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We investigated the use of Landsat ETM+ images in the monitoring of turbidity, colored dissolved organic matter (CDOM), and Secchi disk transparency (Z(SD)) in lakes of two river basins located in southern Finland. The ETM+ images were acquired in May, June, and September 2002 and were corrected for atmospheric disturbance using the simplified method of atmospheric correction (SMAC) model. The in situ measurements consisted of water sampling in the largest lake of the region, routine monitoring results for the whole study area, and Z(SD) observations made by volunteers. The ranges of the water quality variables in the dataset were as follows: turbidity, 0.6-25 FNU; absorption coefficient of CDOM at 400 nm, 1.0-12.2 m(-1); Z(SD), 0.5-5.5 m; and chlorophyll a concentration, 2.4-80 microg L(-1). The estimation accuracies of the image-specific empirical algorithms expressed as relative errors were 23.0% for turbidity, 17.4% for CDOM, and 21.1% for Z(SD). If concurrent in situ measurements had not been used for algorithm training, the average error would have been about 37%. The atmospheric correction improved the estimation accuracy only slightly compared with the use of top-of-atmospheric reflectances. The accuracy of the water quality estimates without concurrent in situ measurements could have been improved if in-image atmospheric parameters had been available. The underwater reflectance simulations of the ETM+ channel wavelengths using water quality typical for Finnish lakes (data from 1113 lakes) indicated that region-specific algorithms may be needed in other parts of the country, particularly in the case of Z(SD). Despite the limitations in the spectral and radiometric resolutions, ETM+ imagery can be an effective aid, particularly in the monitoring and management of small lakes (<1 km(2)), which are often not included in routine monitoring programs.

This paper describes the ideas, data and methods to produce Finnish Corine Land Cover 2006 (CLC2006) classification. This version is based on use of existing national GIS data and satellite images and their automated processing, instead of visual interpretation of satellite images. The main idea is that land use information is based on GIS datasets and land cover information interpretation of satellite images. Because Finland participated to CLC2000-project, also changes between years 2000 and 2006 are determined. Finnish approach is good example how national GIS data is used to produce data fulfilling European needs in bottom-up fashion.

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