Abstract
We analyzed 27 established and new simple and therefore perhaps portable satellite phycocyanin pigment reflectance algorithms for estimating cyanobacterial values in a temperate 8.9 km2 reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense coincident water surface observations collected from 44 sites within 1 h of image acquisition. The algorithms were adapted to real Compact Airborne Spectrographic Imager (CASI), synthetic WorldView-2, Sentinel-2, Landsat-8, MODIS and Sentinel-3/MERIS/OLCI imagery resulting in 184 variants and corresponding image products. Image products were compared to the cyanobacterial coincident surface observation measurements to identify groups of promising algorithms for operational algal bloom monitoring. Several of the algorithms were found useful for estimating phycocyanin values with each sensor type except MODIS in this small lake. In situ phycocyanin measurements correlated strongly (r2 = 0.757) with cyanobacterial sum of total biovolume (CSTB) allowing us to estimate both phycocyanin values and CSTB for all of the satellites considered except MODIS in this situation.
Highlights
IntroductionHABs are often associated with prokaryotic cyanobacteria (i.e., blue-green algae (BGA)) [1]
Strong correlations (Pearson’s r2 > 0.6; p < 0.001) between image derived indices and dense coincident surface observations of BGA during this experiment indicate that Be162BsubPhy, SI052BDA, Be162B700sub601, Be16NDPhyI, Gi033BDA, Da052BDA, SM122BDA, Ku15PhyCI, MM092BDA, MI092BDA, Wy08CI, Zh10FLH, and MM12NDCI BGA algorithms worked well with Compact Airborne Spectrographic Imager (CASI) imagery
Be162Bsub algorithm with simulated Sentinel-2 imagery; the Be16FLHviolet with simulated Landsat-8 imagery; and the MM092BDA, Be16NDPhyI, MM12NDCI, Go04MCI, Ku15PhyCI, Wy08CI, SI052BDA, Be162BsubPhy, and Hu103BDA BGA algorithms with simulated Sentinel-3/MERIS/OLCI imagery
Summary
HABs are often associated with prokaryotic cyanobacteria (i.e., blue-green algae (BGA)) [1]. These HABs have made the development of satellite reflectance algorithms for the estimation of the chlorophyll-a (Chl-a) and phycocyanin (PC) pigments associated with cyanobacterial biomass a high research priority for monitoring and warning efforts [3,4,5,6]. Satellite reflectance algorithms for estimating BGA values with algorithms focused on phycocyanin reflectance signatures in temperate inland water bodies have been reviewed and evaluated by many researchers [10,11,14,16,22]. The large amount of previous BGA algorithm research has resulted in numerous algorithm options for algal bloom monitoring
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