Project Funding: 2017 - 2021

NRA: 2016 NASA: Ecological Forecasting   

Funded by NASA

Abstract:
Floating mats of pelagic Sargassum macroalgae serve as an ecologically important habitat for many marine animals and therefore are regarded by the Sargasso Sea Commission as “the golden floating rainforest of the Atlantic Ocean.” On the other hand, excessive Sargassum beaching has become an increasing nuisance in the Caribbean since 2011. Recent efforts, mainly funded by NASA, led to the ground-breaking work of using Landsat and MODIS to map Sargassum, and to the establishment of a prototype decision-making tool to track large Sargassum mats in near real-time, the Sargassum Watch System (SaWS, http://optics.marine.usf.edu/projects/saws.html). Yet several improvements are required to maximize its full potential. Thus, based on the existing infrastructure (hardware, software, personnel) and the established prototype SaWS, the goal of this project is to further develop and improve SaWS in its data products and in both its long-term and short-term forecasting capacity to better serve the community. Specifically, the project has the following objectives: 1) Expand SaWS coverage to include waters off Africa and Brazil, where Sargassum beaching has been reported but currently there is no near real-time imagery support 2) Determine Sargassum distribution and abundance as well as their seasonality, inter-annual variability, and long-term trend with uncertainty estimates for the IAS and other regions 3) Develop a forecasting model to predict Sargassum blooms in different ocean basins, and determine likelihood of Sargassum beaching for each Caribbean nation or region; 4) Establish short-term forecasting capacity in predicting Sargassum transport, and implement such a capacity for near real-time use in the SaWS 5) Generate and distribute weekly and biweekly composites of value-added products in the SaWS to avoid arbitrary interpretation of imagery by untrained users 6) Increase the user base for SaWS in order to maximize the potential of NASA data for community use 7) Make SaWS quasi-operational and sustainable to benefit society, and make it a template for other regions to monitor and respond to macroalgae blooms. The project will be conducted through multi-sensor remote sensing, statistical analysis, modeling, image processing, computer programming, and interactions and collaborations with various user groups. Indeed, based on previous efforts, SaWS is at approximately ARL 4 already, with some components of ARLs 5 – 9 also implemented. However, without dedicated effort and innovations SaWS is currently at its maximum capacity. The project will make significant improvements in this prototype decision-making tool through achieving the 7 specific objectives, thus contributing directly to the ultimate goal of NASA Applied Science. We expect the following outputs: 1) Enhanced SaWS to distribute new value-added data products in near real-time to help make near real-time decisions (beaching management, tourism, cruise planning, etc) through improved short-term forecast of Sargassum transport and beaching potentials; 2) Long-term spatial-temporal distributions of Sargassum abundance in the IAS and other regions with uncertainty estimates and improved understanding of their climate and environmental controls, which will provide baseline data to help implement/improve Sargassum management plans; 3) Long-term forecast of likelihood of Sargassum blooms with several months of lead time to inform relevant stakeholders for long-term planning; 4) Technical reports, publications, and a sustained system to facilitate use of NASA data to help make management and research decisions. The end users of the improved SaWS range from Federal and state agencies to educational institutions, environmental groups, and private entities. These may include: National Marine Fisheries Service (NMFS), the Sargasso Sea Commission, airline companies, beach management agencies, and tourism industry.

Publications:

Hardy, R. F., Hu, C., Witherington, B., Lapointe, B., Meylan, A., Peebles, E., Meirose, L., Hirama, S. 2018. Characterizing a Sea Turtle Developmental Habitat Using Landsat Observations of Surface-Pelagic Drift Communities in the Eastern Gulf of Mexico. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(10), 3646-3659. DOI: 10.1109/jstars.2018.2863194

Hu, C. 2021. Remote detection of marine debris using satellite observations in the visible and near infrared spectral range: Challenges and potentials. Remote Sensing of Environment. 259, 112414. DOI: 10.1016/j.rse.2021.112414

Hu, C. 2022. Hyperspectral reflectance spectra of floating matters derived from Hyperspectral Imager for the Coastal Ocean (HICO) observations. Earth System Science Data. 14(3), 1183-1192. DOI: 10.5194/essd-14-1183-2022

Hu, C. 2022. Hyperspectral reflectance spectra of floating matters derived from Hyperspectral Imager for the Coastal Ocean (HICO) observations. Earth System Science Data. 14(3), 1183-1192. DOI: 10.5194/essd-14-1183-2022

Hu, C. 2022. Remote detection of marine debris using Sentinel-2 imagery: A cautious note on spectral interpretations. Marine Pollution Bulletin. 183, 114082. DOI: 10.1016/j.marpolbul.2022.114082

Hu, C. Hyperspectral reflectance spectra of floating matters derived from HICO observations DOI: 10.5194/essd-2021-321

Hu, C. Potential impacts of tropical cyclones on pelagic Sargassum DOI: 10.1002/essoar.10511045.1

Hu, C. Potential impacts of tropical cyclones on pelagic Sargassum DOI: 10.1002/essoar.10511045.1

Hu, C., Zhang, S., Barnes, B. B., Xie, Y., Wang, M., Cannizzaro, J. P., English, D. C. 2023. Mapping and quantifying pelagic Sargassum in the Atlantic Ocean using multi-band medium-resolution satellite data and deep learning. Remote Sensing of Environment. 289, 113515. DOI: 10.1016/j.rse.2023.113515

Hu, C., Zhang, S., Barnes, B. B., Xie, Y., Wang, M., Cannizzaro, J. P., English, D. C. 2023. Mapping and quantifying pelagic Sargassum in the Atlantic Ocean using multi-band medium-resolution satellite data and deep learning. Remote Sensing of Environment. 289, 113515. DOI: 10.1016/j.rse.2023.113515

Hu, C., Zhang, S., Barnes, B. B., Xie, Y., Wang, M., Cannizzaro, J. P., English, D. C. 2023. Mapping and quantifying pelagic Sargassum in the Atlantic Ocean using multi-band medium-resolution satellite data and deep learning. Remote Sensing of Environment. 289, 113515. DOI: 10.1016/j.rse.2023.113515

Lapointe, B. E., Brewton, R. A., Herren, L. W., Wang, M., Hu, C., McGillicuddy, D. J., Lindell, S., Hernandez, F. J., Morton, P. L. 2021. Nutrient content and stoichiometry of pelagic Sargassum reflects increasing nitrogen availability in the Atlantic Basin. Nature Communications. 12(1). DOI: 10.1038/s41467-021-23135-7

Le Henaff, M., Kourafalou, V. H., Androulidakis, Y., Smith, R. H., Kang, H., Hu, C., Lamkin, J. T. 2020. In Situ Measurements of Circulation Features Influencing Cross-Shelf Transport Around Northwest Cuba. Journal of Geophysical Research: Oceans. 125(7). DOI: 10.1029/2019JC015780

Putman, N. F., Goni, G. J., Gramer, L. J., Hu, C., Johns, E. M., Trinanes, J., Wang, M. 2018. Simulating transport pathways of pelagic Sargassum from the Equatorial Atlantic into the Caribbean Sea. Progress in Oceanography. 165, 205-214. DOI: 10.1016/j.pocean.2018.06.009

Qi, L., Hu, C., Mikelsons, K., Wang, M., Lance, V., Sun, S., Barnes, B. B., Zhao, J., Van der Zande, D. 2020. In search of floating algae and other organisms in global oceans and lakes. Remote Sensing of Environment. 239, 111659. DOI: 10.1016/j.rse.2020.111659

Rodriguez-Martinez, R. E., Jordan-Dahlgren, E., Hu, C. 2022. Spatio-temporal variability of pelagic Sargassum landings on the northern Mexican Caribbean. Remote Sensing Applications: Society and Environment. 27, 100767. DOI: 10.1016/j.rsase.2022.100767

Rodriguez-Martinez, R. E., Jordan-Dahlgren, E., Hu, C. 2022. Spatio-temporal variability of pelagic Sargassum landings on the northern Mexican Caribbean. Remote Sensing Applications: Society and Environment. 27, 100767. DOI: 10.1016/j.rsase.2022.100767

Trinanes, J., Putman, N. F., Goni, G., Hu, C., Wang, M. 2021. Monitoring pelagic Sargassum inundation potential for coastal communities. Journal of Operational Oceanography. 16(1), 48-59. DOI: 10.1080/1755876X.2021.1902682

Wang, M., Hu, C. 2018. On the continuity of quantifying floating algae of the Central West Atlantic between MODIS and VIIRS. International Journal of Remote Sensing. 39(12), 3852-3869. DOI: 10.1080/01431161.2018.1447161

Wang, M., Hu, C. 2021. Automatic Extraction of Sargassum Features From Sentinel-2 MSI Images. IEEE Transactions on Geoscience and Remote Sensing. 59(3), 2579-2597. DOI: 10.1109/TGRS.2020.3002929

Wang, M., Hu, C. 2021. Satellite remote sensing of pelagic Sargassum macroalgae: The power of high resolution and deep learning. Remote Sensing of Environment. 264, 112631. DOI: 10.1016/j.rse.2021.112631

Wang, M., Hu, C., Cannizzaro, J., English, D., Han, X., Naar, D., Lapointe, B., Brewton, R., Hernandez, F. 2018. Remote Sensing of Sargassum Biomass, Nutrients, and Pigments. Geophysical Research Letters. 45(22), 12,359-12,367. DOI: 10.1029/2018GL078858

Wang, Z., Townsend, P. A., Schweiger, A. K., Couture, J. J., Singh, A., Hobbie, S. E., Cavender-Bares, J. 2019. Mapping foliar functional traits and their uncertainties across three years in a grassland experiment. Remote Sensing of Environment. 221, 405-416. DOI: 10.1016/j.rse.2018.11.016

Zhang, S., Hu, C., Barnes, B. B., Harrison, T. N. 2022. Monitoring Sargassum Inundation on Beaches and Nearshore Waters Using PlanetScope/Dove Observations. IEEE Geoscience and Remote Sensing Letters. 19, 1-5. DOI: 10.1109/LGRS.2022.3148684

Zhang, Y., Hu, C. 2021. Ocean Temperature and Color Frontal Zones in the Gulf of Mexico: Where, When, and Why. Journal of Geophysical Research: Oceans. 126(10). DOI: 10.1029/2021JC017544

Zhang, Y., Hu, C., Barnes, B. B., Liu, Y., Kourafalou, V. H., McGillicuddy, D. J., Cannizzaro, J. P., English, D. C., Lembke, C. 2023. Bio-Optical, Physical, and Chemical Properties of a Loop Current Eddy in the Gulf of Mexico. Journal of Geophysical Research: Oceans. 128(3). DOI: 10.1029/2022JC018726

Zhang, Y., Hu, C., Barnes, B. B., Liu, Y., Kourafalou, V. H., McGillicuddy, D. J., Cannizzaro, J. P., English, D. C., Lembke, C. 2023. Bio-Optical, Physical, and Chemical Properties of a Loop Current Eddy in the Gulf of Mexico. Journal of Geophysical Research: Oceans. 128(3). DOI: 10.1029/2022JC018726

More details may be found in the following project profile(s):

• NASA Biological Diversity & Ecological Conservation (BDEC) Project Profile