GAIA™
The Global scene Architecture for Integrated atmosphere, terrain, and cloud Analysis (GAIA™) is a robust, state-of-the-science
code for generating terrain and cloud scenes in the ultraviolet (UV), visible (VIS), and infrared (IR) portions of the spectrum. It is
database driven, using available databases to define the terrain and clouds, and then using state-of-the-science observables algorithms
to predict the scene in the desired spectral band.
Currently, GAIA™ accesses the following databases:
Puget Sound in Washington State:
i.
ii.
Terrain Altitude
a. ETOPO10 (10 arc-min)
b. ETOPO1 (1 arc-min)
c. Shuttle Radar Topography Mission (SRTM)
(90 m worldwide)
d. SRTM (30 m United States and possessions)
e. ASTER Global Digital Elevation Map (30 m
worldwide)
Land Cover
a. Ecosystem (Owen 10 arc-min)
b. Primary (MODIS 500 m)
c. Secondary (MODIS 500 m)
d. Dynamics (MODIS 500 m)
iii. Clouds
a. Low and Mid Etage Clouds
i. Cloud Top Altitude (MODIS 5 km)
ii. Cloud Base Altitude (MODIS 5 km)
iii. Fraction Cloud Cover (MODIS 5 km)
b. High Etage Clouds
i. Cirrus Top Altitude (MODIS 5 km)
ii. Cirrus Base Altitude (MODIS 5 km)
iii. Cirrus Mask (MODIS 1 km)
iv. Contrails (MODIS 1 km)
30 m Altitude and Primary Land Cover
Puget Sound in Washington State:
30 m Altitude and Secondary Land Cover
Using this set of databases (or any other similar database), GAIA™
fills in missing “holes” in the data (e.g., missing altitude data from SRTM
due to terrain blockage) and fractally interpolates the measured data to
provide a scene grid. For example, the above figures show a threedimensional image of the Puget Sound area in Washington state terrain altitude based on 30-m SRTM data, overlaid by the Primary
and Secondary Land Covers, respectively. The scenes are approximately 123 km square. The color scene for the primary land cover
is water (blue), vegetation (different shades of green), and urban areas (e.g., Seattle, Tacoma) (grey). GAIA™ will translate the
MODIS land cover classes (i.e., water, evergreen needle-leaf forest, evergreen broadleaf forest, deciduous needle-leaf forest,
deciduous broadleaf forest, mixed forest, closed shrub lands, open shrub lands, woody savannas, savannas, grasslands, permanent
wetlands, croplands, urban and built-up, cropland/natural vegetation mosaic, snow and ice, and barren or sparsely vegetated) into
scene types, each of which consists of a combination of terrain materials (e.g., pine trees, broadleaf trees, shrubs, grass, different types
of soils and rocks, asphalt, concrete). Other databases provide additional information in the amount of ground water (e.g., streams,
lakes) and soil moisture, the type of soils (i.e., fractions of clay, sand, silt, organic matter, and coarse fragments), and seasonal
variations in snow cover.
Computational Physics, Inc., 8001 Braddock Rd, Ste 210, Springfield, VA 22151
Phone: 703.764.7501 FAX: 703.764.7500
Contact: Dr. William M. Cornette [email protected]
GAIA™
Once the composition of each pixel is known, the primary and secondary land covers are mixed together using a fractal algorithm and
the ground water and snow are added. The temperatures of each material in the pixel and the radiative environment are determined by
the Moderate Spectral Atmospheric Radiance and Transmittance (MOSART) code. From this information, GAIA™ calculates the ataperture radiance for a sensor viewing the scene, either from space, from an airborne platform, or from a ground-based system.
The clouds are generated using MODIS Cloud Cover data sets that contain essentially global data for a 24-hour period at 5 km
spatial resolution (i.e., Latitude, Longitude, Surface Temperature, Surface Pressure, Cloud Top Pressure, Cloud Top Temperature,
Tropopause Height, Cloud Fraction, Cloud Effective Emissivity, Cloud Phase Infrared, Cloud Mask, Quality Assurance) and at 1 km
spatial resolution (i.e., Latitude, Longitude, Effective Particle Radius, Cloud Optical Thickness, Cirrus Reflectance, Cirrus Reflectance
Flag, Cloud Mask, Quality Assurance).
From this data and fractal
interpolation, GAIA™ creates grids of cloud top altitude and cloud base
altitude that are fully consistent with the underlying terrain, the time of year,
and the remotely sensed data. A multiple scattering radiative transfer
algorithm determines the cloud top and cloud bottom radiances.
This cloud grid can be integrated into the terrain grid to include cloud
shadows on the terrain, cloud cooling of terrain temperatures, and, of course,
clouds in the scene. For example, a terrain scene radiance map without clouds
but with cloud shadows (dark areas) on the terrain is shown in the figure
below.
A sample radiance scene is shown below for the long-wave infrared
(LWIR) of the Puget Sound area of Washington State for an airborne sensor at
20 km altitude located approximately 3 km southwest of the lower left-hand
corner. Variations in scene brightness can be seen as a function of terrain
altitude (e.g., the foothills of the Olympic Mountains in the upper left corner),
distance from the sensor (e.g., the scene in the lower left corner and closest to
the sensor is brightest), and location (e.g., the water temperature varies
throughout Puget Sound).
MODIS Cloud Height
(5 km resolution)
Sample
Cloud Scene
The atmospheric conditions for the scene generation, including transmission, path radiance, incident direct diffuse solar
irradiance, incident direct and diffuse lunar irradiance, and incident diffuse thermal irradiance are provided for a three-dimensional
grid (i.e., latitude, longitude, and altitude), as well as the terrain material and cloud temperatures, are provided by the MOSART v3.0
code. The Ocean Universal Scene (OCEANUS™) model has also been integrated into GAIA™ to generate scenes anywhere on the
surface of the Earth.
Sample Terrain Scene with
Cloud Shadows (Dark Areas)
Sample LWIR Puget Sound Scene
More Information: www.cpi.com/projects/gaia.html