A Spectro-radiometric Analysis of Ocean Colour Sensors and Proposal for a Miniature Hyper Spectral Imager for Future
- 57 Downloads
Ocean colour sensors traditionally are of fixed spectral channel systems with specified bandwidth of about 20 nm in the visible region and about 40 nm in Near Infrared region. In these systems, it is known that a radiometric error of 1% in the measurement of top of the atmosphere signal may lead to an error of 10% in the retrieved ocean upwelling radiance. In this paper we investigated the range of wavelengths participating in signal collection (effective spectral pass band, ESPB) using relative spectral response data of various sensors flown earlier. ESPB values were computed for each spectral channel for various percentages of signal and the results showed that they are quite high compared to bandwidths specified. These values were found to vary with sensor and channel. ESPB shall be small for accurate computation of spectral radiance. As the knowledge of spectral profile of the signal in the range of ESPB helps in better estimation of spectral radiance at the intended wavelengths, a miniature high performance linear variable filter based hyperspectral sensor is proposed as an alternative. We present here the design concept and report the estimated performance of such sensor that can be realized even with commercial off the shelf components for operational implementation.
KeywordsOcean colour sensor Bandwidth Effective spectral pass band B-spline Error range Hyper spectral imager Linear variable filter SNR Spectral binning
We are grateful to Indian Institute of Remote sensing (IIRS), Space Applications Centre (SAC) and National Remote Sensing Centre (NRSC) of ISRO and Doon University (DU) for supporting this research work. Our sincere thanks to Ocean Biology Processing Group of NASA’s Goddard Space Flight Centre (GSFC) for the RSR data of various sensors. We gratefully acknowledge the useful discussions we had with Dr Prakash Chauhan, Mr Nitesh Thapa, SAC, Dr Sameer Saran, IIRS, Dr Sarnam Sigh, IIRS and Dr Vijay Sridhar, DU.
- Committee on Assessing Requirements for Sustained Ocean Color Research and Operations. (2011). Assessing requirements of sustained ocean colour research and operations. Washington: National Research Council. ISBN 978-0-309-21044-7.Google Scholar
- Daniel, R. K., Robert, L. L., Michael, R. C., & Rong-Rong, L. (2011). Hyperspectral imager for the coastal ocean (HICO) performance testing and calibration. In Presentation to HICO user group (HUG). Google Scholar
- IOCCG. (2015). Historical ocean colour sensors. http://www.ioccg.org/sensors/historical.html. Accessed 5 Aug 2015
- IOCCG. (2016a). Current ocean colour sensors. http://www.ioccg.org/sensors/current.html. Accessed 5 Aug 2015
- IOCCG. (2016b). Scheduled ocean colour sensors. http://ioccg.org/resources/missions-instruments/scheduled-ocean-colour-sensors/. Accessed 5 Aug 2015
- Joseph, G. (2005). Fundamentals of remote sensing (2nd ed.). Hyderabad: Universities Press.Google Scholar
- Kumar, A. S. K., & Samudraiah, D. R. M. (2015). Hyperspectral imager onboard Indian mini satellite-1. In S.-E. Qian (Ed.), Optical payloads for space missions. New York: Wiley.Google Scholar
- Kwaitkowska, E. J. (2006). Ocean colour data processing. In Presentation at INPE, Brazil.Google Scholar
- Mobley, C. (2011). Remote sensing chapter—Ocean optics. Web book. www.Oceanopticsbook.info. Accessed 29 Sep 2015
- Samir, P. (2013). Ocean colour monitor-2 pre launch calibration and post launch performance. In Presentation at IOCCG meet. Google Scholar