Use of Landsat Data to Track Historical Water Quality Changes in Florida Keys Marine Environments

Brian B. Barnes; Chuanmin Hu; Kara L. Holekamp; Slawomir Blonski; Bruce A. Spiering; David Palandro; Brian Lapointe

doi:10.1016/j.rse.2013.09.020

Use of Landsat Data to Track Historical Water Quality Changes in Florida Keys Marine Environments

Brian B. Barnes, Chuanmin Hu, Kara L. Holekamp, Slawomir Blonski, Bruce A. Spiering, David Palandro, Brian Lapointe

College of Marine Science

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

Abstract

<a title="Learn more about Satellite Remote Sensing from ScienceDirect's AI-generated Topic Pages"> Satellite remote sensing </a> has shown the advantage of <a title="Learn more about Water Quality Assessment from ScienceDirect's AI-generated Topic Pages"> water quality assessment </a> at synoptic scales in coastal regions, yet modern sensors such as <a title="Learn more about Sea-Viewing Wide Field-of-View Sensor from ScienceDirect's AI-generated Topic Pages"> SeaWiFS </a> or <a title="Learn more about MODIS from ScienceDirect's AI-generated Topic Pages"> MODIS </a> did not start until the late 1990s. For non-interrupted observations, only the <a title="Learn more about Landsat from ScienceDirect's AI-generated Topic Pages"> Landsat </a> series have the potential to detect major water quality events since the 1980s. However, such ability is hindered by the unknown data quality or consistency through time. Here, using the Florida Keys as a case study, we demonstrate an approach to identify historical water quality events through improved atmospheric correction of Landsat data and cross-validation with concurrent MODIS data. After aggregation of the <a title="Learn more about Landsat 5 from ScienceDirect's AI-generated Topic Pages"> Landsat-5 </a> Thematic Mapper (TM) 30-m pixels to 240-m pixels (to increase the signal-to-noise ratio), a MODIS-like atmospheric correction approach using the Landsat shortwave-infrared (SWIR) bands was developed and applied to the entire Landsat-5 TM data series between 1985 and 2010. <a title="Learn more about Remote Sensing from ScienceDirect's AI-generated Topic Pages"> Remote sensing </a> reflectance (R RS ) anomalies from Landsat (2 standard deviations from a pixel-specific monthly climatology) were found to detect MODIS R RS anomalies with over 90% accuracy for all three bands for the same period of 2002–2010. Extending this analysis for the entire Landsat-5 time-series revealed R RS anomaly events in the 1980s and 1990s, some of which are corroborated by known ecosystem changes due in part to changes in local freshwater flow. Indeed, TM R RS anomalies were shown to be useful in detecting shifts in <a title="Learn more about Sea Grasses from ScienceDirect's AI-generated Topic Pages"> seagrass </a> density, turbidity increases, black water events, and <a title="Learn more about Phytoplankton from ScienceDirect's AI-generated Topic Pages"> phytoplankton </a> blooms. These findings have large implications for ongoing and future water quality assessment in the Florida Keys as well as in many other coastal regions.

Original language	American English
Journal	Remote Sensing of Environment
Volume	140
DOIs	https://doi.org/10.1016/j.rse.2013.09.020
State	Published - Jan 1 2014

Keywords

Water quality
Remote sensing
Atmospheric correction
Seagrass

Disciplines

Life Sciences

Access to Document

10.1016/j.rse.2013.09.020License: CC BY

https://doi.org/10.1016/j.rse.2013.09.020

Cite this

@article{1708f65d594f41ca84469a9c4e27f28a,

title = "Use of Landsat Data to Track Historical Water Quality Changes in Florida Keys Marine Environments",

abstract = " Satellite remote sensing has shown the advantage of water quality assessment at synoptic scales in coastal regions, yet modern sensors such as SeaWiFS or MODIS did not start until the late 1990s. For non-interrupted observations, only the Landsat series have the potential to detect major water quality events since the 1980s. However, such ability is hindered by the unknown data quality or consistency through time. Here, using the Florida Keys as a case study, we demonstrate an approach to identify historical water quality events through improved atmospheric correction of Landsat data and cross-validation with concurrent MODIS data. After aggregation of the Landsat-5 Thematic Mapper (TM) 30-m pixels to 240-m pixels (to increase the signal-to-noise ratio), a MODIS-like atmospheric correction approach using the Landsat shortwave-infrared (SWIR) bands was developed and applied to the entire Landsat-5 TM data series between 1985 and 2010. Remote sensing reflectance (R RS ) anomalies from Landsat (2 standard deviations from a pixel-specific monthly climatology) were found to detect MODIS R RS anomalies with over 90% accuracy for all three bands for the same period of 2002–2010. Extending this analysis for the entire Landsat-5 time-series revealed R RS anomaly events in the 1980s and 1990s, some of which are corroborated by known ecosystem changes due in part to changes in local freshwater flow. Indeed, TM R RS anomalies were shown to be useful in detecting shifts in seagrass density, turbidity increases, black water events, and phytoplankton blooms. These findings have large implications for ongoing and future water quality assessment in the Florida Keys as well as in many other coastal regions. ",

keywords = "Water quality, Remote sensing, Atmospheric correction, Seagrass",

author = "Barnes, {Brian B.} and Chuanmin Hu and Holekamp, {Kara L.} and Slawomir Blonski and Spiering, {Bruce A.} and David Palandro and Brian Lapointe",

year = "2014",

month = jan,

day = "1",

doi = "10.1016/j.rse.2013.09.020",

language = "American English",

volume = "140",

journal = "Remote Sensing of Environment",

}

TY - JOUR

T1 - Use of Landsat Data to Track Historical Water Quality Changes in Florida Keys Marine Environments

AU - Barnes, Brian B.

AU - Hu, Chuanmin

AU - Holekamp, Kara L.

AU - Blonski, Slawomir

AU - Spiering, Bruce A.

AU - Palandro, David

AU - Lapointe, Brian

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Satellite remote sensing has shown the advantage of water quality assessment at synoptic scales in coastal regions, yet modern sensors such as SeaWiFS or MODIS did not start until the late 1990s. For non-interrupted observations, only the Landsat series have the potential to detect major water quality events since the 1980s. However, such ability is hindered by the unknown data quality or consistency through time. Here, using the Florida Keys as a case study, we demonstrate an approach to identify historical water quality events through improved atmospheric correction of Landsat data and cross-validation with concurrent MODIS data. After aggregation of the Landsat-5 Thematic Mapper (TM) 30-m pixels to 240-m pixels (to increase the signal-to-noise ratio), a MODIS-like atmospheric correction approach using the Landsat shortwave-infrared (SWIR) bands was developed and applied to the entire Landsat-5 TM data series between 1985 and 2010. Remote sensing reflectance (R RS ) anomalies from Landsat (2 standard deviations from a pixel-specific monthly climatology) were found to detect MODIS R RS anomalies with over 90% accuracy for all three bands for the same period of 2002–2010. Extending this analysis for the entire Landsat-5 time-series revealed R RS anomaly events in the 1980s and 1990s, some of which are corroborated by known ecosystem changes due in part to changes in local freshwater flow. Indeed, TM R RS anomalies were shown to be useful in detecting shifts in seagrass density, turbidity increases, black water events, and phytoplankton blooms. These findings have large implications for ongoing and future water quality assessment in the Florida Keys as well as in many other coastal regions.

AB - Satellite remote sensing has shown the advantage of water quality assessment at synoptic scales in coastal regions, yet modern sensors such as SeaWiFS or MODIS did not start until the late 1990s. For non-interrupted observations, only the Landsat series have the potential to detect major water quality events since the 1980s. However, such ability is hindered by the unknown data quality or consistency through time. Here, using the Florida Keys as a case study, we demonstrate an approach to identify historical water quality events through improved atmospheric correction of Landsat data and cross-validation with concurrent MODIS data. After aggregation of the Landsat-5 Thematic Mapper (TM) 30-m pixels to 240-m pixels (to increase the signal-to-noise ratio), a MODIS-like atmospheric correction approach using the Landsat shortwave-infrared (SWIR) bands was developed and applied to the entire Landsat-5 TM data series between 1985 and 2010. Remote sensing reflectance (R RS ) anomalies from Landsat (2 standard deviations from a pixel-specific monthly climatology) were found to detect MODIS R RS anomalies with over 90% accuracy for all three bands for the same period of 2002–2010. Extending this analysis for the entire Landsat-5 time-series revealed R RS anomaly events in the 1980s and 1990s, some of which are corroborated by known ecosystem changes due in part to changes in local freshwater flow. Indeed, TM R RS anomalies were shown to be useful in detecting shifts in seagrass density, turbidity increases, black water events, and phytoplankton blooms. These findings have large implications for ongoing and future water quality assessment in the Florida Keys as well as in many other coastal regions.

KW - Water quality

KW - Remote sensing

KW - Atmospheric correction

KW - Seagrass

UR - https://digitalcommons.usf.edu/msc_facpub/1930

UR - https://doi.org/10.1016/j.rse.2013.09.020

U2 - 10.1016/j.rse.2013.09.020

DO - 10.1016/j.rse.2013.09.020

M3 - Article

VL - 140

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

ER -

Use of Landsat Data to Track Historical Water Quality Changes in Florida Keys Marine Environments

Abstract

Keywords

Disciplines

Access to Document

Other files and links

Cite this