USGS Home
SOFIA Home

Remote Sensing of Water Turbidity and Sedimentation in Florida Bay and Biscayne Bay

Metadata also available as - [Outline] - [Parseable text] - [XML]

Frequently-anticipated questions:


What does this data set describe?

Title:
Remote Sensing of Water Turbidity and Sedimentation in Florida Bay and Biscayne Bay
Abstract:
A decline in water clarity in Florida Bay has been observed following the seagrass dieoffs starting in the late 1980's. Algal blooms and discolored water have been reported in Florida Bay over the last several years and factors such as resuspension of material and nutrients from the bottom have been suggested as a cause. Monthly monitoring programs by Florida International University (FIU) and Florida Department of Environmental Protection (FDEP) have provided documentation of blooms through chlorophyll measurements. This study used remote sensing to examine resuspension events, the distribution of turbid water and changes in the patterns of water clarity in the Bay.

This project used data collected by the Advanced Very High Resolution Radiometer (AVHRR) on water reflectance for the Florida Bay region over the 12-year period from July 1985 to September 1997, and field data on light attenuation and changes in bottom cover.

Supplemental_Information:
As of March 15, 2005, USGS is no longer processing AVHRR images. For recent imagery, please visit the Institute for Marine Remote Sensing (IMaRS) website at <http://imars.usf.edu/cgi-bin/db?site=gulf&index=1&type=st&mode=daily>.
  1. How should this data set be cited?

    Richard P. Stumpf (no longer with USGS) Megan L. Frayer, 2005, Remote Sensing of Water Turbidity and Sedimentation in Florida Bay and Biscayne Bay.

    Online Links:

  2. What geographic area does the data set cover?

    West_Bounding_Coordinate: -81.25
    East_Bounding_Coordinate: -80.3
    North_Bounding_Coordinate: 25.8
    South_Bounding_Coordinate: 24.75

  3. What does it look like?

  4. Does the data set describe conditions during a particular time period?

    Beginning_Date: Jul-1985
    Ending_Date: Sep-1997
    Currentness_Reference: Publication date

  5. What is the general form of this data set?

    Geospatial_Data_Presentation_Form: project

  6. How does the data set represent geographic features?

    1. How are geographic features stored in the data set?

      Indirect_Spatial_Reference: Florida Bay, Biscayne Bay

    2. What coordinate system is used to represent geographic features?

  7. How does the data set describe geographic features?


Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

  2. Who also contributed to the data set?

  3. To whom should users address questions about the data?

    Rob Wertz
    U.S. Geological Survey
    600 Fourth Street South
    St. Petersburg, FL 33701
    USA

    727 803-8747 ext. 3045 (voice)
    727 803-2030 (FAX)
    rwertz@usgs.gov


Why was the data set created?

The project is conducting comparisons between chlorophyll values collected from the shipboard monitoring programs and pre-cruise reflectances to assess whether there is a link between resuspension events and algal blooms. The next stage in the project is to expand the AVHRR data set backward to before the seagrass dieoffs and to incorporate Landsat data for limited high resolution analysis.


How was the data set created?

  1. From what previous works were the data drawn?

  2. How were the data generated, processed, and modified?

    Date: 2000 (process 1 of 1)
    The datasets were mapped to a Mercator projection with a pixel size of 1.13 km at latitude 25 deg North and residual navigation errors were removed by registering the image within a pixel of the NOAA digital shoreline. The Gulf Stream site showed a slight trend of decreasing reflectance over the 12 years, suggesting a systematic bias to greater offsets with earlier scenes, Monthly average image values were corrected for this bias. In addition cloud-contaminated pixels were flagged using a combination of techniques: thresholds on sea-surface temperatures and channel 2, and spatial variations on channel 2 and a thermal band.

    In the dataset the typical month has 3-9 nominally cloud-free scenes prior to a1994 and 8-16 scenes starting in 1995. Winter 1994 had only four acceptable scenes owing to the extremely late overpass time of NOAA-11 (1600 local standard time). Scenes with solar angles >70 degrees were discarded. Gaps occur in late summer months for 1988-1989. From the available images, monthly average images were determined using the cloud-free pixels. Then the mean winter reflectance from December to March and the mean summer reflectance June to September were determined.

    Field ecologists in the project area document light attenuation using scalar radiometers that measure photo-synthetically-active radiation (PAR, 400-700nm). We used a Licor 4pi PAR sensor for profiles of scalar irradiance at 0.25-m increments from 0.25 m (or 0.5m) depth to the bottom.

    SEAGRASSES Bottom coverage of Thalassia testudium in Rankin Lake, Johnson Key Basin, and Rabbit Key Basin was determined using a modified Braun-Blanquet cover-abundance method (Mueller-Dombois and Ellerberg, 1974). Coverage for 1991 was obtained by randomly sampling 10 locations per basin from a 0.5-nautical (nmi) grid. Coverage for 1994-1996 was obtained by systematic random sampling within 30-35 tessellated hexagons per basin. All data were obtained by sampling four 0.25 meter square quadrats per station (north, east, south and west of the vessel). The density values correspond to the following modified Braun-Blanquet cover-abundance scale: 5=cover of more than 75% of the quadrat; 4=50-75% cover; 3=25-50% cover; 2=5-25% cover, 1=numerous stems with less than 5% cover or scattered with up to 5% cover; 0.5=few stems with small cover; 0.1=solitary, with small cover, and 0=not present. Frequency of occurrence and density information for each species within a particular basin was calculated using the formulas: Frequency = no. of occupied quad/total no. of quads and Density = sum of B-B scale values/total no. of quads. The areal extent of each cover was estimated by kriging the mean station data for each basin using Surfer software package Golden Software. With the nominal 1-km spacing of the samples, each 1-m sq sample site fell in a different pixel. Reflectances for all pixels with sites in a basin were averaged; the combination of kriging and averaging dampens out the scaling problems between the 1-m sq samples with the individual 1.2 km sq pixels.

    Any use of trade, product, or firm names is for descriptive purposes only and does not constitute endorsement by the U.S. Government

    Person who carried out this activity:

    Rob Wertz
    U.S. Geological Survey
    600 Fourth Street South
    St. Petersburg, FL 33701
    USA

    727 803-8747 ext. 3045 (voice)
    727 803-2030 (FAX)
    rwertz@usgs.gov

  3. What similar or related data should the user be aware of?

    Ransibrahmanakul, Varis Stumpf, Richard P., 2002, The Use of AVHRR Satellite Data for Estimating Spatially Varying Critical Wind Stress in Florida Bay: Journal of Coastal Research v. 18, no. 2, p. 267-273, Coastal Education and Research Foundation (CERF), Royal Palm Beach, FL.

    Online Links:

    Other_Citation_Details:
    accessed as of 5/10/2011

    The full article is available via journal subscription or single article purchase. The first page of the article may be viewed on the website below.

    Stumpf, R. P. Frayer, M. L.; Durako, M. J, 1999, Variations in water clarity and bottom albedo in Florida Bay from 1985 to 1997: Estuaries v.22, n. 2B, p. 431-444, Springer New York, New York, New York.

    Online Links:

    Other_Citation_Details: accessed as of 5/10/2011
    Mueller-Dombois, D. Ellerberg, H., 1974, Aims and Methods of Vegetation Ecology: John Wiley and Sons, New York, NY.

    Stumpf, R. P. Pennock, J. R., 1989, Calibration of a general optical equation for remote sensing of suspended sedimetns in a moderately turbid estuary: Journal of Geophysical Research - Oceans v. 94, n. C10, p. 14363-14371, American Geophysical Union, Washington, DC.

    Online Links:

    Other_Citation_Details:
    accessed as of 5/10/2011

    The full article is available via journal subscription or single article purchase. The abstract may be viewed on the website below.

    Stumpf, R. P. Pennock, J. R., 1991, Remote estimation of the diffuse attenuation coefficient in a moderately turbid estuary: Remote Sensing of Environment v. 38, n. 3, p.183-191, Elsevier Science B. V., Amsterdam, The Netherlands.

    Online Links:

    Other_Citation_Details:
    accessed as of 5/10/2011

    The full article is available via journal subscription or single article purchase. The abstract may be viewed on the website below by selecting the volume and issue number.

    Iverson. R. L. Bittaker, H. F., 1986, Seagrass distribution and abundance in eastern Gulf of Mexico coastal waters: Estuarine, Coastal and Shelf Science v. 22, n. 5, p. 577-602, Elsevier B. V., Amsterdam, The Netherlands.

    Online Links:

    Other_Citation_Details:
    accessed as of 5/16/2011

    The full article is available via journal subscription or single article purchase. The abstract may be viewed on the website by selecting the volume and issue number.

    Rao, C. R. N. Chen, J., 1995, Inter-satellite calibrations for the visible and near-infrared channels of the Advanced Very High Resolution Radiometer on the NOAA-7, NOAA-9, and NOAA-11 spacecraft: International Journal of Remote Sensing v. 16, n. 11, p. 1931-1942, Taylor & Francis Gourp, online.

    Online Links:

    Other_Citation_Details:
    accessed as of 5/16/2011

    The full article is available via journal subscription or single article purchase. The abstract may be viewed on the website below.

    Rao, C. R. N. Chen, J., 1996, Post-launch calibraiton of the visible and near-infrared channels of the Advanced Very High Resolution Radiometer on the NOAA-14 spacecraft: International Journal of Remote Sensing v. 17, n. 14, p. 2743-2747, Taylor & Francis Group, online.

    Online Links:

    Other_Citation_Details:
    accessed as of 5/16/2011

    The full article is available via journal subscription or single article purchase. The abstract may be viewed on the website below.

    Stumpf, R. P., 1992, Remote sensing of water quality in coastal waters: Environmental Research Institute of Michigan, Ann arbor, MI.

    Other_Citation_Details:
    in Proceedings of Remote Sensing of Marine and Coastal Environments, Society of Photo-Instrumentation Engineers 1930; N. Wallman, ed.


How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?

  2. How accurate are the geographic locations?

    The datasets were mapped to a Mercator projection with a pixel size of 1.13 km at latitude 25 deg North and residual navigational errors were removed by registering the image within a pixel of the NOAA digital shoreline.

  3. How accurate are the heights or depths?

  4. Where are the gaps in the data? What is missing?

    Nearly 1700 scenes were used from over 2000 scenes processed with about 1000 nominally cloud-free scenes. The analysis used the afternoon satellites, NOAA-9, NOAA-11, and NOAA-14, as these have the best relative calibration and provided more robust datasets in the winter when the sun is lowest.

    The failure of NOAA-13 on launch in 1993 left NOAA-11 as the primary satellite in 1994. The orbit of NOAA-11 had precessed to late afternoon precluding quality imagery in winter 1994 due to low sun angles. NOAA-11 failed in September 1994 and an afternoon satellite was not available till the launch of NOAA-14 in late December.

  5. How consistent are the relationships among the observations, including topology?

    The AVHRR on the National Oceanic and Atmospheric Administration’s polar-orbiting meteorological satellite provides almost daily imagery at 1-km pixel resolution.

    Monthly average image values were corrected month-by-month for a systematic bias for greater offsets with earlier scenes at the Gulf Stream site (Stumpf et al. 1997). In addition to reflectance calculations, cloud-contaminated pixels were flagged using a combination of techniques: thresholds on sea-surface temperature and channel 2, and spatial variations on channel 2 and a thermal band.

    While each AVHRR sensor is calibrated prior to launch, the lack of onboard calibration raised concerns for post-launch calibration and sensor deterioration. The problem was resolved when a relative calibration of the sensors on the afternoon satellites was developed (Rao and Chen, 1995 & 1996)


How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Access_Constraints: none
Use_Constraints: none

  1. Who distributes the data set? (Distributor 1 of 1)

    Rob Wertz
    U.S. Geological Survey
    600 Fourth Street South
    St. Petersburg, FL 33701
    USA

    727 803-8747 ext. 3045 (voice)
    727 803-2030 (FAX)
    rwertz@usgs.gov

  2. What's the catalog number I need to order this data set?

    Florida Bay satellite images

  3. What legal disclaimers am I supposed to read?

    The data have no implied or explicit guarantees.

  4. How can I download or order the data?


Who wrote the metadata?

Dates:
Last modified: 16-May-2011
Metadata author:
Heather Henkel
U.S. Geological Survey
600 Fourth Street South
St. Petersburg, FL 33701
USA

727 803-8747 ext 3028 (voice)
727 803-2030 (FAX)
sofia-metadata@usgs.gov

Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)


This page is <http://sofia.usgs.gov/metadata/sflwww/FBturbidity.faq.html>

U.S. Department of the Interior, U.S. Geological Survey
Comments and suggestions? Contact: Heather Henkel - Webmaster
Generated by mp version 2.8.18 on Mon May 16 10:13:05 2011