The doctoral dissertations of the former Helsinki University of Technology (TKK) and Aalto University Schools of Technology (CHEM, ELEC, ENG, SCI) published in electronic format are available in the electronic publications archive of Aalto University - Aaltodoc.
Aalto

Remote Sensing of Water Quality for Finnish Lakes and Coastal Areas

Sampsa Koponen

Dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the Department of Electrical and Communications Engineering for public examination and debate in Auditorium S4 at Helsinki University of Technology (Espoo, Finland) on the 22nd of December, 2006, at 12 noon.

Overview in PDF format (ISBN 951-22-8534-7)   [1297 KB]
Dissertation is also available in print (ISBN 951-22-8533-9)

Abstract

In this thesis empirical remote sensing methods for estimating water quality in Finnish lakes and coastal areas are developed and tested. The remote sensing instruments used here are Airborne Imaging Spectrometer for Applications (AISA), Medium Resolution Imaging Spectrometer (MERIS) onboard the Envisat-satellite and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the TERRA-satellite.

Based on the results from this study the AISA airborne spectrometer is applicable for estimating chlorophyll a (chl a), Secchi depth, and turbidity in lakes. The 250-m resolution MODIS data are used for estimating turbidity and quality class in lakes. Full resolution (300 m) MERIS data are used for estimating chl a, total suspended solids (TSS) and the absorption coefficient of coloured dissolved organic matter (aCDOM(400)) during a spring bloom event in the Gulf of Finland (a situation where the default MERIS processor fails to provide valid data).

The retrieval of water quality information is based on single channel and channel-ratio algorithms, which are calibrated and tested with in situ (ground truth) observations. The accuracy of the retrieval is good. The results are based on a large number of data points (several thousand in one of the cases). Thus, the reliability of the results is high.

The thematic maps and statistics derived with remote sensing data demonstrate the advantages of remote sensing over the traditional water quality monitoring, which is based on in situ measurements. The main shortcoming of presented methods is that since the algorithms are based on empirical relationships, which include atmospheric effects, they require calibration (for different atmospheric parameters) before they can be used with other remotely sensed images. The effects of the atmosphere on MERIS channel-ratio algorithms are estimated with an atmospheric model.

This thesis consists of an overview and of the following 6 publications:

  1. Koponen, S., Pulliainen, J., Servomaa, H., Zhang, Y., Hallikainen, M., Kallio, K., Vepsäläinen, J., Pyhälahti, T., and Hannonen, T., Analysis on the feasibility of multi-source remote sensing observations for chl-a monitoring in Finnish lakes. The Science of the Total Environment, vol. 268, nos. 1-3, pp. 95-106, 2001. © 2001 Elsevier Science. By permission.
  2. Kallio, K., Koponen, S., and Pulliainen, J., Feasibility of airborne imaging spectrometry for lake monitoring—a case study of spatial chlorophyll a distribution in two meso-eutrophic lakes. International Journal of Remote Sensing, vol. 24, no. 19, pp. 3771-3790, 2003. © 2003 Taylor & Francis. By permission.
  3. Koponen, S., Attila, J., Pulliainen, J., Kallio, K., Pyhälahti, T., Lindfors, A., Rasmus, K., and Hallikainen, M., A case study of airborne and satellite remote sensing of a spring bloom event in the Gulf of Finland. Continental Shelf Research, in press, 2006. © 2006 by authors and © 2006 Elsevier Science. By permission.
  4. Koponen, S., Pulliainen, J., Kallio, K., Vepsäläinen, J., and Hallikainen, M., Use of MODIS data for monitoring turbidity in Finnish Lakes. Proceedings of the IEEE 2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001), CD-ROM, 3 p., Sydney, Australia, 9-13 July, 2001.
  5. Koponen, S., Pulliainen, J., Kallio, K., and Hallikainen, M., Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data. Remote Sensing of Environment, vol. 79, no. 1, pp. 51-59, 2002. © 2002 Elsevier Science. By permission.
  6. Koponen, S., Pulliainen, J., Kallio, K., Vepsäläinen, J., Pyhälahti, T., and Hallikainen, M., Water quality classification of lakes using 250-m MODIS data. IEEE Geoscience and Remote Sensing Letters, vol. 1, no. 4, pp. 287-291, 2004. © 2004 IEEE. By permission.

Keywords: remote sensing, water quality, MERIS, MODIS, AISA

This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.

© 2006 Helsinki University of Technology

Last update 2011-05-26