Title: Classification of cloud scenes by Argus spectral data

Authors: Rehan Siddiqui; Rajinder Jagpal; Naif Al Salem; Brendan M. Quine

Addresses: Department of Physics and Astronomy, York University, 4700 Keele Street, Toronto, M3J 1P3, Canada ' Department of Physics and Astronomy, York University, 4700 Keele Street, Toronto, M3J 1P3, Canada ' Department of Physics and Astronomy, York University, 4700 Keele Street, Toronto, M3J 1P3, Canada ' Department of Physics and Astronomy, York University, 4700 Keele Street, Toronto, M3J 1P3, Canada; Department of Earth and Space Science and Engineering, York University, 4700 Keele Street, Toronto, M3J 1P3, Canada

Abstract: The mini-spectrometer Argus 1000 being in space, continuously monitors the sources and sinks of the trace gases. This paper presents a methodology of classification of cloud scene by Argus Spectral Data (CCSArSD) by applying radiance enhancement (RE) technique within 900-1700 nm of wavelength bands at infrared sounder along with GENSPECT line by line radiative transfer code for different weeks per passes. Argus was launched on aboard CanX-2 micro-satellite on 28th April 2008 as part of a technology demonstration mission. The algorithm describes a method to detect the cloudy or non-cloudy scenes. We have collected more than 300 weeks per passes with each have more than 200 spectra. The REi within the selected wavelength bands of Argus, provides a promising results to classify the cloud scene. We moreover worked on the shortwave upwelling radiative flux (W/m2) to improve the CCSArSD model, which needs further study to jump up to higher rank.

Keywords: radiance enhancement; remote sensing; radiative transfer; near infrared detectors; clouds; carbon retrieval; micro-spectrometer; cloudy scenes; Argus spectral data; trace gases.

DOI: 10.1504/IJSPACESE.2015.075911

International Journal of Space Science and Engineering, 2015 Vol.3 No.4, pp.295 - 311

Received: 06 Oct 2015
Accepted: 17 Nov 2015

Published online: 11 Apr 2016 *

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