Temporal dynamics of sand dune bidirectional reflectance characteristics for absolute radiometric calibration of optical remote sensing data

Craig A. Coburn; Gordon S. J. Logie

doi:10.1117/1.JRS.12.012006

28 September 2017 Temporal dynamics of sand dune bidirectional reflectance characteristics for absolute radiometric calibration of optical remote sensing data

Craig A. Coburn, Gordon S. J. Logie

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 1, 012006 (September 2017). https://doi.org/10.1117/1.JRS.12.012006

Abstract

Attempts to use pseudoinvariant calibration sites (PICS) for establishing absolute radiometric calibration of Earth observation (EO) satellites requires high-quality information about the nature of the bidirectional reflectance distribution function (BRDF) of the surfaces used for these calibrations. Past studies have shown that the PICS method is useful for evaluating the trend of sensors over time or for the intercalibration of sensors. The PICS method was not considered until recently for deriving absolute radiometric calibration. This paper presents BRDF data collected by a high-performance portable goniometer system to develop a temporal BRDF model for the Algodones Dunes in California. By sampling the BRDF of the sand surface at similar solar zenith angles to those normally encountered by EO satellites, additional information on the changing nature of the surface can improve models used to provide absolute radiometric correction. The results demonstrated that the BRDF of a reasonably simple sand surface was complex with changes in anisotropy taking place in response to changing solar zenith angles. For the majority of observation and illumination angles, the spectral reflectance anisotropy observed varied between 1% and 5% in patterns that repeat around solar noon.

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Craig A. Coburn and Gordon S. J. Logie "Temporal dynamics of sand dune bidirectional reflectance characteristics for absolute radiometric calibration of optical remote sensing data," Journal of Applied Remote Sensing 12(1), 012006 (28 September 2017). https://doi.org/10.1117/1.JRS.12.012006

Received: 31 May 2017; Accepted: 13 September 2017; Published: 28 September 2017

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