Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 523

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Chlorophyll algorithms for ocean color sensors - OC4, OC5 & OC6

Open access
O'Reilly, John E., Werdell, P. Jeremy·2019·Remote Sensing of Environment

Abstract

A high degree of consistency and comparability among chlorophyll algorithms is necessary to meet the goals of merging data from concurrent overlapping ocean color missions for increased coverage of the global ocean and to extend existing time series to encompass data from recently launched missions and those planned for the near future, such as PACE, OLCI, HawkEye, EnMAP and SABIA-MAR. To accomplish these goals, we developed 65 empirical ocean color (OC) chlorophyll algorithms for 25 satellite instruments using the largest available and most globally representative database of coincident in situ chlorophyll a and remote sensing reflectances. Excellent internal consistency was achieved across these OC ‘Version -7’ algorithms, as demonstrated by a median regression slope and coefficient of determination (R 2 ) of 0.985 and 0.859, respectively, among 903 pairwise comparisons of OC-modeled chlorophyll. SeaWiFS and MODIS-Aqua satellite-to- in situ match-up results indicated equivalent, and sometimes superior, performance to current heritage chlorophyll algorithms. During the past forty years of ocean color research the violet band (412 nm) has rarely been used in empirical algorithms to estimate chlorophyll concentrations in oceanic surface water. While the peak in chlorophyll-specific absorption coincides with the 443 nm band present on most ocean color sensors, the magnitude of chlorophyll-specific absorption at 412 nm can reach upwards of ~70% of that at 443 nm. Nearly one third of total chlorophyll-specific absorption between 400 and 700 nm occurs below 443 nm, suggesting that bands below 443 nm, such as the 412 nm band present on most ocean color sensors, may also be useful in detecting chlorophyll under certain conditions and assumptions. The 412 nm band is also the brightest band (that is, with the most dominant magnitude) in remotely sensed reflectances retrieved by heritage passive ocean color instruments when chlorophyll is less than ~0.1 mg m −3 , which encompasses ~24% of the global ocean. To attempt to exploit this additional spectral information, we developed two new families of OC algorithms, the OC5 and OC6 algorithms, which include the 412 nm band in the MBR. By using this brightest band in MBR empirical chlorophyll algorithms, the highest possible dynamic range of MBR may be achieved in these oligotrophic areas. The terms oligotrophic, mesotrophic, and eutrophic get frequent use in the scientific literature to designate trophic status; however, quantitative definitions in terms of chlorophyll levels are arbitrarily defined. We developed a new, reproducible, bio-optically based index for trophic status based on the frequency of the brightest, maximum band in the MBR for the OC6_SEAWIFS algorithm, along with remote sensing reflectances from the entire SeaWiFS mission. This index defines oligotrophic water as chlorophyll less than ~0.1 mg m −3 , eutrophic water as chlorophyll a bove 1.67 mg m −3 and mesotrophic water as chlorophyll between 0.1 and 1.67 mg m −3 . Applying these criteria to the 40-year mean global ocean chlorophyll data set revealed that oligotrophic, mesotrophic, and eutrophic water occupy ~24%, 67%, and 9%, respectively, of the area of the global ocean on average.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.rse.2019.04.021

Cites

48 of 48 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 48 references

Metadata

Authors
O'Reilly, J. E., & Werdell, P. J.
Venue
Remote Sensing of Environment
Publisher
Elsevier BV
Published
2019-08
Volume
229
Pages
32-47
ISSN
0034-4257 (ISSN-L)
OpenAlex
W2943845795
Cited by
523
References
48
FWCI
21.65
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Chlorophyll algorithms for ocean color sensors - OC4, OC5 & OC6. https://app.cochat.ai/papers/10.1016/j.rse.2019.04.021
The paper
O'Reilly, J. E., & Werdell, P. J. (2019). Chlorophyll algorithms for ocean color sensors - OC4, OC5 & OC6. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2019.04.021

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.