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Spectral variability of oil slicks under different observing conditions derived from satellite and airborne optical remote sensing

Center for the Integrated Modeling and Analysis of Gulf Ecosystems II (C-IMAGE II)

DOI:
10.7266/n7-1nhg-ez10
 
UDI:
R4.x267.000:0113
Last Update:
Jan 02 2019 18:41 UTC
 
Dataset Author(s):
Shaojie Sun; Chuanmin Hu
Point of Contact:
Hu, Chuanmin
University of South Florida / College of Marine Science
140 7th Ave South
St. Petersburg, Florida  33701
USA
huc@usf.edu
Funding Source:
RFP-IV
Data Collection Period:
2010-04-24 to 2014-08-23

Identified Submitted Review Available
3 3 3 3

Suggested Citation:

Shaojie Sun; Chuanmin Hu (2018) Spectral variability of oil slicks under different observing conditions derived from satellite and airborne optical remote sensing. Distributed by: Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC), Harte Research Institute, Texas A&M University-Corpus Christi. doi:10.7266/n7-1nhg-ez10

Abstract:

In this dataset, we present the spectral variability of oil slicks under different observing conditions using MODIS (Moderate Resolution Imaging Spectroradiometer), MERIS (Medium Resolution Imaging Spectrometer), MISR (Multi-angle Imaging SpectroRadiometer), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and AVIRIS (Airborne Visible/ Infrared Imaging Spectrometer). Optical remote sensing is commonly used to detect oil in the surface ocean due to the spectral differences between oil and water, allowing to modulate oil–water spatial and spectral contrasts. However, understanding these contrasts is challenging because of variable results from laboratory and field experiments, as well as different observing conditions and spatial/spectral resolutions of remote sensing imagery. A multistep scheme is proposed to classify oil type (emulsion and non-emulsion) and to estimate relative oil thickness for each type based on the known optical properties of oil, with sample results from AVIRIS and MODIS imagery provided in the dataset. This dataset supports the publication: Sun, S., & Hu, C. (2018). The Challenges of Interpreting Oil-Water Spatial and Spectral Contrasts for the Estimation of Oil Thickness: Examples From Satellite and Airborne Measurements of the Deepwater Horizon Oil Spill. IEEE Transactions on Geoscience and Remote Sensing, 1–16. doi:10.1109/tgrs.2018.2876091

Purpose:

The dataset was generated to demonstrate oil slick spectral variability under different observing conditions in multispectral and hyperspectral remote sensing imagery, and to figure out parameters other than oil thickness that contribute to the change of oil slick reflectance in remote sensing imagery in the real marine environment. The information and results derived in this study will contribute to the development of algorithms to estimate oil thickness by using multispectral satellite remote sensing imagery.

Theme Keywords:

Oil spill, Optical remote sensing, Oil thickness, Oil emulsion, hyperspectral, multispectral, MODIS, MERIS, Landsat 7, MISR, AVIRIS, Rayleigh-corrected reflectance (Rrc), sun glint strength (LGN)

File Format:

xlsx, hdr, nc, png, hdf, xml, txt

Filename:

1_2_19_dataset upload.zip (1.99 GB)

Dataset Downloads:

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Spectral variability of oil slicks under different observing conditions derived from satellite and airborne optical remote sensing



Identification Information
Distribution Information
Metadata Maintenance Information

Metadata: 
  File identifier: 
      R4.x267.000-0113-metadata.xml
  Language: 
      eng; USA
  Character set: 
    Character set code: 
      utf8
  Hierarchy level: 
    Scope code: 
      dataset
  Metadata author: 
    Responsible party: 
      Individual name: 
          Carla Fotherby
      Organisation name: 
          University of South Florida
      Position name: 
          Collections Specialist
      Contact info: 
        Contact: 
          Phone: 
            Telephone: 
              Voice: 
                  8139746220
              Facsimile: 
          Address: 
            Address: 
              Delivery point: 
                  4202 E. Fowler Ave.
              City: 
                  Tampa
              Administrative area: 
                  Florida
              Postal code: 
                  33620
              Country: 
                  USA
              Electronic mail address: 
                  cbutel@usf.edu
      Role: 
        Role code: 
          pointOfContact
  Date stamp: 
      2019-01-09T22:13:08+00:00
  Metadata standard name: 
      ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
  Metadata standard version: 
      ISO 19115-2:2009(E)
  Dataset URI: 
      https://data.gulfresearchinitiative.org/metadata/R4.x267.000:0113
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Identification info: Data identification: Citation: Citation: Title: Spectral variability of oil slicks under different observing conditions derived from satellite and airborne optical remote sensing Alternate title: Date: Date: Date: 2018-10-05 Date type: Date type code: creation Abstract: In this dataset, we present the spectral variability of oil slicks under different observing conditions using MODIS (Moderate Resolution Imaging Spectroradiometer), MERIS (Medium Resolution Imaging Spectrometer), MISR (Multi-angle Imaging SpectroRadiometer), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and AVIRIS (Airborne Visible/ Infrared Imaging Spectrometer). Optical remote sensing is commonly used to detect oil in the surface ocean due to the spectral differences between oil and water, allowing to modulate oil–water spatial and spectral contrasts. However, understanding these contrasts is challenging because of variable results from laboratory and field experiments, as well as different observing conditions and spatial/spectral resolutions of remote sensing imagery. A multistep scheme is proposed to classify oil type (emulsion and non-emulsion) and to estimate relative oil thickness for each type based on the known optical properties of oil, with sample results from AVIRIS and MODIS imagery provided in the dataset. This dataset supports the publication: Sun, S., & Hu, C. (2018). The Challenges of Interpreting Oil-Water Spatial and Spectral Contrasts for the Estimation of Oil Thickness: Examples From Satellite and Airborne Measurements of the Deepwater Horizon Oil Spill. IEEE Transactions on Geoscience and Remote Sensing, 1–16. doi:10.1109/tgrs.2018.2876091 Purpose: The dataset was generated to demonstrate oil slick spectral variability under different observing conditions in multispectral and hyperspectral remote sensing imagery, and to figure out parameters other than oil thickness that contribute to the change of oil slick reflectance in remote sensing imagery in the real marine environment. The information and results derived in this study will contribute to the development of algorithms to estimate oil thickness by using multispectral satellite remote sensing imagery. Status: Progress code: completed Point of contact: Responsible party: Individual name: Chuanmin Hu Organisation name: University of South Florida / College of Marine Science Position name: Professor Contact info: Contact: Phone: Telephone: Voice: 7275533987 Facsimile: Address: Address: Delivery point: 140 7th Ave South City: St. Petersburg Administrative area: Florida Postal code: 33701 Country: USA Electronic mail address: huc@usf.edu Role: Role code: pointOfContact Point of contact: Responsible party: Individual name: Shaojie Sun Organisation name: University of South Florida / College of Marine Science Position name: Graduate Student Contact info: Contact: Phone: Telephone: Voice: 8138412976 Facsimile: Address: Address: Delivery point: 140 7th Ave South City: St. Petersburg Administrative area: Florida Postal code: 33701 Country: USA Electronic mail address: suns@mail.usf.edu Role: Role code: principalInvestigator Descriptive keywords: Keywords: Keyword: Oil spill Keyword: Optical remote sensing Keyword: Oil thickness Keyword: Oil emulsion Keyword: hyperspectral Keyword: multispectral Keyword: MODIS Keyword: MERIS Keyword: Landsat 7 Keyword: MISR Keyword: AVIRIS Keyword: Rayleigh-corrected reflectance (Rrc) Keyword: sun glint strength (LGN) Type: Keyword type code: theme Descriptive keywords: Keywords: Keyword: Gulf of Mexico Type: Keyword type code: place Language: eng; USA Topic category: Topic category code: oceans Topic category: Topic category code: environment Topic category: Topic category code: geoscientificInformation Topic category: Topic category code: imageryBaseMapsEarthCover Extent: Extent: Geographic element: Geographic bounding box: West bound longitude: -91 East bound longitude: -84 South bound latitude: 26 North bound latitude: 31 Geographic element: BoundingPolygon: Polygon: Polygon: Outer boundary: Linear ring: gml:posList: 26 -91 31 -91 31 -84 26 -84 26 -91 Temporal element: Temporal extent: Extent: Time period: Description: ground condition Begin date: 2010-04-24 End date: 2014-08-23 Supplemental Information: MODIS: Four Moderate Resolution Imaging Spectroradiometer (MODIS; onboard Aqua and/or Terra) Rayleigh-corrected reflectance (Rrc, units=dimensionless) imagery in HDF format processed with the software SeaDAS (version 7.0) at a 250 m spatial resolution and mapped to a cylindrical equidistant projection [bounding box (North, South, West, East; decimal degrees) = 31, 26, -91, -84] for April 26, 2010 (Aqua), May 17, 2010 (Aqua and Terra) and May 28, 2010 (Terra). HDF files contain the Rrc data at the following wavelengths (nm): 412, 443, 469, 488, 531, 547, 555, 645, 667, 678, 748, 859, 869, 1240, 1640, 2130; the viewing geometry [solar zenith (solz), sensor zenith (senz), solar azimuth (sola), and sensor azimuth (sena)]; and glint coefficient (glint_coef). An RGB true-color image was created for each MODIS image. The Rrc data was extracted at selected locations and saved in excel files (latitude (decimal degrees), longitude (decimal degrees), wavelength (nm), Rrc, and Rrc difference). The Rrc difference is the difference between the selected location (with oil) and a nearby pixel (to represent the water reflectance and a non-oil pixel).
          
MISR: Nine Multi-angle Imaging Spectroradiometer (MISR) Top-of-Atmosphere radiance (TOA) data HDF files from May 17, 2010 in the Mississippi Delta region. The filenames are MISR_AM1_GRP_TERRAIN_LM_Pmmm_Onnnnnn_cc_SITE_MISSDELTA_Fff_vvvv .hdf, where MISR_AM1_GRP_TERRAIN mean Level1B2 geo-rectified radiances, LM means the ellipsoid-projected local mode, Pmmm corresponds to the orbit path number, Onnnnnn is the absolute orbit number, cc is the camera identifier, ff is the file format version and vvvv is the version number (which relates to the reprocessing of a dataset with different software and/or ancillary inputs). The parameters defined to carry a Radiometric Data Quality Indicator (RDQI) associated with each measurement. The files contain geometric parameters which measure the sun and view angles at the reference ellipsoid; and Bidirectional Reflectance Factor (BRF) conversion factor for each band. Each file has 4 spectral bands: blue (446 nm), green (558 nm), red (672 nm) and near-infrared (NIR, 867 nm); and 9 viewing angles: 0, 26.1, 45.6, 60, 70.5, -26.1, -45.6, -60, -70.5 degrees. Each file has a corresponding XML file with metadata. The radiance data were extracted at selected locations (MISR_05_17_2010.xlsx) with emulsion, thin oil, thick oil and water for all angles and spectral bands. Radiance was also extracted at a transect for only the blue and NIR spectral bands and all angles.
          
MERIS: Three Medium Resolution Imaging Spectrometer (MERIS) Rrc data files for April 25, 2010, April 26, 2010, and April 28, 2010 in HDF format processed with the software SeaDAS (version 7.0) at a 250 m spatial resolution and mapped to a cylindrical equidistant projection [bounding box (North, South, West, East; decimal degrees) = 31, 26, -91, -84]. The HDF files contain the Rrc data at the following wavelengths (nm): 413, 443, 490, 510, 560, 620, 665, 681, 709, 754, 762, 779, 865, and 885; the viewing geometry [solar zenith (solz), sensor zenith (senz), solar azimuth (sola), and sensor azimuth (sena)]; and glint coefficient (glint_coef), relative azimuth angle (phi), ozone, wind and pressure. An RGB true-color image was created for each MERIS file. The Rrc data was extracted at selected locations and saved in excel files (latitude (decimal degrees), longitude (decimal degrees), site name, wavelength (nm), Rrc, and Rrc difference).
          
ETM+: One Landsat 7 Enhanced Thematic Mapper Plus (ETM+) Rrc data file in netCDF format processed with the software ACOLITE (V20170718.0) at a 30 m spatial resolution. The netCDF file contains chlorophyll-a derived with the OC3 algorithm (CHL-OC3), diffuse attenuation at 490 nm derived with the QAA algorithm (KD490), quality control flags, Scattering Line Height (SLH), latitude (decimal degrees), longitude (decimal degrees), the Rrc data at the following wavelengths (nm): 479, 561, 661, 835, 1650, and 2209. An RGB true-color image was created for the Landsat file. The Rrc data was extracted at selected locations and saved in excel files (latitude (decimal degrees), longitude (decimal degrees), site name, wavelength (nm), Rrc, and Rrc difference).
          
AVIRIS_Classification_Result: The original AVIRIS file can be accessed openly via https://pubs.usgs.gov/of/2010/1167/downloads/figure16c-geotiff.tif. The reflectance spectra were extracted at selected locations and saved in AVIRIS_05_17_2010.xlsx (latitude (decimal degrees), longitude (decimal degrees), site name, wavelength (nm), Reflectance, and Reflectance difference). The emulsion_relative_thickness and non_emulsion_relative_thickness are the resulted relative thickness of oil emulsion and non-emulsions following the proposed classification scheme. The AVIRIS_scatter_plot.xlsx file contains the comparison of the relative thickness of oil emulsions from the multiband classification scheme with the USGS derived oil emulsion thickness using a hyperspectral algorithm. The AVIRIS_Classification_Result.xlsx includes data of mean and standard deviation spectra of classified pixels, using both classification approaches.
          
MODIS_Classification_Result: This folder includes the results of MODIS relative thickness of oil emulsion following the same classification scheme and an AVIRIS derived emulsion thickness derived by USGS after binning to 250-m spatial resolution. LGN_vs_Rrc_Difference.xlsx: contains id, MODIS_filename, year, month, day, latitude (decimal degrees), longitude (decimal degrees), oil-water Rrc difference (i.e., Rrc difference between oil pixels and nearby oil-free pixels in the MODIS 859 nm band), sun glint strength (LGN) calculated from >300 natural slicks in the Gulf of Mexico using MODIS data. LGN was estimated using Cox and Munk (1954) model. The values represent the mean of the extracted oil slick (a polygon).|AVIRIS and MODIS Classification: The classification scheme is a step-wise model to classify oil type (emulsion status) and classify relative thickness of both oil emulsions and non-emulsions using multiband satellite data; The USGS method using a hyperspectral approach to quantitatively map oil emulsions using hyperspectral AVIRIS data. Please refer to Sun and Hu, 2018 for further details of the classification scheme and its comparison with the USGS approach.||||Cox, C., & Munk, W. (1954). Measurement of the Roughness of the Sea Surface from Photographs of the Sun’s Glitter. Journal of the Optical Society of America, 44(11), 838. doi:10.1364/josa.44.000838
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Distribution info: Distribution: Distributor: Distributor: Distributor contact: Responsible party: Organisation name: Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) Contact info: Contact: Phone: Telephone: Voice: 3618253604 Address: Address: Delivery point: 6300 Ocean Drive City: Corpus Christi Administrative area: TX Postal code: 78412 Country: USA Electronic mail address: griidc@gomri.org Online Resource: Online Resource: Linkage: URL: https://data.gulfresearchinitiative.org Role: Role code: distributor Distributor format: Format: Name: xlsx, hdr, nc, png, hdf, xml, txt Version: inapplicable File decompression technique: zip Distributor transfer options: Digital transfer options: Transfer size: 1994.3009 Online: Online Resource: Linkage: URL: https://data.gulfresearchinitiative.org/data/R4.x267.000:0113 Protocol: https
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Metadata maintenance: Maintenance information: Maintenance and update frequency: unknown Maintenance note: This ISO metadata record was automatically generated from information provided to GRIIDC for dataset: R4.x267.000:0113 on 2019-02-17T13:31:41+00:00
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