Technical Note

Mapping coloured dissolved organic matter concentrationin coastal waters

T. KUTSER*, B. PAAVEL, L. METSAMAA and E. VAHTMAE

Estonian Marine Institute, University of Tartu, Maealuse 10a, Tallinn 12618, Estonia

(Received 23 June 2007; in final form 7 March 2008)

Optical properties of the Baltic Sea are dominated by coloured dissolved organic

matter (CDOM). High concentration of CDOM is probably one of the reasons

why standard chlorophyll-retrieval algorithms fail badly in the Baltic Sea. Our aim

was to test can CDOM be mapped by remote sensing instruments in coastal waters

of relatively CDOM-rich environments like the Baltic Sea. The results show that

sensors with high radiometric resolution, such as Advanced Land Imager (ALI),

can be used for mapping CDOM in a wide concentration range. The ALI image

also showed that optical properties of coastal waters are extremely variable.

CDOM concentration may vary 4–5-fold in two adjacent 30 m pixels. This indi-

cates a need for relatively high spatial resolution (30 m or less) remote sensing data

in monitoring coastal environments.

1. Introduction

Coloured dissolved organic matter (CDOM) is an important component in many

aquatic ecosystems. It is a carbon source for bacteria and it protects biota from UV-B

damage. CDOM is also the dominating optically active substance in many water

bodies, determining formation of underwater light field and water-leaving radiance

measurable by remote sensors. One such water body is the Baltic Sea. Strong absorp-

tion of light by CDOM at shorter wavelengths is probably the main reason whystandard chlorophyll-a retrieval algorithms fail in the Baltic Sea (Darecki and

Stramski 2004, Kutser 2004, Reinart and Kutser 2006).

CDOM retrieval algorithms have been developed for lakes (Kutser et al. 1998,

2005a, 2005b, Kallio et al. 2001) and marine waters (Chen et al. 2003, Kowalczuk

et al. 2005, Doxaran et al. 2005, Schwarz 2005). Different approaches have been used

in estimation of CDOM concentration in water. Band-ratio type algorithms that have

been developed for marine waters mainly utilize SeaWiFS band configuration.

However, spatial resolution of SeaWiFS is not sufficient in many coastal waters.Kutser et al. (2001) and Kutser (2004) have proposed two slightly different

approaches where modelled reflectance spectra are used to retrieve CDOM, chlor-

ophyll and suspended matter concentrations simultaneously from remote sensing

data. These approaches, however, require availability of hyperspectral data or at

least it is preferable to have hyperspectral data. Landsat series satellites have spatial

resolution that is adequate in coastal waters with sophisticated shoreline. However,

radiometric sensitivity of Landsat is insufficient in very CDOM-rich waters, as has

*Corresponding author. Email: Tiit.Kutser@sea.ee

International Journal of Remote SensingISSN 0143-1161 print/ISSN 1366-5901 online # 2009 Taylor & Francis

http://www.tandf.co.uk/journalsDOI: 10.1080/01431160902744837

International Journal of Remote Sensing

Vol. 30, No. 22, 20 November 2009, 5843–5849

been shown by Kutser et al. (2005a). Advanced Land Imager (ALI), a prototype of

next generation Landsat sensors, is suitable for mapping CDOM also in very brown

waters (Kutser et al. 2005a, 2005b). Therefore, we decided to use this instrument for

mapping CDOM in coastal waters where the concentration of CDOM may vary

significantly.

2. Methods

The study site is located in Muhu Strait, located between two large islands, Saaremaa

and Hiiumaa, and the Estonian west coast, in the eastern part of the Baltic Sea (see

figure 1). The area is relatively shallow, generally less than 10 m deep. The shoreline is

sophisticated and there are lots of small islets scattered over the Strait. There are two

major river inflows in the area. Both rivers bring CDOM-rich water into the Strait.An image of Advanced Land Imager acquired in 1 September 2005 (figure 2) was

used in estimating CDOM concentration in the Muhu Strait area. ALI on EO-1 is a

prototype of next generation Landsat series satellites with improved spectral and

radiometric resolution and substantial mass, volume and cost savings. It has 10 bands:

a panchromatic band with 10 m spatial resolution and nine spectral bands with 30 m

spatial resolution. Radiometric resolution of ALI is 16-bit (compared to the 8-bit

Landsat). In the present study we mainly used two bands: band 4 (525–605 nm) and

band 5 (630–690 nm). Note that earlier the ALI band numeration corresponded toLandsat one, e.g. the green band (ALI band 4) had number 2 and the red band (ALI

band 5) had number 3. Atmospheric correction of the image was performed by the

dark pixel subtraction method. CDOM concentration in water is usually expressed as

an absorption coefficient of filtrated water at a certain wavelength. We used a

wavelength of 420 nm. The CDOM-retrieval algorithm used was proposed by

Kutser et al. (2005b):

F I N L A N D

E S T O N I A

L A T V I A

Figure 1. Map of the study area. Location of the ALI image used in this study, and shown infigures 2 and 3, is indicated with the frame.

5844 T. Kutser et al.

aCDOMð420Þ ¼ 5:13B4

B5

� ��2:67

; (1)

where aCDOM(420) is the CDOM absorption coefficient at 420 nm, and B4 and B5 are

reflectances in ALI bands band 4 and band 5 respectively.

Surface water samples were taken for laboratory analysis at the same time as the

satellite overpass. Concentration of chlorophyll-a, total suspended matter and CDOM

were measured. The CDOM absorption coefficient spectra were measured against the

reference of distilled water. Samples filtrated through Whatman GF/F filter were used.

There were two water samples taken from the ALI swath area. CDOM concentrations

in these two stations was relatively low (aCDOM(420) = 0.998 m-1 and 1.046 m-1).Chlorophyll-a concentration was 2.7 mg m-3 and 2.6 mg m-3 respectively. Total

suspended matter concentrations were relatively high: 7.9 mg l-1 and 9.8 mg l-1 due

to windy days prior the image acquisition.

M

H

Figure 2. Advanced Land Imager (ALI) true colour image of Muhu Strait, eastern part of theBaltic Sea. The image was acquired on 1 September 2005. Matsalu Bay is indicated with ‘M’ andHaapsalu Bay with ‘H’. The size of the ALI image is 37 · 80 km.

Mapping CDOM in coastal waters 5845

3. Results and discussion

It is seen in the ALI image that both river estuaries in the Muhu Strait area contain

CDOM-rich brown water. Outflow from the Haapsalu Bay (indicated by ‘H’ in figure 2)

is relatively low, while outflow from the Matsalu Bay (indicated by ‘M’ in figure 2) is

significant. Also the CDOM concentration in and near Matsalu Bay is very high. The

aCDOM(420) values exceed 30 m-1 in the Matsalu Bay and are between 5 m-1 and 15 m-1

in the river plume flowing into the Muhu Strait, according to the ALI results (figure 3).

Optical contrast between the Strait waters and the river plume is very distinct despiteCDOM being the dominating optically active substance in the Strait waters. Average

15

9

6

3

0

12

Figure 3. CDOM map of the Muhu Strait obtained from the ALI image using the equation (1).Numbers in the colour bar indicate CDOM absorption at 420 nm (in m-1).

5846 T. Kutser et al.

aCDOM(420) values outside the river plume are around 1.5 m-1 while typical values for

the first plume pixel are around 6–7 m-1, indicating that there is very little mixing

between plume and Strait waters. Mixing is taking place a few kilometres south from

the Matsalu Bay entrance where aCDOM(420) values are 3–4 m-1 in the river plume and

around 2 m-1 in surrounding Strait waters.Unfortunately we do not have in situ CDOM values from the river plume area.

There were only two sampling stations in the area imaged by ALI and both of them

were near islets located in the south-western corner of the ALI image. The

aCDOM(420) values measured in these two stations were 0.998 m-1 and 1.046 m-1

while ALI estimates were 0.79 m-1 and 1.17 m-1 respectively. Values of aCDOM(420) of

more than 30 m-1 were observed in the Matsalu Bay. These kinds of high CDOM

values are not exceptional. For example, aCDOM(420) values up to 33 m-1 have been

measured in Estonian lakes (Arst et al. 2008). Clementson et al. (2004) measuredaCDOM(440) values up to 30 m-1 (which equals 43 m-1 for aCDOM(420)) in the Huon

River estuary in Tasmania, where the optical properties of river water are rather

similar to the Matsalu Bay. Thus, the CDOM estimates for the Matsalu Bay are

realistic.

Clementson et al. (2004) and some other authors have found that CDOM is

inversely correlated with salinity. This is typical for CDOM-rich river plumes in

oceanic waters where dark brown river waters with negligible salinity flow into clear

ocean waters with high salinity. Salinity in the Baltic Sea is low (maximum 6%0 in thestudy area) and CDOM is the dominating optically active substance in the Baltic Sea.

Therefore, it is not expected that there is any correlation between the CDOM con-

centration and water salinity in the study area.

Comparing modelling results (Kutser et al. 2005a) with high CDOM values in the

Matsalu Bay suggests that 8-bit remote sensing instruments (Landsat) and 11-bit

instruments (Ikonos) may not be suitable for mapping CDOM in such CDOM-rich

coastal waters. However, mapping of CDOM concentration in coastal areas off the

CDOM-rich river plumes should be possible also with 8-bit and 11-bit sensors.The CDOM values collected in situ are from the lower end of the concentration

range observed in the study area. Therefore, we cannot conclude with high confidence

that there is a need to adjust the coefficients in equation (1) for the Baltic Sea

conditions. The coefficients varied very little between the modelling study carried

out for a large variety of optically active substances (Kutser et al. 2005a) and the cal/

val activities carried out with ALI images and in situ data (Kutser et al. 2005a, 2005b).

However, slight modifications in the coefficients may give better CDOM estimates for

the Baltic Sea. We do have in situ data where handheld spectrometer measurements(that can be resampled to ALI bands) were performed simultaneously with water

sampling. This will allow us to estimate further suitability of the CDOM retrieval

algorithm shown in equation (1). This, however, is a question of further study.

The ALI image also shows an interesting hydrodynamic effect. Water in the Muhu

Strait was flowing against the general cyclonic circulation of the Baltic Sea during the

image acquisition. This can be explained by difference in water level heights in the

Gulf of Finland (northern end of the ALI image) and Gulf of Riga (south from the

ALI image; see figure 1). The direction of the flow in Muhu Strait can change withinhours (J. Elken, personal communication).

Detailed spatial analysis of the CDOM map obtained from ALI imagery showed

that bottom visibility had impact on the CDOM retrieval results. This means that

optically shallow water areas have to be masked out before calculating CDOM maps.

Mapping CDOM in coastal waters 5847

This can be done using near-IR bands where the water leaving signal is not zero in case

of shallow waters (Vahtmae et al. 2006).

An interesting feature is seen in the centre of the ALI image. Ferries crossing the

Strait from the Estonian mainland to Hiiumaa Island (about a kilometre west of the

area imaged by ALI) have mixed up sediments from the sea bottom. The track of moreturbid water is clearly seen from space.

3. Conclusions

Results of this study show that sensors such as ALI are suitable for mapping CDOM

concentration in coastal waters despite the fact that ALI was designed for landapplications. The 16-bit radiometric resolution also allows detection of variations in

case of very dark objects such as waters with aCDOM(420) values more than 30 m-1.

The CDOM-retrieval algorithm, originally developed for boreal lakes, gave reason-

able results although we were able to validate the results only in the lower end of the

concentration range.

The ALI image showed that optical properties of water in coastal areas like the

Muhu Strait are extremely variable. For example, CDOM concentration varied

4–5 times in case of two adjacent 30 m pixels. This indicates a need for relativelyhigh spatial resolution (30 m or less) remote sensing data in monitoring coastal

environments. The results also highlight the usefulness of remote sensing data in

coastal waters as in situ sampling in a few sparse stations cannot provide adequate

information about spatially very heterogeneous environments.

Acknowledgements

This study was supported by the Estonian Science Foundation grant 6051 and

Estonian Basic Research grant 0712669s05.

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