Abstract
In a continuing effort to develop suitable methods for the surveillance of harmful algal blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote-sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002-2006; during the boreal Summer-Fall periods - July-December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×104cellsl-1 defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (∼80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (∼20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ∼70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ∼86%). These results demonstrate an excellent detection capability, on average ∼10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs.
| Original language | English |
|---|---|
| Pages (from-to) | 440-448 |
| Number of pages | 9 |
| Journal | Harmful Algae |
| Volume | 9 |
| Issue number | 5 |
| DOIs | |
| State | Published - Jun 1 2010 |
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Keywords
- Algorithm development
- Central West Florida Shelf (Gulf of Mexico)
- Detection
- Florida Red Tide (Karenia brevis)
- Harmful algal bloom (HAB)
- Hybrid Scheme
- Ocean color (MODIS-Aqua)
- Satellite remote sensing
ASJC Scopus subject areas
- Aquatic Science
- Plant Science
Cite this
Satellite remote sensing of harmful algal blooms : A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis). / Carvalho, Gustavo A.; Minnett, Peter J; Fleming, Lora E.; Banzon, Viva F.; Baringer, Warner.
In: Harmful Algae, Vol. 9, No. 5, 01.06.2010, p. 440-448.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Satellite remote sensing of harmful algal blooms
T2 - A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis)
AU - Carvalho, Gustavo A.
AU - Minnett, Peter J
AU - Fleming, Lora E.
AU - Banzon, Viva F.
AU - Baringer, Warner
PY - 2010/6/1
Y1 - 2010/6/1
N2 - In a continuing effort to develop suitable methods for the surveillance of harmful algal blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote-sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002-2006; during the boreal Summer-Fall periods - July-December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×104cellsl-1 defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (∼80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (∼20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ∼70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ∼86%). These results demonstrate an excellent detection capability, on average ∼10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs.
AB - In a continuing effort to develop suitable methods for the surveillance of harmful algal blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote-sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002-2006; during the boreal Summer-Fall periods - July-December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×104cellsl-1 defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (∼80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (∼20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ∼70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ∼86%). These results demonstrate an excellent detection capability, on average ∼10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs.
KW - Algorithm development
KW - Central West Florida Shelf (Gulf of Mexico)
KW - Detection
KW - Florida Red Tide (Karenia brevis)
KW - Harmful algal bloom (HAB)
KW - Hybrid Scheme
KW - Ocean color (MODIS-Aqua)
KW - Satellite remote sensing
UR - http://www.scopus.com/inward/record.url?scp=77955054592&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77955054592&partnerID=8YFLogxK
U2 - 10.1016/j.hal.2010.02.002
DO - 10.1016/j.hal.2010.02.002
M3 - Article
AN - SCOPUS:77955054592
VL - 9
SP - 440
EP - 448
JO - Harmful Algae
JF - Harmful Algae
SN - 1568-9883
IS - 5
ER -