True colour classification of natural waters with medium-spectral resolution satellites: SeaWiFS, MODIS, MERIS and OLCI - PubMed (original) (raw)

True colour classification of natural waters with medium-spectral resolution satellites: SeaWiFS, MODIS, MERIS and OLCI

Hendrik J van der Woerd et al. Sensors (Basel). 2015.

Abstract

The colours from natural waters differ markedly over the globe, depending on the water composition and illumination conditions. The space-borne "ocean colour" instruments are operational instruments designed to retrieve important water-quality indicators, based on the measurement of water leaving radiance in a limited number (5 to 10) of narrow (≈10 nm) bands. Surprisingly, the analysis of the satellite data has not yet paid attention to colour as an integral optical property that can also be retrieved from multispectral satellite data. In this paper we re-introduce colour as a valuable parameter that can be expressed mainly by the hue angle (α). Based on a set of 500 synthetic spectra covering a broad range of natural waters a simple algorithm is developed to derive the hue angle from SeaWiFS, MODIS, MERIS and OLCI data. The algorithm consists of a weighted linear sum of the remote sensing reflectance in all visual bands plus a correction term for the specific band-setting of each instrument. The algorithm is validated by a set of 603 hyperspectral measurements from inland-, coastal- and near-ocean waters. We conclude that the hue angle is a simple objective parameter of natural waters that can be retrieved uniformly for all space-borne ocean colour instruments.

Keywords: MERIS; MODIS; OLCI; SeaWiFS; citizen science; colourimetry; hue angle; ocean colour remote sensing; spectral bands; water quality.

PubMed Disclaimer

Figures

Figure 1

Figure 1

Diagram to show the contribution of a small part of the spectrum, lying between bands b1 and b2, to the tristimulus values (ΔT).

Figure 2

Figure 2

A chromaticity diagram showing the hue colour angle (α) match relative to the white point (_x_w, _y_w) of the FU scale colours. The dominant wavelength of the specific segment is indicated in nm.

Figure 3

Figure 3

Example of synthetic (full lines) and field (dashed lines) spectra with hue angles varying between 225° and 40°. Spectral satellite bands are given for OLCI, MERIS, MODIS and SeaWiFS.

Figure 4

Figure 4

The true hue angle as function of the linear hue angle derived from the MERIS band combination.

Figure 5

Figure 5

Deviation delta (°) from the hyperspectral hue angle as function of the MERIS hue angle derived from the linear satellite band combination.

Figure 6

Figure 6

Deviation delta (°) from the hyperspectral hue angle as function of OLCI, MODIS and SeaWiFS hue angles derived from linear satellite band combinations. Note the change in the vertical scale from upper to lower panel.

Figure 7

Figure 7

Example of the hue angle (“the colour”) reconstruction for MERIS. Hyperspectral hue angle (TriOS-Ramses) versus MERIS band hue angle after polynomial fit. The plot includes the linear fit line.

Figure 8

Figure 8

Inter-comparison of the hue angle (“the colour”) reconstruction of four ocean colour satellite sensors. Dotted lines give the best linear fit to the data.

Figure 9

Figure 9

Hue angle image processing of MERIS, MODISA and SeaWiFS (left to right) with the code proposed in this manuscript. Area North Sea, date 4 May 2006.

References

    1. Sathyendranath S., editor. Reports of the International Ocean Colour Coordinating Group. IOCCG; Darmouth, NS, Canada: 2000. Remote Sensing of Ocean Colour in Coastal, Other Optically-Complex Waters. No. 3.
    1. Lee Z.P., editor. Reports of the International Ocean-Colour Coordinating Group. IOCCG; Dartmouth, NS, Canada: 2006. Remote Sensing of Inherent Optical Properties: Fundamentals, Tests of Algorithms, and Applications. No. 5.
    1. Lee Z.P., Carder K., Arnone R., He M. Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments. Sensors. 2007;7:3428–3441. doi: 10.3390/s7123428. -DOI -PMC -PubMed
    1. Odermat D., Gitelson A., Brando V.E., Schaepman M. Review of constituent retrieval in optically deep and complex waters from satellite imagery. Remote Sens. Environ. 2012;118:116–126. doi: 10.1016/j.rse.2011.11.013. -DOI
    1. Van der Woerd H.J., Pasterkamp R. HYDROPT: A fast and flexible method to retrieve chlorophyll-a from multispectral satellite observations of optically complex coastal waters. Remote Sens. Environ. 2008;112:1795–1807. doi: 10.1016/j.rse.2007.09.001. -DOI

LinkOut - more resources