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Example: Multispectral Sensors and FLAASH

Example: Multispectral Sensors and FLAASH®

This example demonstrates how to prepare imagery from most multispectral sensors for use in FLAASH. It uses Landsat 8 imagery as a case study, but the general concepts apply to other sensors such as QuickBird, WorldView, IKONOS, and others.

These steps do not use a specific data file for illustration; they are general steps that you can use with your own imagery.

See the following tutorials for related topics:

  • Preprocessing AVIRIS Data (demonstrates the use of hyperspectral data in FLAASH)
  • Using ASTER Data with FLAASH: available in the ENVI Classic Help

Calibrate the Image to Radiance


FLAASH needs a radiance image for input.

  1. Click the Open button in the toolbar.
  2. For Landsat 8, select a *_MTL.txt metadata file. By opening the metadata file, ENVI reads the entire dataset plus the available metadata. If you open the individual GeoTIFF files for each band, ENVI reads them as TIFF files and you will not have access to metadata that is needed for calibration. For other multispectral sensors, see the Radiometric Calibration topic for the correct metadata file to open.
  3. In the search field of the Toolbox, type the word "calibrate."
  4. Double-click on the Radiometric Calibration tool name that appears. You can also find this tool by expanding the Radiometric Correction folder in the Toolbox.
  5. In the File Selection dialog, select the *MTL_Multispectral dataset.
  6. Perform optional spatial and/or spectral subsetting, and click OK.
  7. In the Radiometric Calibration dialog, click the Apply FLAASH Settings button. This will create an output file that has all of the required criteria for importing into FLAASH. ENVI automatically determines the correct Scale Factor to get the data in the units of spectral radiance that FLAASH requires. With Landsat, it multiples the pixel values by 0.1.
  8. Enter an output filename for the calibrated image.
  9. Click OK. The calibration process may take a long time because it is creating a floating-point image, which will have a large file size. Wait for the Radiometric Calibration task to complete in the Process Manager.

Start FLAASH


  1. Type the word "flaash" in the search field of the Toolbox.
  2. Double-click the FLAASH Atmospheric Correction tool name that appears.
  3. In the FLAASH Parameters dialog, click Input Radiance Image and select the radiance file that you just created.
  4. When the Radiance Scale Factors dialog appears, select the option for Use single scale factor for all bands. Leave the Single scale factor value as 1.000, and click OK. ENVI already applied the correct scale factor in the Radiometric Calibration tool, so you do not need to make adjustments here.
  5. In the FLAASH Parameters dialog, click Output Reflectance File and select a folder and filename for the reflectance file that FLAASH will create.
  6. Select an Output Directory for FLAASH Files that will contain various FLAASH processing files.
  7. Provide a Rootname for FLAASH Files. This name will be appended to the processing files that FLAASH creates.

Enter Scene and Sensor Information

  1. ENVI automatically determines the scene center location from the metadata. You do not need to enter the Lat and Lon coordinates.
  2. From the Sensor Type drop-down list, select Multispectral > Landsat-8 OLI. The Sensor Altitude and Pixel Size (m) fields are automatically filled in.
  3. Provide an estimated Ground Elevation (km) value for the center of the scene. You can use a tool such as Google Earth™ to locate the approximate elevation.
  4. Right-click on the original Landsat scene filename in the Layer Manager and select View Metadata.
  5. Click the Time category on the left side of the Metadata Viewer.
  6. Note the Acquisition Time, and enter this information in the Flight Date and Flight Time fields of the FLAASH Parameters dialog.

Enter Water Vapor and Aerosol Information

The proper water and aerosol retrieval settings are less critical for multispectral sensors than they are for imaging spectrometers such as AVIRIS and EO-1 Hyperion. Most multispectral sensors do not have the spectral resolution to perform accurate water and aerosol retrieval. The following steps provide some general recommendations. If you leave the remaining fields at their default values, it would still yield a relatively accurate atmospheric correction, suitable for most image-processing applications. However, the following steps will teach you about these options in greater detail.

  1. The Atmospheric Model setting relates to the average water vapor amount for the scene. Since Landsat 8 does not have any water vapor bands and do you likely do not have water vapor information available for the scene, you can choose one of these model atmospheres. They are just generalizations based on approximate geographic location. Select the option that is closest to the geographic location and season for your scene.
  2. Again, because most multispectral sensors do not have the appropriate bands to retrieve water vapor information, the default value of 1.00 is sufficient for the Water Column Multiplier field.
  3. The Initial Visibility (km) field is set to 40 km, which indicates clear atmospheric conditions throughout the scene. You can lower this value if the scene is in a dense urban area with atmospheric pollution, or if weather reports indicate hazy conditions that day.
  4. The choice of Aerosol Model is not critical if the Initial Visibility (km) value is 40 km. If the visibility is lower, select one of the following options:
    • Urban: A mixture of 80% rural aerosol with 20% soot-like aerosols, appropriate for high-density urban areas.
    • Maritime: Represents the boundary layer over oceans, or continents under a prevailing wind from the ocean. It is composed of two components, one from sea spray and another from rural continental aerosol (that omits the largest particles).
    • Tropospheric: Applies to calm, clear (visibility greater than 40 km) conditions over land and consists of the small-particle component of the rural model.
  5. For Aerosol Retrieval, keep the default selection of 2-Band (K-T).

  6. Click the Multispectral Settings button.
  7. Click the Kaufman-Tranre Aerosol Retrieval tab. Use this section to approximate aerosol conditions over land or water.
  8. Click the Defaults button and choose an option, depending on whether your scene is over land or over water:
    • Over-Land Retrieval standard (660:2100 nm)
    • Over-Water Retrieval (2100:880 nm)
  9. ENVI determines the best bands to use based on your selection, along with a recommended upper channel reflectance value and reflectance ratio. The default values are typically accurate, but you can experiment with different values.

Create the Reflectance Image

  1. Click the Save buttton and enter a filename to save your settings in case you need to change them later.
  2. Click the Apply button.
  3. When processing is complete, open the Data Manager and scroll down to the reflectance file that you just created.
  4. Right-click on the filename and select Load True Color.
  5. One way to validate that that apparent reflectance results are accurate is to view a Spectral Profile. Right-click on the reflectance filename in the Layer Manager and select Profiles > Spectral.
  6. FLAASH scaled the reflectance values by 10,000. The reason for the scaling is to convert the reflectance data to integers, which takes up less disk space than floating-point data. If you prefer to have the reflectance data range from 0 to 1.0, you have two options:
    • Click the Advanced Settings button of the FLAASH Parameters dialog, then change the Output Reflectance Scale Factor to 1. Re-run FLAASH. Processing will take longer because ENVI creates a floating-point reflectance image.
    • Use the Band Math tool to divide the reflectance pixel values by 10,000.

Areas of dark shadow or water may have negative reflectance values. This is just an artifact of pixels that represented low radiance values, and they do not model atmospheric conditions well.



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