A satellite remote-sensing multi-index approach to discriminate pelagic Sargassum in the waters of the Yucatan Peninsula, Mexico

ABSTRACT

Recently, the need for quantitative information on the spatiotemporal distribution of floating macroalgae, particularly the two species of genus Sargassum, has grown because of blooms of these species in the Gulf of Mexico and Caribbean Sea. Remote sensing is one of the most frequently used tools to assess pelagic Sargassum distribution. The purpose of this study was to implement a methodological approach to detect floating algae in an efficient and replicable manner at a moderate cost. We analyzed Landsat 8 imagery, from which we calculated four vegetation indices and one floating-algae index to implement a supervised classification, together with the bands 2 and 5, using the Random Forest algorithm. The analysis was performed monthly from 2014 to 2015 for the northeastern Yucatan Peninsula, Mexico, with a total of 91 analyzed images. The quantitative performance metrics of the classifier (overall, Kappa and Tau) were greater than 80%, whereas bands 2 and 5 as well as the atmospherically resistant vegetation index made the greatest contributions to the classifications. During summer 2015, more than 4,000 ha of Sargassum coverage per image were observed, which was substantially greater than that over the rest of the period. This approach constitutes a transferable alternative for the systematic detection of Sargassum, which enables a quantitative semi-automated time series comparison.

Acknowledgments

This work was supported by the Hydrocarbon Fund of the National Council for Science and Technology (SENER-CONACyT Hidrocarburos), project No. 201441, and the funding source did not participate in the design of this assessment. This study is part of project No. 201441 “Implementation of oceanographic observation networks (physical, geochemical, ecological) to generate scenarios in the face of possible contingencies related to hydrocarbon exploration and production in the deep waters of the Gulf of Mexico and it is a contribution of the Gulf of Mexico Research Consortium (CIGoM)”. Thanks to Pronatura Peninsula de Yucatan for its operative support through our collaboration on the project “Assessment and monitoring of ecosystems for immature sea turtles in Yum Balam” (SAM Fund/FMCN A1605007 MEX008-024). We are particularly grateful to Chuanmin Hu, Ph.D. of the College of Marine Science at the University of South Florida for his support and advice concerning the structuring and instrumentation of the satellite image atmospheric correction process. We thank Robert Hardy for sharing his experience on Sargassum detection. We especially thank Héctor Hérnandez Nuñez for preprocessing the images. We also thank David Espinosa Puch for his key contribution to the analysis of the images as part of an internship.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This Research was funded by the National Council of Science and Technology of Mexico - Mexican Ministry of Energy - Hydrocarbon Trust [project 201441]. This is a contribution of the Gulf of Mexico Research Consortium (CIGoM).