Analysis on the feasibility of multi-source remote sensing observations for chl-a monitoring in Finnish lakes

Chiorophyll-a (chl-a) concentration of lake water can be measured with airb orne (or spaceborne) optical remote sensing instruments. The rmse obtained here with empirical algorithms and 122 measurement points was 8.9 mug/l (al l points used for training and testing). Airborne Imaging Spectrometer for Applications (AISA) was used in four lake water quality measurement campaig ns (8 measurement days) in southern Finland during 1996-1998 with other air borne instruments and extensive in situ data collection. As empirical algor ithms are employed for chi-a retrieval from remote sensing data, temporally varying factors such as surface reflection and atmospheric effects degrade the estimation accuracy. This paper analyzes the quantitative accuracy of empirical chi-a retrieval algorithms available as methods to correct tempor al disturbances are either included or excluded. The aim is to evaluate the usability of empirical chi-a retrieval algorithms in cases when no concurr ent reference in situ data are available. Four methods to reduce the effect s of temporal variations are investigated. The methods are: (1) atmospheric correction; (2) synchronous radiometer data; (3) wind speed data; and (4) bidirectional scattering model based on wind speed and sun angle data. The effects of different correction methods are analyzed by using single-dare t est data and multi-date training data sets. The results show that the use o f a bidirectional scattering model and atmospheric correction reduces the b ias component of the measurement error. Radiometer data also appear to impr ove the accuracy. However, if concurrent in situ reference data are not ava ilable, the retrieval algorithms and correction methods should be improved for reducing the bias error. (C) 2001 Elsevier Science B.V. All rights rese rved.