA™)

Physics-based synthetic scenes in the ultraviolet (UV), visible, and infrared (IR)

GAIA™ is a physics-based model for accurately and rapidly generating terrain and cloud imagery in the UV, visible and IR for any location on Earth at any time of year. The terrain radiance maps generated by GAIA™ are radiometrically correct images as viewed from the front end of a sensor. GAIA™ creates a radiance field based on user input parameters such as latitude and longitude, viewing geometries, and time of year. Using large amounts of remotely sensed data, it accounts for land topography, vegetation material optical and thermal properties, terrain self shadowing, cloud shadowing, seasonal variations, and downwelled sky radiance due to scattering and emission as well as reflected and absorbed energy. This radiance field is then propagated back through the atmosphere where it is attenuated by scattering and absorption and where path radiance due to atmospheric scattering and emission is added. The result is a synthetic sensor-viewing scene which exhibits proper phenomenology for the given user inputs. Atmospheric effects are provided by the AETHER™ radiative transfer model. GAIA™ can calculate at-aperture radiance for any reasonable sensor geometry, including space-based, airborne and ground-based systems.

gaia

GAIA™ generates images for the full electromagnetic spectrum requiring it to trace the illuminating radiation path from its source (sun/moon) to the various objects in the scene. As shown above, the radiation is scattered, absorbed, or transmitted from the scene objects. Scene objects can include sand, vegetation, water bodies, snow, ice, clouds, asphalt, rock, gravel, metal, wood, fabric, and other man-made materials.

Our ocean model, OCEANUS™, has been integrated into GAIA™ to provide enhanced ocean scene capabilities for a scene generation model that covers the earth.

 

morning

Morning

Mid-Day

afternoon

Afternoon

Series of synthetic SWIR images of North Korea, generated by GAIA™, for varying times of day.