Manipulating Satellite Imagery to Analyze Clarity of Lakes

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Manipulating Satellite Imagery to Analyze Clarity
of Lakes

• Matthew J. Kucharski
• Under the direction of Stefan Falke
• And CAPITA
• Washington University in St. Louis
• REU Program
• August 6, 2004

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Purpose of Project

• SeaWiFS satellite imagery data processing
• Understand the processing of SeaWiFS data for
  imaging
• Convert raw data to usable formats for air and
  water quality analysis
• Application of satellite imagery to lake water
  quality monitoring
• Compare SeaWiFS and MODIS surface reflectance
  data to lake clarity monitoring data

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Spectral Characteristics of atmosphere,
vegetation, soil, and water

• Atmosphere reflectance
• Black Carbon, Oxygen, Clouds, etc.
• Vegetation
• High in green (555 nm) and infrared wavelengths
• Soil
• Reflects Red and wavelengths with higher
  frequency

Soil
Vegetation
Water
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Properties of water in the visible light spectrum

• Absorbs most of the light reflected upon it
• 80-90 of the sensor reading over water is from
  the atmosphere
• Water reflects mostly the lower frequency
  electromagnetic wavelengths i.e. blue wavelength

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Passive remote sensing from Satellite

• Use of the suns radiance
• Absorption and scattering of sunlight in the air,
  ground, and water

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CAPITA and Processing SeaWiFS data

• At Center for Air Pollution Impact and Trend
  Analysis (CAPITA), SeaWiFS data is being
  processed for optical thickness of aerosols
  across the United States

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The SeaWiFS data Process

• Georeferencing
• Splicing and Mosaicing
• Rayleigh correction
• Scattering angle correction
• Process Created by Sean Raffuse at Washington
  University

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Other Manipulations for SeaWiFS dataCreate Time
Series Plots and Color Time Series
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Previous attempts at using Satellite for Lake
monitoring

• Environment Remote Sensing Center at University
  of Wisconsin
• Uses Landsat and MODIS imagery to monitor Water
  clarity i.e. Secchi Depth.
• Correlation found between Secchi Depth and Blue
  to Red ratio of the reflectance

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Using SeaWiFS imagery for Lake Monitoring

• Lake monitoring can potentially be monitored
  daily.
• CAPITA has SeaWiFS data since 1999
• Time Series Plots creates a new dimension to lake
  monitoring

Missed Algae Event?
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Lakes in Wisconsin

• Wisconsin has many lakes of various sizes
• Well organized monitoring of smaller lakes
• Wisconsin Department of Natural Resources and the
  Self-Help Lake Monitoring Volunteers
• Monitors many lakes during the summer

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Findings of Wisconsin Lakes
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Problems with SeaWiFS for Lake Monitoring

• One km Resolution creates a wide area to monitor
• Not functional with smaller or narrower lakes
• Temporal Alignment
• Atmosphere remaining after processing
• Haze, clouds ect.

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MODIS vs. SeaWiFS ImageryTable Rock Lake

• SeaWiFS Image 1 km resolution

• MODIS Image 250m resolution

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Table Rock Lake

• Current research project involving Wash U.
• High phosphorus levels
• Creates Eutrophication
• Monitored using Secchi Disk Depth by the Lakes of
  Missouri Volunteer Program

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Problems and Potentialwith MODIS

• MODIS image and Georeferencing
• Less data easily accessible
• Requires processing similar to SeaWiFS
• No temporal dimension

• Experiments by other organizations show a promise
  correlation in Secchi Depth and Satellite imagery
• Daily Global Coverage

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Future Work
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References

• Giammar, Daniel and Angenent, Lars, 2004.
  Evaluation of Chemical and Biological Tracers
  for Source Appointment of phosphorus in Table
  Rock Lake, on the Missouri-Arkansas Border.
  Proposal
• Introduction to Remote Sensing Environment. 2004.
  www.microimage.com. Lincoln MicroImages, Inc.
  http//www.microimages.com/getstart/pdf/introrse.p
  df
• Kaufman, Y. J., Tanre, D., Gordon, H. R.,
  Nakajima, T., Lenoble, J., Frouin, R., Grassl,
  H., Herman, B. M., King, M. D., and Teillet,
  P.M., (1997), Passive remote sensing of
  tropospheric aerosol and atmospheric correction
  for the aerosol effect, J. Geophys. Res.
  10216,815-16,830.
• Li, F., and Husar, R. B., (1999), Pre-processing
  of SeaWiFS satellite data for aerosol retrieval
  Online. Center for Air Pollution Impact and
  Trend Analysis. Available from
  http//capita.wustl.edu/capita/capitareports/CoRe
  trieval/SeaWiFSPreProcessinghtm. Accessed 22
  January 2002.
• Lillesand, Thomas M. Combining Satellite Remote
  Sensing and Volunteer Secchi Disk Measurement
  for Lake Transparency Monitoring. University of
  Wisconsin
• Radiative Transfer Theory, Atmospheric
  Correction, and Ocean Color. University of
  Miami. June 25, 2004 http//www.physics.miami.ed
  u/chris/envr_optics.html
• Raffuse, Sean M. 2003. Estimation of Daily
  Surface Reflectance over the United States from
  the SeaWifS Sensor. Thesis. Washington
  University In St. Louis
• Schultz, Gert A. Ed., Engman, Edwin T., Ed.
  Remote Sensing in Hydrology and Water Management.
  Springer Heidelberg 2000
• Wisconsin Department of Natural Resources.
  Self-Help Lake Monitoring. July 6, 2004
  http//www.dnr.state.wi.us/org/water/fhp/lakes/se
  lfhelp/index.htm

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Acknowledgements

• I would like to acknowledge Dr. Stefan Falke, Dr.
  Rudolf Husar, and Erin Robinson at CAPITA. Also,
  Gene Bulfin with technical support.