Title of article :
Unattended processing of shipborne hyperspectral reflectance measurements
Author/Authors :
Simis، نويسنده , , Stefan G.H. and Olsson، نويسنده , , John، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Pages :
11
From page :
202
To page :
212
Abstract :
Hyperspectral remote-sensing reflectance (Rrs) from above-surface (ir)radiance measurements is derived using a new, automated method that is suitable for use on moving platforms. The sensors are mounted on a rotating platform that compensates for changing solar and ship azimuth angles, optimizing the sensor azimuth for minimal contribution of sky radiance to measured water-leaving radiance. This sea-surface reflectance (ρs) lies in the order of 2.5–8% of sky radiance, and is determined through spectral optimization, minimizing the propagation of atmospheric absorption features to Rrs. Up to 15 of these gas absorption features are frequently recognized in (ir)radiance spectra under clear and overcast skies. Rrs was satisfactorily reproduced for a wide range of simulated Case 2 waters and clear sky conditions. A set of 13,784 in situ measurements collected with optimized viewing angles on the high-absorption, low-scattering Baltic Sea was collected in April and July 2010–2011. The processing procedure yielded a 22% retrieval rate of ρs for the field data. The shape of the subsurface irradiance reflectance measurements (R(0−)) measured at anchor stations was well reproduced in above-surface Rrs in those cases where the algorithm converged on a solution for ρs, except under unstable or weak illumination conditions. Clear-sky conditions resulted in the best correspondence of Rrs and R(0−) and gave the highest (> 50%) retrieval rates of ρs. Two indices, derived from the available sensor data, are given to describe illumination conditions, and are shown to predict the ability of the algorithm to retrieve Rrs.
Keywords :
Sky Radiance , Reflectance , Hyperspectral , Case-2 water , Shipborne monitoring
Journal title :
Remote Sensing of Environment
Serial Year :
2013
Journal title :
Remote Sensing of Environment
Record number :
1633401
Link To Document :
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