Calibration of satellite data in reflectance using the 5S algorithm

Johan Lavreau

doi:10.1117/12.197238

21 December 1994 Calibration of satellite data in reflectance using the 5S algorithm

Johan Lavreau

Proceedings Volume 2318, Recent Advances in Remote Sensing and Hyperspectral Remote Sensing; (1994) https://doi.org/10.1117/12.197238
Event: Satellite Remote Sensing, 1994, Rome, Italy

Abstract

Most applications of spectral geology require image data to be expressed in the form of reflectance values in order to allow comparisons with field or laboratory measurements. Two problems must be solved in order to pass from the digital number (DN) provided by the satellite operator to a reflectance value: (1) the calibration factors of the DN into a physical value as luminance/radiance at satellite level (Ls), and (2) the computation of a reflectance at ground level (R_g) from this Ls. The calibration in luminance is straightforward as a gain and, sometimes, an offset factor is provided by the operator. The computation of the R_g of a target can be performed if the conditions of illumination and travel of the radiation through the atmosphere are known as well as the nature of the target and its environment. The 5S algorithm of simulation of the solar illumination calculates the radiation at the ground and at satellite level for a given target and environment, through an atmospheric model adapted to the circumstances of image acquisition. Given an environment identical or different from the target, the input variables of the algorithm (nature of the sensor, illumination conditions, type of atmosphere, type and thickness of aerosols) can be adapted for scaling Ls according to parametric R_g values. This relation is approximately linear. A scale of R_g values can thus be matched with a scale of R_s values, which can in turn be converted to DN values, or inversely.

Citation Download Citation

Johan Lavreau "Calibration of satellite data in reflectance using the 5S algorithm", Proc. SPIE 2318, Recent Advances in Remote Sensing and Hyperspectral Remote Sensing, (21 December 1994); https://doi.org/10.1117/12.197238

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KEYWORDS

Satellites

Calibration

Reflectivity

Atmospheric modeling

Environmental sensing

Sensors

Earth observing sensors

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