APPLICATION OF HYPERSPECTRAL IMAGERY AND DIGITAL VIDEOGRAPHY TO MANAGE ALGAL BLOOMS IN AQUACULTURE SYSTEMS: CURRENT STATUS

摘要

Detection of harmful algal blooms in Case II hypereutrophic aquaculture systems continues to be a challenge. Attempts to isolate certain pond constituents have been difficult because both organic matter and suspended sediments can mask detection of these components. A three band reciprocal reflectance model, originally developed to detect Chlorophyll-a (Chl-a) in terrestrial vegetation, had been tuned previously for detection of Chl-a in catfish production ponds at the USDA-ARS Stoneville, MS research facility using pond samples and spectroradiometer data. To test the model's robustness, this study applied the tuned model to two other data sets from the same ponds. The strength of the model was confirmed by goodness of fit to these data. The good results are also noteworthy by the fact that spectroradiometer readings for the calibration data set were taken slightly below the water surface whereas readings for the evaluation sets were taken above the water surface, the latter possibly introducing specular reflection effects. Some model fits indicated peculiar outliers which, on preliminary analysis, indicated the presence of very high concentrations of Phaeophytin (Chl-a degradation products). Remote sensing systems to detect Chl-a in catfish production ponds can be adapted by selection of narrow-band optical filters with band centers at 650, 710, and 740 nm.