Lake water quality classification with airborne multichannel spectrometer

Remote sensing methods for water quality assessment are discussed. Secchi depth, turbidity and chlorophyll-a concentration are important variables. Remote sensing offers some advantages such as good spatial and temporal coverage and the possibility of measuring many lakes simultaneously. With remote sensing some variables of lake water quality could potentially be assessed up to several times per year. Remote sensing instruments can also measure lakes that are not currently monitored and possibly reduce the amount of water sampling measurements needed for the assessment. In order to study the usability of remote sensing for water quality measurements, the Laboratory of Space Technology of the Helsinki University of Technology together with the Finnish Environment Institute (FEI) conducted four airborne remote sensing and ground truth measurement campaigns in Southern Finland during 1996-1998. The campaigns were part of the EU-funded Salmon project and national water quality remote sensing projects. This paper investigates the feasibility of remote sensing data for operational lake water classification. While numerous papers describe remote sensing methods used for water quality estimation, the classification of lake water quality has not been previously investigated using as many variables and as large data set as the present study.