Information about the Earth and its environment is collected on a continuoual basis from an array of instruments either already in space or to be deployed on Earth-orbiting satellites. Similar information is also collected from air-borne platforms. Most of the instruments deployed on aircraft or on Earth-orbiting satellites measure electromagnetic radiation at a multitude of wavelengths between the ultraviolet and the microwave region of the spectrum.

In passive remote sensing the measured signal is due either to solar radiation reflected by the Earth-atmosphere system or else emitted by the Earth's surface and the atmosphere. Proper interpretation of the measured signal require knowledge of the interaction of the radiation with the atmosphere and the underlying surface. Thus, in the remote sensing community there is a need to know how the radiance at the top-of-the-atmosphere (TOA) or at aircraft altitude depends on atmospheric and surface parameters.

The most important of these parameters are the aerosol optical depth and the surface reflectance (albedo or Bidirectional Reflectance Distribution Function, BRDF). The TOA radiance is exactly what an instrument deployed on an Earth-orbiting satellite would measure. Thus, a computational tool that predicts how the TOA radiance depends on aerosol optical depth and surface reflectance is of great interest to the remote sensing community.

Design and construction of algorithms for accurate 'atmospheric correction' play a crucial role in remote sensing of surface characteristics. Such corrections are necessary to enable the user to retrieve the radiance emanating from lakes and marine bodies of water, and the radiance leaving a plant canopy on land. The radiance leaving the plant canopy or the water contains the information needed to assess biological productivity on land or in the water.

We are currently developing research tools that can be used to extract information about the environment from in situ and remote sensing data. These tools will enable the user to obtain information about the Earth-atmosphere system by properly analyzing the remotely-sensed data.