Dependence of Satellite Ocean Color Data Products on Viewing Angles: A Comparison Between SeaWiFS, MODIS, and VIIRS

Brian B. Barnes; Chuanmin Hu

doi:10.1016/j.rse.2015.12.048

Dependence of Satellite Ocean Color Data Products on Viewing Angles: A Comparison Between SeaWiFS, MODIS, and VIIRS

Brian B. Barnes, Chuanmin Hu

College of Marine Science

Research output: Contribution to journal › Article › peer-review

Abstract

Despite widespread use of <a title="Learn more about Extraterrestrial Ocean from ScienceDirect's AI-generated Topic Pages"> satellite ocean </a> color data, measured radiance and derived geophysical parameters (e.g., <a title="Learn more about Remote Sensing from ScienceDirect's AI-generated Topic Pages"> remote sensing </a> reflectance or R rs , chlorophyll a concentration, <a title="Learn more about Absorptivity from ScienceDirect's AI-generated Topic Pages"> absorption and scattering coefficients </a> , diffuse attenuation coefficients) may show inconsistencies according to the sensor viewing geometry. In particular, data fluctuations based on sensor <a title="Learn more about Zenith Angle from ScienceDirect's AI-generated Topic Pages"> zenith angle </a> (SZA) can cause variable uncertainties in derived time series, as well as regional or global means. This study analyses single- and merged-sensor datasets from <a title="Learn more about Sea-Viewing Wide Field-of-View Sensor from ScienceDirect's AI-generated Topic Pages"> SeaWiFS </a> , <a title="Learn more about MODIS from ScienceDirect's AI-generated Topic Pages"> MODIS </a> , and <a title="Learn more about VIIRS from ScienceDirect's AI-generated Topic Pages"> VIIRS </a> for the <a title="Learn more about Gulf of Mexico from ScienceDirect's AI-generated Topic Pages"> Gulf of Mexico </a> region, finding pronounced variation within and between satellites as a function of SZA. Such effects are generally restricted to data with SZA above 40°, although large variation exists between satellites and products. The non-tilted MODIS and VIIRS also show residual errors during summer time for SZA < 30° due to imperfect sun glint and <a title="Learn more about Bidirectional Reflectance from ScienceDirect's AI-generated Topic Pages"> bidirectional reflectance </a> distribution function (BRDF) corrections. Furthermore, certain algorithms and products are more resilient to angular dependence in R rs data. Overall, this study provides a framework for interpretation and account of SZA dependence in satellite ocean color data products, towards creation of cross-sensor time series as required for analysis of changes on multi-decadal scales. Finally, these findings can inform design and calibration of future geostationary sensors, for which targets have fixed viewing geometry.

Original language	American English
Journal	Remote Sensing of Environment
Volume	175
DOIs	https://doi.org/10.1016/j.rse.2015.12.048
State	Published - Jan 1 2016

Keywords

Ocean color
Data continuity
Uncertainty
Sensor zenith
Time series

Disciplines

Life Sciences

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10.1016/j.rse.2015.12.048License: CC BY

https://doi.org/10.1016/j.rse.2015.12.048

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title = "Dependence of Satellite Ocean Color Data Products on Viewing Angles: A Comparison Between SeaWiFS, MODIS, and VIIRS",

abstract = " Despite widespread use of satellite ocean color data, measured radiance and derived geophysical parameters (e.g., remote sensing reflectance or R rs , chlorophyll a concentration, absorption and scattering coefficients , diffuse attenuation coefficients) may show inconsistencies according to the sensor viewing geometry. In particular, data fluctuations based on sensor zenith angle (SZA) can cause variable uncertainties in derived time series, as well as regional or global means. This study analyses single- and merged-sensor datasets from SeaWiFS , MODIS , and VIIRS for the Gulf of Mexico region, finding pronounced variation within and between satellites as a function of SZA. Such effects are generally restricted to data with SZA above 40°, although large variation exists between satellites and products. The non-tilted MODIS and VIIRS also show residual errors during summer time for SZA < 30° due to imperfect sun glint and bidirectional reflectance distribution function (BRDF) corrections. Furthermore, certain algorithms and products are more resilient to angular dependence in R rs data. Overall, this study provides a framework for interpretation and account of SZA dependence in satellite ocean color data products, towards creation of cross-sensor time series as required for analysis of changes on multi-decadal scales. Finally, these findings can inform design and calibration of future geostationary sensors, for which targets have fixed viewing geometry. ",

keywords = "Ocean color, Data continuity, Uncertainty, Sensor zenith, Time series",

author = "Barnes, {Brian B.} and Chuanmin Hu",

year = "2016",

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doi = "10.1016/j.rse.2015.12.048",

language = "American English",

volume = "175",

journal = "Remote Sensing of Environment",

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T1 - Dependence of Satellite Ocean Color Data Products on Viewing Angles: A Comparison Between SeaWiFS, MODIS, and VIIRS

AU - Barnes, Brian B.

AU - Hu, Chuanmin

PY - 2016/1/1

Y1 - 2016/1/1

N2 - Despite widespread use of satellite ocean color data, measured radiance and derived geophysical parameters (e.g., remote sensing reflectance or R rs , chlorophyll a concentration, absorption and scattering coefficients , diffuse attenuation coefficients) may show inconsistencies according to the sensor viewing geometry. In particular, data fluctuations based on sensor zenith angle (SZA) can cause variable uncertainties in derived time series, as well as regional or global means. This study analyses single- and merged-sensor datasets from SeaWiFS , MODIS , and VIIRS for the Gulf of Mexico region, finding pronounced variation within and between satellites as a function of SZA. Such effects are generally restricted to data with SZA above 40°, although large variation exists between satellites and products. The non-tilted MODIS and VIIRS also show residual errors during summer time for SZA < 30° due to imperfect sun glint and bidirectional reflectance distribution function (BRDF) corrections. Furthermore, certain algorithms and products are more resilient to angular dependence in R rs data. Overall, this study provides a framework for interpretation and account of SZA dependence in satellite ocean color data products, towards creation of cross-sensor time series as required for analysis of changes on multi-decadal scales. Finally, these findings can inform design and calibration of future geostationary sensors, for which targets have fixed viewing geometry.

AB - Despite widespread use of satellite ocean color data, measured radiance and derived geophysical parameters (e.g., remote sensing reflectance or R rs , chlorophyll a concentration, absorption and scattering coefficients , diffuse attenuation coefficients) may show inconsistencies according to the sensor viewing geometry. In particular, data fluctuations based on sensor zenith angle (SZA) can cause variable uncertainties in derived time series, as well as regional or global means. This study analyses single- and merged-sensor datasets from SeaWiFS , MODIS , and VIIRS for the Gulf of Mexico region, finding pronounced variation within and between satellites as a function of SZA. Such effects are generally restricted to data with SZA above 40°, although large variation exists between satellites and products. The non-tilted MODIS and VIIRS also show residual errors during summer time for SZA < 30° due to imperfect sun glint and bidirectional reflectance distribution function (BRDF) corrections. Furthermore, certain algorithms and products are more resilient to angular dependence in R rs data. Overall, this study provides a framework for interpretation and account of SZA dependence in satellite ocean color data products, towards creation of cross-sensor time series as required for analysis of changes on multi-decadal scales. Finally, these findings can inform design and calibration of future geostationary sensors, for which targets have fixed viewing geometry.

KW - Ocean color

KW - Data continuity

KW - Uncertainty

KW - Sensor zenith

KW - Time series

UR - https://digitalcommons.usf.edu/msc_facpub/1962

UR - https://doi.org/10.1016/j.rse.2015.12.048

U2 - 10.1016/j.rse.2015.12.048

DO - 10.1016/j.rse.2015.12.048

M3 - Article

VL - 175

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

ER -

Dependence of Satellite Ocean Color Data Products on Viewing Angles: A Comparison Between SeaWiFS, MODIS, and VIIRS

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