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Atmospheric Correction of Moderate- and High-Resolution Satellite Imagery
Abstract
The exploitation of satellite imagery for Earth remote sensing has steadily increased in sophistication since the first Earth-observing satellite was launched in 1960. The technological advances in sensors, telecommunications, and ground processing systems resulted in a large increase of satellite data collection due to finer spatial resolution, greater spectral sampling, and the number of Earth-observing missions. With increasing volumes of satellite observations came increasingly sophisticated algorithms to determine the properties of the atmosphere and underlying surfaces. The exploitation (or processing) of satellite data can then be viewed as implementing the inverse problem of inferring atmospheric and surface characteristics from the satellite measurements of outgoing electromagnetic radiation. The challenges in solving inverse problems of this kind, even in an approximate sense, are largely governed by the type of data collected. The collection of top of the atmosphere (TOA) data depends on the satellite orbit, e.g., low Earth orbit (LEO), versus geostationary orbit. It also depends on whether the instruments collect polarized or unpolarized electromagnetic radiation and whether single or multiple lines of sight are collected concurrently.
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