414
T. J. Ballatore et al.
Horion et al. (2010) used standard and adapted MODIS Aqua Ocean Color products to create regionally calibrated products for chlorophyll-a concentration and
attenuation coefficients at 490 nm [K d (490)] for Lake Tanganyika. The examination of known targets using clear sky images revealed the standard atmospheric
correction method to be inadequate for Lake Tanganyika. An aerosol correction
model designed for coastal regions with 90 % humidity proved the most effective approach. When using this atmospheric correction, the regression between the standard
Ocean Color Group algorithm for chlorophyll-a concentration and in situ chlorophyll
concentration had an offset near 0, a slope near 1, and an rmse around 20 %.
MODIS-derived chlorophyll-a estimations revealed a pattern of higher concentration events compared to field sampling. The high chlorophyll values seemed linked
to increases in cyanobacteria abundance in surface waters, and often occurred near
the onset of the rainy season. The authors concluded that their MODIS-based estimates of chlorophyll-a provided a good approximation of actual concentrations in
the upper water column. Bergamino et al. (2010) relied on the regionally calibrated
chlorophyll-a product developed by Horion et al. (2010) to examine the spatiotemporal dynamics of phytoplankton in Lake Tanganyika. The daily phytoplankton
photosynthesis per unit area of Lake Tanganyika was modeled and the daily primary
production of the whole lake was estimated by weighting the averages according to
the relative area of each region.
Based on an EOF analysis, 13 co-varying regions in Lake Tanganyika were identified. These data show that the traditional division of the lake into three lake basins is
largely correct, and the observed temporal patterns revealed significant differences in
estimated concentrations between the regions. The dry season was found to be more
productive than the wet season, with the southern section exhibiting two peaks in
primary production and the central and northern sections exhibiting a single, smaller
peak. The observations of these trends indicated the usefulness of satellite-based
analysis for Lake Tanganyika, providing the possibility to examine long-term and
short-term changes in lake dynamics.
Matthews et al. (2010) used MERIS imagery to assess the suitability of a variety
of algorithms for use in cyanobacteria-rich waters. Empirical algorithms resulted in
high correlation values, but were found to be of limited use to separate signals from
co-varying in-water constituents. Semi-analytical algorithms were not successful,
due to poor atmospheric correction techniques and training ranges of key optical
variables not being appropriate for a water body of this type. A major conclusion of
this study was the observation that top of atmosphere satellite data could be used to
detect hypereutrophic conditions in inland waters.
Cózar et al. (2012) used water-leaving radiances from the SeaWiFS sensor to
estimate chlorophyll-a concentration in Lake Victoria by way of the Maximum Band
Ratio (MBR) using the OC4.v4 algorithm. Statistical analysis of the relative optical
variability within the lake provided the means for assessing bio-optical, and thus,
limnological variability and lake dynamics. In addition, AVHRR imagery was used
in this study to calculate lake surface temperature to examine the changes in water
column stability. Seasonal increases in lake surface temperature in the North Region
coincided with rises in the estimated chlorophyll concentration, while the South
T. J. Ballatore et al.
Horion et al. (2010) used standard and adapted MODIS Aqua Ocean Color products to create regionally calibrated products for chlorophyll-a concentration and
attenuation coefficients at 490 nm [K d (490)] for Lake Tanganyika. The examination of known targets using clear sky images revealed the standard atmospheric
correction method to be inadequate for Lake Tanganyika. An aerosol correction
model designed for coastal regions with 90 % humidity proved the most effective approach. When using this atmospheric correction, the regression between the standard
Ocean Color Group algorithm for chlorophyll-a concentration and in situ chlorophyll
concentration had an offset near 0, a slope near 1, and an rmse around 20 %.
MODIS-derived chlorophyll-a estimations revealed a pattern of higher concentration events compared to field sampling. The high chlorophyll values seemed linked
to increases in cyanobacteria abundance in surface waters, and often occurred near
the onset of the rainy season. The authors concluded that their MODIS-based estimates of chlorophyll-a provided a good approximation of actual concentrations in
the upper water column. Bergamino et al. (2010) relied on the regionally calibrated
chlorophyll-a product developed by Horion et al. (2010) to examine the spatiotemporal dynamics of phytoplankton in Lake Tanganyika. The daily phytoplankton
photosynthesis per unit area of Lake Tanganyika was modeled and the daily primary
production of the whole lake was estimated by weighting the averages according to
the relative area of each region.
Based on an EOF analysis, 13 co-varying regions in Lake Tanganyika were identified. These data show that the traditional division of the lake into three lake basins is
largely correct, and the observed temporal patterns revealed significant differences in
estimated concentrations between the regions. The dry season was found to be more
productive than the wet season, with the southern section exhibiting two peaks in
primary production and the central and northern sections exhibiting a single, smaller
peak. The observations of these trends indicated the usefulness of satellite-based
analysis for Lake Tanganyika, providing the possibility to examine long-term and
short-term changes in lake dynamics.
Matthews et al. (2010) used MERIS imagery to assess the suitability of a variety
of algorithms for use in cyanobacteria-rich waters. Empirical algorithms resulted in
high correlation values, but were found to be of limited use to separate signals from
co-varying in-water constituents. Semi-analytical algorithms were not successful,
due to poor atmospheric correction techniques and training ranges of key optical
variables not being appropriate for a water body of this type. A major conclusion of
this study was the observation that top of atmosphere satellite data could be used to
detect hypereutrophic conditions in inland waters.
Cózar et al. (2012) used water-leaving radiances from the SeaWiFS sensor to
estimate chlorophyll-a concentration in Lake Victoria by way of the Maximum Band
Ratio (MBR) using the OC4.v4 algorithm. Statistical analysis of the relative optical
variability within the lake provided the means for assessing bio-optical, and thus,
limnological variability and lake dynamics. In addition, AVHRR imagery was used
in this study to calculate lake surface temperature to examine the changes in water
column stability. Seasonal increases in lake surface temperature in the North Region
coincided with rises in the estimated chlorophyll concentration, while the South