Project Funding: 2014 - 2016

NRA: 2013 NASA: The Science of Terra and Aqua   

Funded by NASA

Abstract:
Excellent near real-time land and atmosphere applications have been developed using MODIS observations (e.g., fire and smoke detection at NASA's Land, Atmosphere Near- Real-Time Capability for EOS or LANCE). In contrast, near real-time ocean applications have relied mostly on traditional ocean products (e.g., chlorophyll-a concentrations, sea surface temperature) that are developed by the MODIS ocean team to achieve high accuracy. The accuracy requirement, critical for science studies, led to the compromise of coverage, suggesting alternative approaches for algorithm design to fulfill near real-time needs of data coverage and timely information. In addition, non-traditional data products for near real-time applications also require new algorithms.  Thus, the goal of this project is to maximize the potentials of MODIS/Terra and MODIS/Aqua for near real-time ocean applications through developing new algorithms and refining existing prototype algorithms. Specifically, the following algorithms and products will be the project focus in order to better respond to marine hazards and plan for field measurements: 1. Floating Algae Index algorithm to detect pelagic macro algae and other floating materials. The prototype algorithm has been developed already, yet a refinement is required to better differentiate floating algae from clouds and to minimize cross-sensor differences. The cloudmasking also requires new algorithms; 2. Color Index algorithm to trace ocean color features (eddies, plumes, circulation). The prototype CI has been developed to be torrent to thin clouds, thick aerosols, and strong sun glint and therefore shows significant improvement in coverage over the traditional accuracy-driven ocean color products. Yet better ozone and Rayleigh correction are required to improve product consistency between different solar/viewing geometry; 3. Feature tracking algorithm to derive surface ocean current vectors from sequential CI images from Terra and Aqua (3 hours apart); 4. Image normalization and segmentation algorithms to delineate oil slicks. MODIS sun glint imagery has been used to visualize surface oil slicks through manual color stretch and manual delineation, yet automatic delineation of slicks and image normalization are required for more objective analyses. A Virtual Antenna System (VAS) has been established to generate prototype near real- time products. The VAS downloads MODIS low-level data from NASA, processes them using prototype algorithms, and then makes them available on a customized Web site that serves more than 60 countries on a daily basis. The proposed algorithm development and refinement will significantly enhance the near real-time applications through improving the quality of existing products and through developing new products. The proposed work will focus on MODIS/Terra and MODIS/Aqua, yet the approaches will be extended to sister sensors such as VIIRS to assure continuity and, in particular, will lay the ground for future satellite missions such as GEO-CAPE and HyspIRI. The proposal is in response to ROSES2013 A.28 Theme 2.3: "Real- or Near-Real-Time Data Algorithms", which asks for "proposals to enhance, refine, or develop near real time algorithms for application and operational usage." Indeed, nearly all real-time ocean applications have relied on traditional ocean products, yet in the past several years the non-traditional products as outlined above have found wide applications by a variety of user groups. The proposal seeks to enhance these prototype algorithms and applications to maximize the potentials of NASA capacity enabled by Terra and Aqua to better serve the global communities. If the proposal is selected for funding, the PI wishes to become a member of the Ocean Biology and Biogeochemistry Measurements Team.

Publications:

Androulidakis, Y., Kourafalou, V., Le Henaff, M., Kang, H., Sutton, T., Chen, S., Hu, C., Ntaganou, N. 2019. Offshore Spreading of Mississippi Waters: Pathways and Vertical Structure Under Eddy Influence. Journal of Geophysical Research: Oceans. 124(8), 5952-5978. DOI: 10.1029/2018JC014661

Androulidakis, Y., Kourafalou, V., Ozgokmen, T., Garcia-Pineda, O., Lund, B., Le Henaff, M., Hu, C., Haus, B. K., Novelli, G., Guigand, C., Kang, H., Hole, L., Horstmann, J. 2018. Influence of River-Induced Fronts on Hydrocarbon Transport: A Multiplatform Observational Study. Journal of Geophysical Research: Oceans. 123(5), 3259-3285. DOI: 10.1029/2017JC013514

Barnes, B. B., Garcia, R., Hu, C., Lee, Z. 2018. Multi-band spectral matching inversion algorithm to derive water column properties in optically shallow waters: An optimization of parameterization. Remote Sensing of Environment. 204, 424-438. DOI: 10.1016/j.rse.2017.10.013

Barnes, B. B., Hu, C. 2016. Dependence of satellite ocean color data products on viewing angles: A comparison between SeaWiFS, MODIS, and VIIRS. Remote Sensing of Environment. 175, 120-129. DOI: 10.1016/j.rse.2015.12.048

Cannizzaro, J. P., Barnes, B. B., Hu, C., Corcoran, A. A., Hubbard, K. A., Muhlbach, E., Sharp, W. C., Brand, L. E., Kelble, C. R. 2019. Remote detection of cyanobacteria blooms in an optically shallow subtropical lagoonal estuary using MODIS data. Remote Sensing of Environment. 231, 111227. DOI: 10.1016/j.rse.2019.111227

Chen, S., Hu, C., Barnes, B. B., Xie, Y., Lin, G., Qiu, Z. 2019. Improving ocean color data coverage through machine learning. Remote Sensing of Environment. 222, 286-302. DOI: 10.1016/j.rse.2018.12.023

Cunning, R., Silverstein, R. N., Barnes, B. B., Baker, A. C. 2019. Extensive coral mortality and critical habitat loss following dredging and their association with remotely-sensed sediment plumes. Marine Pollution Bulletin. 145, 185-199. DOI: 10.1016/j.marpolbul.2019.05.027

Feng, L., Hu, C. 2016. Cloud adjacency effects on top-of-atmosphere radiance and ocean color data products: A statistical assessment. Remote Sensing of Environment. 174, 301-313. DOI: 10.1016/j.rse.2015.12.020

Feng, L., Hu, C., Li, J. 2018. Can MODIS Land Reflectance Products be Used for Estuarine and Inland Waters? Water Resources Research. 54(5), 3583-3601. DOI: 10.1029/2017WR021607

Long, J. S., Hu, C., Wang, M. 2017. Long-term spatiotemporal variability of southwest Florida whiting events from MODIS observations. International Journal of Remote Sensing. 39(3), 906-923. DOI: 10.1080/01431161.2017.1392637

Marechal, J., Hellio, C., Hu, C. 2017. A simple, fast, and reliable method to predict Sargassum washing ashore in the Lesser Antilles. Remote Sensing Applications: Society and Environment. 5, 54-63. DOI: 10.1016/j.rsase.2017.01.001

Qi, L., Tsai, S., Chen, Y., Le, C., Hu, C. 2019. In Search of Red Noctiluca scintillans Blooms in the East China Sea. Geophysical Research Letters. 46(11), 5997-6004. DOI: 10.1029/2019GL082667

Wang, M., Hu, C. 2017. PredictingSargassumblooms in the Caribbean Sea from MODIS observations. Geophysical Research Letters. 44(7), 3265-3273. DOI: 10.1002/2017GL072932

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., Barnes, B. B., Mitchum, G., Lapointe, B., Montoya, J. P. 2019. The great Atlantic Sargassum belt. Science. 365(6448), 83-87. DOI: 10.1126/science.aaw7912

Weisberg, R. H., Liu, Y., Lembke, C., Hu, C., Hubbard, K., Garrett, M. 2019. The Coastal Ocean Circulation Influence on the 2018 West Florida Shelf K . brevis Red Tide Bloom. Journal of Geophysical Research: Oceans. 124(4), 2501-2512. DOI: 10.1029/2018JC014887

Zhang, M., Hu, C., Cannizzaro, J., English, D., Barnes, B. B., Carlson, P., Yarbro, L. 2018. Comparison of two atmospheric correction approaches applied to MODIS measurements over North American waters. Remote Sensing of Environment. 216, 442-455. DOI: 10.1016/j.rse.2018.07.012

Zhang, M., Hu, C., Cannizzaro, J., Kowalewski, M. G., Janz, S. J. 2018. Diurnal changes of remote sensing reflectance over Chesapeake Bay: Observations from the Airborne Compact Atmospheric Mapper. Estuarine, Coastal and Shelf Science. 200, 181-193. DOI: 10.1016/j.ecss.2017.10.021

Zhang, Y., Hu, C., Liu, Y., Weisberg, R. H., Kourafalou, V. H. 2019. Submesoscale and Mesoscale Eddies in the Florida Straits: Observations from Satellite Ocean Color Measurements. Geophysical Research Letters. 46(22), 13262-13270. DOI: 10.1029/2019GL083999

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

• NASA Ocean Biology & Biogeochemistry (OBB) Project Profile