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Evaluation and Optimization of Remote Sensing Techniques for Detection of Karenia Brevis Blooms on the West Florida Shelf
Remote Sensing of Environment
  • I. M Soto
  • Jennifer Cannizzaro, University of South Florida
  • Frank E Muller-Karger, University of South Florida
  • Chuanmin Hu, University of South Florida
  • J. Wolny
  • Dmitry Goldgof, University of South Florida
Document Type
Publication Date
  • Detection techniques,
  • Harmful Algal Bloom (HAB),
  • Karenia brevis,
  • MODIS,
  • Ocean color,
  • Red tide,
  • West Florida Shelf
Digital Object Identifier (DOI)

We evaluated the performance of several published algorithms designed to detect Karenia brevis blooms on the West Florida Shelf using satellite imagery. Algorithms were tested using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images and historical ground-truth observations collected from August 2002 to December 2011. A total of 2323 phytoplankton cell count samples collected by the Florida Fish and Wildlife Conservation Commission (FWC) matched valid ocean color satellite observations over this period. Techniques were tested using the F-measure (FM) statistic. FM evaluates the proportion of image pixels that matches or misclassifies ground-based K. brevis observations. Several ocean color data products, such as normalized Fluorescence Line Height (nFLH), were also tested independently or combined to evaluate their effectiveness to detect K. brevis blooms. Techniques were optimized by altering their specific thresholds until the maximum FM was obtained. The historical techniques with the best performance were the Red Band Difference (RBD) and the Rrs-nFLH technique. This last method (Rrs-nFLH) is a combination of two standard ocean color data products: nFLH (>0.033mWcm-2μm-1sr-1) and the remote sensing reflectance at 555nm (Rrs555<0.007sr-1). Both techniques resulted in an FM of 0.62 and less than 3% false positives. The performance of most of the techniques improved significantly after optimization (the average FM increased from 0.47 to 0.57). The addition of a nFLH criterion improved the performance of most methods. We provide a list of recommendations on how to best apply the various techniques.

Citation / Publisher Attribution
Remote Sensing of Environment, v. 170, p. 239-254
Citation Information
I. M Soto, Jennifer Cannizzaro, Frank E Muller-Karger, Chuanmin Hu, et al.. "Evaluation and Optimization of Remote Sensing Techniques for Detection of Karenia Brevis Blooms on the West Florida Shelf" Remote Sensing of Environment Vol. 170 (2015) p. 239 - 254
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