Details:

Journal Title:
Remote Sensing of Environment
Personal Author:
Cannizzaro, Jennifer P. ; Barnes, Brian B. ; Hu, Chuanmin ; Corcoran, Alina A. ; Hubbard, Katherine A. ; ... More +
Cannizzaro, Jennifer P. ; Barnes, Brian B. ; Hu, Chuanmin ; Corcoran, Alina A. ; Hubbard, Katherine A. ; Muhlbach, Eric ; Sharp, William C. ; Brand, Larry E. ; Kelble, Christopher R. Less -
NOAA Program & Office:
OAR (Oceanic and Atmospheric Research)
Description:
Widespread and persistent Ecosystem Disruptive Algal Blooms dominated by marine picocyanobacteria (Synechococcus) commonly occur in the subtropical lagoonal estuary of Florida Bay (U.S.A). These blooms have been linked to a decline in natural sheet flow over the past century from upstream Everglades National Park. Remote sensing algorithms for monitoring cyanobacteria blooms are highly desired but have been mainly developed for freshwater and coastal systems with minimal bottom reflectance contributions in the past. Examination of in situ optical properties revealed that Synechococcus blooms in Florida Bay exhibit unique spectral absorption and reflectance features that form the basis for algorithm development. Using a large, multi-year match-up dataset (2002–2012; n = 682) consisting of in situ pigment concentrations and Moderate Resolution Imaging Spectroradiometer (MODIS) Rayleigh-corrected reflectance (Rrc(λ)), classification criteria for detecting cyanobacteria blooms with chlorophyll-a concentrations (Chl-a) ~5–40 mg m−3 were determined based on a new approach to combine the MODIS Cyanobacteria Index, CIMODIS, and spectral shape around 488 nm, SS(488). The inclusion of SS(488) was required to prevent false positive classifications in seagrass-rich, non-bloom waters with high bottom reflectance contributions. 75% of cyanobacteria blooms were classified accurately based on this modified CI approach with <1% false positives. A strong correlation observed between cyanobacteria bloom in situ Chl-a and CIMODIS (r2 = 0.80, n = 32) then allowed cyanobacterial chlorophyll-a concentrations (ChlCI) to be estimated. Model simulations and image-based analyses showed that this technique was insensitive to variable aerosol properties and sensor viewing geometry. Application of the approach to the entire MODIS time-series (2000–present) may help identify factors controlling blooms and system responses to ongoing management efforts aimed at restoring flow to pre-drainage conditions. The method may also provide insights for algorithm development for other lagoonal estuaries that experience similar blooms.
Keywords:
[+]
Computers In Earth Sciences Geology Soil Science
Source:
Remote Sensing of Environment, 231, 111227
DOI:
https://doi.org/10.1016/j.rse.2019.111227
ISSN:
0034-4257
Format:
PDF
Publisher:
Elsevier BV
Document Type:
Journal Article
Funding:
Grant no. NA15OAR4320064
Rights Information:
Accepted Manuscript
Compliance:
Library
Main Document Checksum:
[+]
urn:sha256:eb8aae26aebe73da3c0dc907623b1effeb39eea9ff68e35f628fe412255800d8
Download URL:
https://repository.library.noaa.gov/view/noaa/57918/noaa_57918_DS1.pdf
File Type:

Supporting Files

• No Additional Files

More +