Previous ENVI User's Guide: Basic Tools Next

Preprocessing Utilities

ENVI provides preprocessing utilities for calibration, general purpose tools, and data-specific tools. These utilities are described in the following sections.

Calibration Utilities

Use Calibration Utilities to apply calibration factors to AVHRR, MSS, QuickBird, TM and TIMS data, and to use a variety of atmospheric correction techniques.

AVHRR Calibration

Use the AVHRR calibration utility to calibrate AVHRR data from the NOAA 12, 14, 15, 16 and 17 satellites. Bands 1 and 2 are calibrated to percent reflectance and bands 3, 4, and 5 are calibrated to brightness temperature, in degrees Kelvin. For detailed instructions, see Calibrating AVHRR Data.

Landsat MSS Calibration

Use Landsat MSS calibration to convert Landsat MSS digital numbers to radiance or exoatmospheric reflectance (reflectance above the atmosphere) using published post-launch gains and offsets (see Landsat TM Calibration for more details):

  1. Select Basic Tools  Preprocessing  Calibration Utilities  Landsat MSS.

    2.  

  2. When the MSS Calibration Input File dialog appears, select the input file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  

  3. Click OK. The MSS Calibration Parameters dialog appears.

    4.  

  4. From the Satellite drop-down button, select the satellite type.

    5.  

  5. Enter the data acquisition month, day, year, and sun angle into the appropriate text boxes.

    6.  

  6. Select the output type by clicking the Radiance or Reflectance toggle buttons.

    7.  

  7. Select either File or Memory output.

    8.  

  8. Click OK to start the function.

The MSS Calibration Status window appears with the output filename listed and the percent completed displayed.

Landsat TM Calibration

Use Landsat TM calibration to convert Landsat TM or ETM digital numbers to radiance or exoatmospheric reflectance (reflectance above the atmosphere) using published post-launch gains and offsets (see http://landsat7.usgs.gov/cpf/cpf.php and http://edcftp.cr.usgs.gov/pub/metadata/satellite/landsat7.tar.gz).

The spectral radiance (Ll) is calculated using the following equation:

where QCAL is the calibrated and quantized scaled radiance in units of digital numbers, LMINl is the spectral radiance at QCAL = 0, LMAXl is the spectral radiance at QCAL = QCALMAX, and QCALMAX is the range of the rescaled radiance in digital numbers. LMINl and LMAXl are derived from tables provided in the Landsat Technical Notes (August 1986) with the information provided through the TM Calibration Parameters dialog in ENVI. QCALMAX is 255 for all TM data and 127 for all MSS data except Band 4 (0.8 to 1.1 mm), which is 63 for certain time periods (data acquired before February 1, 1979 for Landsat 1-3 and processed before October 22, 1982). The resulting radiance (Ll) is in the units of milliwatts per square centimeter per steradian per micrometer (mW/(cm2*sr*mm)).

The exoatmospheric reflectance (rp) is calculated using the following equation:

where Ll is the spectral radiance, d is the Earth-Sun distance in astronomical units, ESUNl is the mean solar exoatmospheric irradiance, and qs is the solar zenith angle in degrees. ESUNl is derived from tables provided in the Landsat Technical Notes (August 1986). The resulting reflectance is unitless.

TM band 6, if present, is converted to temperature. If 7 bands are input, the 6th band is assumed to be the thermal infrared band. If only 6 bands are input, then it is assumed that there is no thermal infrared band.

For Landsat 7 GeoTIFF files that do not contain calibration coefficients, you can use Landsat TM calibration to specify the calibration coefficients and other related parameters, or you can extract the parameters from a Web server.

  1. Select one of the following options from the ENVI main menu bar:
    • Basic Tools  Preprocessing  Calibration Utilities  Landsat TM

      •  

    • Basic Tools  Preprocessing  Data-Specific Utilities  Landsat TM  Landsat TM Calibration

      •  

    • Spectral  Preprocessing  Calibration Utilities  Landsat TM

      •  

    • Spectral  Preprocessing  Data-Specific Utilities  Landsat TM  Landsat TM Calibration

     

  2. When the TM Calibration Input File dialog appears, select the input file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  

  3. Click OK. The TM Calibration Parameters dialog appears.
    • For Landsat 7 HDF files, the data acquisition date information, gains and bias factors, and sun elevation and azimuth are automatically read from the header.

      •  

    • For Landsat 7 GeoTIFF files, these parameters can be obtained from the EROS Data Center as CPF files and MetaData files. They may also be acquired through the Get Calibration Parameters from Web button, which accesses the RSI web server for this information. The Earth-Sun distance used in the calibration is based on the data acquisition date and calculated from a table in the Landsat 7 User's Guide dated 5/1/2001.

      •  


      Note
      If the input filename does not follow the Landsat 7 file-naming convention, the data acquisition date information will default to January 1, 1984 and the sun elevation to 90 degrees.

     

  4. Choose from the following options:
    • Enter or change any of the parameters as necessary.

      •  

    • To download the calibration parameters from the RSI Web server, the Get Calibration Parameters from Web.

      •  


      Note
      You must have an active internet connection to use this option. Moreover, you may not be able to access this site through a firewall or proxy server. In this case, your connection will be timed out within 15 seconds.

       

      The information is obtained from the Web server and automatically entered into the corresponding fields.

       

    • If you are using a file that does not follow the Landsat 7 file-naming convention, follow these steps:

      •  

    • When the warning dialog appears, click OK.

      •  

      The TM Web Calibration Parameters dialog appears.

       

    • Enter the original filename, or select the Date/Path/Row/Band button and enter the corresponding information.

      •  

      The date, path, row, and band information is used to derive a filename based on the Landsat 7 naming convention.

       

    • In the TM Web Calibration Parameters dialog, click OK.

     

  5. Select the desired output type using the Radiance and Reflectance toggle buttons.

    6.  

  6. Provide Scale: Min and Scale: Max values if these values are not provided by a header or the Web server.

    7.  

    The minimum scale and maximum scale values are satellite parameters set for each band. These values are used to derive the gains and offsets.

     

  7. Choose either File or Memory output.

    8.  

  8. Click OK to perform the calibration.

The TM Calibration Status window displays the progress of the operation. When complete, the output file is listed in the Available Bands List.

QuickBird Radiance Calibration

DigitalGlobe's QuickBird image data is typically distributed in relative radiance. Use the QuickBird Radiance calibration utility to convert the relative radiance into absolute radiance in units of []. The calibration is performed using the calibration factors in the QuickBird metadata file (the absCalFactor in the .imd file). The units are converted from [] into [] using the following nominal bandpass widths:

Pan band:
398 nm
Multispectral Band 1 (Blue):
 68 nm
Multispectral Band 2 (Green):
 99 nm
Multispectral Band 3 (Red):
 71 nm
Multispectral Band 4 (NIR):
114 nm

The gain factors that were applied can be found in the ENVI Header file of the calibrated image.

To use the QuickBird Radiance calibration utility perform the following steps.

  1. From the ENVI main menu bar, select Basic Tools  Preprocessing  Calibration Utilities  QuickBird Radiance.

    2.  

  2. In the file selection dialog, select the QuickBird image you wish to calibrate and perform any spatial or spectral subsetting. Select only an original unmodified QuickBird image product. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  

    If ENVI is unable to locate the associated QuickBird Metadata file, you will be prompted to select it.

     

    The QuickBird Calibration Parameters dialog appears.

     

  3. To scale the calibrated result into unsigned integers set the Scale Output to Integers toggle button to Yes and enter a scale factor. To output the result in floating point set the toggle button to No.

    4.  

    Scaling the result into integers will produce a file that is half the size (in bytes) as the floating point result, however the precision is typically reduced to three digits.

     


    Note
    The maximum value that an unsigned integer can hold is 65,535.

     

  4. Choose output to File or Memory for the calibrated result.

    5.  

  5. Click OK to start the processing.

Using FLAASH in ENVI

The FLAASH plug-in to ENVI is available for purchase from RSI or your ENVI distributor. Contact your sales representative or RSI ((303) 786-9900, info@rsinc.com) for more information.

If you have an FLAASH module license, see the FLAASH User's Guide for details.

Using ATREM in ENVI

You can operate the popular ATmosphere REMoval (ATREM) program directly from ENVI. ENVI provides an interface to the ATREM program. The executable code is not distributed with ENVI. ATREM was developed and distributed by the Center for the Study of Earth from Space (CSES), Cooperative Institute for the Research in Environmental Sciences (CIRES), University of Colorado, Boulder.


Note
The ATREM executable code is no longer available for distribution.

Use ATREM to calculate scaled surface reflectance values from hyperspectral radiance data using an approximate atmospheric radiative transfer modeling technique. Radiative transfer modeling is used to calculate the atmospheric transmittance of gases and molecular and aerosol scattering. The water vapor amount is derived on a pixel-by-pixel basis using the 0.94 mm and 1.14 mm water vapor bands and a three channel ratioing technique. For more detailed information see the ATmosphere REMoval Program User's Guide.

If you have the ATREM executable, place it in the ENVI \bin directory and ENVI will automatically use it. If it is located in another directory, a parameter can be set that points to the correct location (see Setting ATREM Output Parameters). When ATREM is executed using ENVI, the input information needed is generated and the ATREM process is spawned by ENVI automatically. The output from ATREM is automatically opened in ENVI and it appears in the Available Bands List upon completion.

Selecting Input Files

Note
If you want to use a subset, use Basic Tools  Resize Images before running ATREM.

  1. Select Basic Tools  Preprocessing  Calibration Utilities  ATREM.

    2.  

  2. When the standard ENVI file selection dialog appears, select a file.
Supplying Wavelengths

Wavelengths are required to run ATREM. If your input data does not include wavelengths in the ENVI header, a prompt appears asking you to supply the wavelengths from an ASCII file:

Select the column that contains the wavelengths and the column that contains full width half maximum (FWHM) values, if included.

The wavelengths and FWHM values must be in units of micrometers.

Inputting AVIRIS or HYDICE Data

If your input data is AVIRIS or HYDICE, select the scaled calibrated radiance image. See the ATREM User's Guide for details.

Setting ATREM Input Parameters

Use the ATREM Input Parameters dialog to select sensor types (AVIRIS, HYDICE, or User Defined) and to enter input data parameters.

  1. When the ATREM Input Parameters dialog appears select the data sensor type from the Sensor drop-down button.

    2.  


    Note
    If you select User Defined, select the file that contains the scale factors from the file selection dialog that appears.

    The user defined scale factor file must contain one scale factor for each band that is used to scale the input radiance data to units of microwatts/(cm2*nm*steradian) following the model of:

    scale_factor * DN = 1 microwatt / (cm2 * nm * steradian)

    The user defined scale factor file contains two columns of ASCII data, band number and scale factor for every band in the data file.

     

  2. Enter the altitude of the sensor in kilometers.

    3.  

  3. Enter the spectral resolution of the input data in nanometers.

    4.  


    Note
    If your ENVI header file contains FWHM values, no value is required, the header values are used instead, and this dialog does not appear. The FWHM values must be in units of micrometers.

     

  4. Select the date and enter the time (in GMT) of the data overflight.

    5.  


    Note
    For AVIRIS data, this information is read from the header if possible.

     

  5. Enter the data scene center latitude and longitude. To change the latitude and longitude from degrees, minutes, seconds to decimal degrees, click on the DD<->DMS button.

    6.  


    Note
    Enter negative values to indicate south latitudes and west longitudes.

     


    Note
    For AVIRIS data, this information is read from the header if possible.

     

  6. Enter the channel ratio parameters or select from the default parameters used to derive the column water vapor amounts for every pixel in the data.

    7.  

  7. Enter the starting wavelength value and number of channels to average for the windows and water vapor absorption bands for both or either of the 0.94 mm and 1.14 mm water vapor bands.

    8.  

    The channel ratio parameters are used to derive the column water vapor amounts for every pixel in the data scene. The amount of water vapor is determined by using a three-channel ratio. Several bands in the water absorption feature are averaged and ratioed against two sets of averaged window channels adjacent to the water absorption feature.

     

    One or both of the water vapor absorption bands can be used to derive the amount of column water vapor. If both the 0.94 mm and the 1.14 mm water vapor absorption bands are used, the amount of column water vapor used is the average of the derived amount for each absorption band.

     

    In some cases only one of the water vapor absorption bands should be used. For example, if your site contains a large amount of iron-rich soils and minerals, only the 1.14 mm water vapor band should be used.

    • To use only one water vapor band, enter the same parameters into both the 0.94 and 1.14 text boxes.

      •  

    • For the iron-rich example, enter the same wavelengths that are in the 1.14 text boxes into the 0.94 text boxes.

      •  

    • To use default channel ratio parameters, select from the Apply Defaults drop-down button. For more information, see the ATREM User's Guide.

     

  8. Select which of the seven atmospheric gases should be modeled and removed during the reflectance calculation by clicking in the check box next to the gas name.

    9.  


    Note
    By default, all the gases are selected.

     

  9. Select an aerosol model using the pull-down selections.

    10.  

  10. Enter a visibility for the conditions during the overflight or click the arrow toggle button to enter an aerosol optical depth measured at the time of the overflight.

    11.  

  11. Select a standard atmospheric model from the pull-down selections and enter a vertical column ozone amount in atm-cm units. Enter the average surface elevation of the data scene in kilometers.

    12.  

  12. Set the output parameters as described in the next section.
Setting ATREM Output Parameters

Use the ATREM Output Parameters dialog to change the output filenames, scale factor, output spectral resolution, and execution path string. The output ATREM parameters file contains the defined parameters in the necessary ATREM input format. ENVI automatically executes ATREM using this file as input. The output image file contains the output apparent reflectance data scaled by the output data scale factor into two-byte integers.

  1. In the ATREM Input Parameters dialog, click Edit Output Parameters. The ATREM Output Parameters dialog appears.

    2.  

  2. Select from the following options:
    • To change any of the default output filenames, enter the new filenames. The output ATREM parameters file contains the defined parameters in the necessary ATREM input format. ENVI automatically executes ATREM using this file as input. The output image file contains the output apparent reflectance data scaled by the output data scale factor into two-byte integers. The output water vapor image contains the total column water vapor amount for every pixel in cm * 1000 so it is two-byte integer data. The output transmission file is an ASCII file that contains 60 atmospheric transmittance spectra. For details on the file format, see the ATREM User's Guide.

      •  

    • Change the Output Data Scale Factor if desired. The ATREM output apparent reflectance values, between 0 and 1, are multiplied by the scale factor to make them into two-byte integer data.

      •  

    • If desired, enter an output spectral resolution.

      •  

      If no value is entered for this parameter, the output spectral resolution will be the same as the input. See the ATREM User's Guide for more information.

       

    • Enter the directory path and name of the ATREM executable. ENVI automatically starts the executable.

     

  3. In the Output Parameters dialog, click OK.
Executing ATREM

After setting the ATREM input and output parameters, click OK in the Input Parameters dialog to start the ATREM process.

ENVI generates the needed ATREM input file and spawns the ATREM process. A window appears displaying the line number that ATREM is working on. When the process is completed, ENVI opens the resulting files, and the water vapor image and the apparent reflectance bands are listed in the Available Bands List.

Flat Field Calibration

Use Flat Field calibration to normalize images to an area of known "flat" reflectance. This is particularly effective for reducing hyperspectral data to relative reflectance. The method requires that you select a Region Of Interest (ROI) prior to execution. The average spectrum from the ROI is used as the reference spectrum, which is then divided into the spectrum at each pixel of the image.

  1. Define an ROI over a spectrally flat area (see Drawing ROIs).

    2.  

  2. Select Basic Tools  Preprocessing  Calibration Utilities  Flat Field.

    3.  

  3. When the Flat Field Calibration Input File dialog appears, select the input file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    4.  

  4. Click OK.

    5.  

  5. When the Flat Field Calibration Parameters dialog appears, select the average spectrum to use for the flat field calibration by clicking on the desired ROI name in the column labeled Select Calibration from Regions. The selected ROI name appears at the bottom of the window in the text box labeled Selected Item.

    6.  

  6. Choose File or Memory output.

    7.  

  7. Click OK to start the calibration.

Log Residuals

The new Log Residuals calibration tool is designed to remove solar irradiance, atmospheric transmittance, instrument gain, topographic effects, and albedo effects from radiance data. This transform creates a pseudo reflectance image that is useful for analyzing mineral-related absorption features. Log residuals calibration is similar to IARR calibration in that both tools use only in-scene statistics to produce a result.

The logarithmic residuals of a dataset are defined as the input spectrum divided by the spectral geometric mean, then divided by the spatial geometric mean. The geometric mean is used because the transmittance and other effects are considered multiplicative; it is calculated using logarithms of the data values. The spectral mean is the mean of all bands for each pixel and removes topographic effects. The spatial mean is the mean of all pixels for each band and accounts for the solar irradiance, atmospheric transmittance, and instrument gain.

Figure 5-10 shows a comparison of input and output spectra.

Figure 5-10: Comparison of Input Spectra from Original Image (left) and Output Spectra from Log Residual Calibrated Image (right)

Figure 5-10: Comparison of Input Spectra from Original Image (left) and Output Spectra from Log Residual Calibrated Image (right)

To apply log residuals calibration to an image:

  1. From the ENVI main menu bar, select one of the following:
    • Basic Tools  Preprocessing  Calibration Utilities  Log Residuals

      •  

    • Spectral  Preprocessing  Calibration Utilities  Log Residuals

     

  2. In the Log Residuals Calibration Input File dialog:

    3.  

  3. In the Log Residuals Calibration Parameters dialog, either:
    • Select to output to a File and type a filename.

      •  

    • Select to output to Memory.

      •  

    • When the output selection is made, click OK.

A status window appears while the calibration is performed. The calibrated data are added to the Available Bands List when the calibration is complete.

IAR Reflectance Calibration

Use IAR Reflectance calibration (Internal Average Relative Reflectance) to normalize images to a scene average spectrum. This is particularly effective for reducing hyperspectral data to relative reflectance in an area where no ground measurements exist and little is known about the scene. It works best for arid areas with no vegetation. An average spectrum is calculated from the entire scene and is used as the reference spectrum, which is then divided into the spectrum at each pixel of the image.

  1. Select Basic Tools  Preprocessing  Calibration Utilities  IAR Reflectance.

    2.  

  2. When the Calibration Input File dialog appears, select the input file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  

  3. Click OK.

    4.  

  4. When the IARR Calibration Parameters dialog appears, select output to File or Memory.

    5.  

  5. Click OK.

If a statistics file does not exist, a processing status window appears while the statistics are calculated and another status window appears while the calibration is performed. The calibrated data are added to the Available Bands List when the calibration is complete.

Empirical Line Calibration

Use Empirical Line calibration to force spectral data to match selected field reflectance spectra. A linear regression is used for each band to equate DN and reflectance. This is equivalent to removing the solar irradiance and the atmospheric path radiance. The following equation shows how the empirical line gain and offset values are calculated.

Reflectance (field spectrum) = gain x radiance (input data) + offset

ENVI's empirical line calibration requires at least one field, laboratory, or other reference spectrum; these can come from spectral profiles or plots, spectral libraries, ROIs, statistics or from ASCII files. Input spectra will automatically be resampled to match the selected data wavelengths. If more than one spectrum is used, then the regression for each band will be calculated by fitting the regression line through all of the spectra. If only one spectrum is used, then the regression line will be assumed to pass through the origin (zero reflectance equals zero DN). The calibration can also be performed on a data set using existing factors.

Computing Factors and Calibrating

Typically, you should choose a dark and a bright region in the image for use in the empirical line calibration (providing that reference spectra are available for these regions). This provides a more accurate linear regression. Using as many paired data/field spectra as you can will also improve the calibration. At least one spectral pair is necessary.


Note
To use spectra from ROIs, define the ROIs prior to running this function.

  1. Select Basic Tools  Preprocessing  Calibration Utilities  Empirical Line  Compute Factors and Calibrate.

    2.  

  2. When the Empirical Line Input File dialog appears, select the input file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  

  3. Click OK. The Empirical Line Spectra dialog appears.

    4.  

  4. Collect image spectra and reference spectra, and pair spectra using the procedures described in the following sections.
Collecting Data (Image) Spectra

Use the Data Spectra Collection dialog to collect the image spectra (un-calibrated spectra), which can come from a plot or profile, a spectral library, ROI, or ASCII spectrum. Use the Import menu and other interactive options to import and collect spectra.

  1. In the Empirical Line Spectra dialog, click Data Spectra: Import Spectra.

    2.  

  2. Collect spectra using the Import menu as described in Importing Endmember Spectra or using the black draw widget at the top of the dialog as described in Dragging-and-Dropping Spectra.

    3.  

  3. After the data spectra are selected, click Apply. The spectra names are entered into the Empirical Line Spectra dialog.

    4.  

  4. Click Cancel to close the Data Spectra Collection dialog.
Collecting Field Spectra

After importing Data (image) spectra into the Empirical Line Spectra dialog, import the corresponding Field (reference) spectra.

  1. In the Empirical Line Spectra dialog, click on the Field Spectra Import Spectra button.

    2.  

  2. Collect spectra using the Import menu as described in Importing Endmember Spectra or using the black draw widget at the top of the dialog as described in Dragging-and-Dropping Spectra.

    3.  

  3. Click Apply to enter the spectra names.

    4.  

  4. Click Cancel to close the Field Spectra Collection dialog.
Pairing Spectra

After importing Data and Field (reference) spectra into the Empirical Line Spectra dialog, use the following procedure to pair the Data and Field (reference) spectra for use in the regression.

  1. In the Empirical Line Spectra dialog, click on the data spectrum name in the top list to select it.

    2.  

  2. In the bottom list, click on the corresponding field spectrum name.

    3.  

  3. Click Enter Pair to associate the two spectra. The paired spectra are listed in the Selected Pairs text box.

    4.  

  4. Repeat the selection process for as many data and field spectra pairs as desired.

    5.  

  5. Click OK.

The Empirical Line Calibration Parameters dialog appears.

Completing the Calibration
  1. After collecting and pairing spectra, choose File or Memory output in the Empirical Line Calibration Parameters dialog.

    2.  


    Note
    To save the correction coefficients in an ASCII file, enter a second filename in the Output Calibration Filename text box.

    The default extension for correction coefficients files is .cff.

     

  2. Click OK to start the calibration.

A processing status window appears while the calibration is performed. When the calibration is completed, the calibration factors are plotted in a standard ENVI plot window and the calibrated image data are added to the Available Bands List.

Calibrating Using Existing Factors

Use Calibrate Using Existing Factors to run Empirical Line Calibration using output correction factors that were saved during another calibration session.

  1. Select Basic Tools  Preprocessing  Calibration Utilities  Empirical Line  Calibrate Using Existing Factors.

    2.  

  2. Select the input file and any spatial and spectral subsets. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  

  3. Click OK.

    4.  

  4. When the Enter Calibration Factors Filename dialog appears, choose a calibration factors file (.cff) created during a previous Empirical Line Calibration session.

    5.  

  5. Click OK.

    6.  

  6. When the Empirical Line Calibration Parameters dialog appears, choose File or Memory output.

    7.  

  7. Click OK to begin the calibration.

Thermal Atmospheric Correction

Use Thermal Atm Correction to approximate and remove the atmospheric contributions to the thermal infrared data. For best results, perform this correction before converting your data to emissivity. The atmospheric correction algorithm used in ENVI is similar to the In-Scene Atmospheric Compensation algorithm, ISAC. For more detailed instructions, see Thermal IR Utilities.

TIMS Radiance Calibration

Use TIMS Radiance to calibrate raw data from the NASA Thermal Infrared Multispectral Scanner (TIMS) to radiance in units of W/m2/mm/sr. For detailed instructions, see TIMS Utilities.

Calculating Emissivity

Use Calculate Emissivity to use one of three techniques in ENVI to separate the emissivity and temperature information in radiance data measured with thermal infrared sensors. Both the Reference Channel and Emissivity Normalization techniques assume a fixed emissivity value and produce emissivity and temperature outputs. The Alpha Residuals technique does not provide temperature information.

Reference Channel Emissivity Calculation

Use Reference Channel to calculate emissivity and temperature values from thermal infrared radiance data. For detailed instructions, see Using Reference Channel Emissivity.

Emissivity Normalization

Use Emissivity Normalization to calculate emissivity and temperature values from thermal infrared radiance data. For detailed instructions, see Using Emissivity Normalization.

Alpha Residuals

Use Alpha Residuals to produce alpha residual spectra that approximate the shape of emissivity spectra from thermal infrared radiance data. For detailed instructions, see Using Alpha Residuals.

General Purpose Utilities

Use General Purpose Utilities to replace bad lines with averages, perform dark subtractions, and to destripe data.

Replacing Bad Lines

Use Replace Bad Lines to replace bad data lines in image data. You must identify the position of the lines to replace before running the function by using the ENVI cursor position function (see Viewing Cursor Location and Value).


Note
To interactively fix bad lines, see Using the Spatial Pixel Editor.

  1. Select Basic Tools  Preprocessing  General Purpose Utilities  Replace Bad Lines. The Bad Lines Input File dialog appears.

    2.  

  2. Select an input file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  

  3. Click OK. The Bad Lines Parameters dialog appears.

    4.  

  4. In the Enter Bad Line text box, specify which bad lines to replace and press the Return or Enter key.

    5.  

  5. The line appears in the Selected Lines list.
    • To remove that line from the list, click on the line.

      •  

    • To save the line coordinates to a file, click Save.

      •  

    • To restore the coordinates from a previously saved file, click Restore.

      •  

    • To clear the list of lines to replace, click Clear.

     

  6. In the Half Width to Average text box, enter the number of adjacent lines to use as an average for calculation of the replacement line.

    7.  


    Note
    The value is symmetrical around the line to replace. For example, the value 2 means that two lines on either side of the selected line will be averaged to calculate the replacement.

     

  7. Click OK.

    8.  

  8. When the Bad Lines Output dialog appears, select output to File or Memory.

    9.  

  9. Click OK.

Using Dark Subtraction

Use Dark Subtract to apply atmospheric scattering corrections to the image data. The digital number to subtract from each band can be either the band minimum, an average based upon a user defined region of interest, or a specific value.

  1. Select Basic Tools  Preprocessing  General Purpose Utilities  Dark Subtract.

    2.  

  2. When the Dark Subtract Input File dialog appears, select an input file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  

  3. Click OK. The Dark Subtraction Values dialog appears.

    4.  

  4. Select a Subtraction method as described in the following sections.

    5.  

  5. In the Dark Subtraction Values dialog, click OK.

    6.  

  6. When the Dark Subtract Parameters dialog appears, select output to File or Memory.

    7.  

  7. Click OK to start the operation.
Selecting Band Minimum Subtraction

To automatically use the minimum DN value of each spectral band for the dark subtraction:

  1. In the Dark Subtraction Values dialog, select the Band Minimum toggle button.

    2.  

  2. Click OK.
Selecting Region of Interest Subtraction

To use the average of an ROI in each spectral band as the value for dark subtraction (ROIs must first be defined - see Defining Regions of Interest):

  1. In the Dark Subtraction Values dialog, select the Region of Interest toggle button.

    2.  

  2. From the list of available regions, select an ROI and click OK.
Selecting User Value Subtraction

To enter a user-defined value to subtract from each band:

  1. In the Dark Subtraction Values dialog, select the User Value toggle button. A list of the bands and a default value of 0.0000 appear under the Current Subtraction Values label.

    2.  

  2. Click on one of the band names.

    3.  

  3. In the Edit Selected Item text box, enter the desired subtraction value. Press the Return or Enter key.

    4.  

  4. Edit the other band values as desired.

    5.  

  5. Click OK.

Applying Gain and Offset

Use Apply Gain and Offset to apply a simple gain and offset correction to a set of bands. ENVI multiplies the selected bands by an input gain value and adds an offset value that you define.

  1. Select Basic Tools  Preprocessing  General Purpose Utilities  Apply Gain and Offset.

    2.  

  2. Select an input file and any spatial and/or spectral subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset. The Gain and Offset Values dialog appears.

    3.  

  3. In the Gain Values list, click on a band name.

    4.  

  4. In the Edit Selected Item text box, edit the gain value of the item.

    5.  

  5. In the Offset Values list, click on a band name.

    6.  

  6. In the Edit Selected Item text box, edit the offset value of the item.

    7.  

  7. Repeat this selection and assignment of values for each band to process.
    • To reset all of the bands to their original values, click Reset.

      •  

    • To return to the main menu, click Cancel.

     

  8. Click on the Output Data Type menu and select a data type for the output.

    9.  

  9. Select output to File or Memory.

    10.  

  10. Click OK.

A status window displays the status of the operation. The resulting bands are listed in the Available Bands List.

Destriping Data

Use Destripe data to remove periodic scan line striping in image data. This type of striping is often seen in Landsat MSS data (every 6th line) and less commonly, in Landsat TM data (every 16th line). When destriping the data, ENVI calculates the mean of every nth line and normalizes each line to its respective mean. In order for destriping to function properly, the data must be in the acquired format (horizontal strips) and cannot be rotated or georeferenced.

  1. Select Basic Tools  Preprocessing  General Purpose Utilities  Destripe.

    2.  

  2. When the Destriping Data Input File appears, select the input file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  

  3. Click OK.

    4.  

  4. When the Destriping Parameters dialog appears, enter the number of detectors in the box labeled Number of Detectors. The number of detectors is the periodicity of the striping (e.g., for Landsat MSS, the value would be 6).

    5.  


    Note
    If the file type has been set in the header, the default is set automatically.

     

  5. Select either File or Memory output.

    6.  


    Note
    To return to the main menu at any time, click Cancel.

     

  6. Click OK to start the operation.

Applying Cross-Track Illumination Corrections

Use Cross-Track Illumination Correction to remove variation in the cross-track illumination of an image. Cross track illumination variations may be due to vignetting effects, instrument scanning, or other non-uniform illumination effects. Along-track mean values are calculated and you can plot them to show the mean variation in the cross-track direction. A polynomial function, with the order defined by you, is fit to the means and used to remove the variation.

  1. Select Basic Tools  Preprocessing  General Purpose Utilities  Cross-Track Illumination Correction.

    2.  

  2. When the Cross Track Illumination Input File dialog appears, select the input file and perform any spatial or spectral subsetting or masking. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset. For masking details, see Selecting a Mask. The Cross Track Illumination Correction Parameters dialog appears.

    3.  

  3. Select the cross track direction by clicking in the check box next to either Samples or Lines.

    4.  

  4. Select either an Additive or Multiplicative correction method. The Additive method will subtract the fitted polynomial from the data and the Multiplicative method will divide the data by the fitted polynomial.

    5.  

  5. Enter the desired polynomial order and click Plot Polynomial. A plot of the mean data values display in red with the selected polynomial fit overlaid in white. It is best to use a low order polynomial so as not to remove the local variation in the data.

    6.  


    Note
    You can change the polynomial order and plot it again.

     

  6. Select output to Memory or File.

    7.  

  7. Click OK to start the processing.

    8.  


    Note
    The Cross-Track Illumination Correction plot pull-down menus will not be active until you close the Cross Track Illumination Correction Parameters dialog.

Converting Complex Data

Use Convert Complex Data to output selected images calculated from complex data. Image types included are: Real (real portion of number), Imaginary (imaginary portion), Power (log10 of magnitude), Magnitude (square root of sum of the squares of the real and imaginary), and Phase (arc tangent of imaginary divided by real).

  1. Select Basic Tools  Preprocessing  General Purpose Utilities  Convert Complex Data.

    2.  

  2. Select an input data file and click OK.

    3.  

  3. When the Convert Complex Parameters dialog appears, select the output band functions by clicking in the check boxes next to the function names.

    4.  

  4. Select File or Memory output.

    5.  

  5. Click OK.

The calculated images appear in the Available Bands List.

Converting VAX to IEEE Data

Use the VAX to IEEE Converter to convert VAX floating point images to IEEE standard floating point. Most computers support the IEEE standard representation of floating point numbers, but DEC VAX computers still use their own internal floating point representation and some image data still are distributed in this format.

  1. Select Basic Tools  Preprocessing  General Purpose Utilities  Convert VAX to IEEE.

    2.  

  2. When the VAX Floating Point Input File dialog appears, choose the file to converted from the list of available files.

    3.  

  3. Click OK.

    4.  

  4. When the VAX to IEEE Parameters dialog appears, enter the VAX header size (bytes).

    5.  

  5. Select one of the following options:
    • To copy the header information into the output file as an embedded ENVI header, click Yes next to Copy Header.

      •  

    • To copy only the data, click No.

     

  6. Enter an output filename.

    7.  

  7. Click OK to convert the file.

Data-Specific Utilities

Use Data-Specific Utilities to apply data-specific functions that work specifically on your data type.

Displaying HDF Global Attributes

Use View HDF Global Attributes to create a text report of any global attribute values that are present in an HDF scientific data (SD) file.

  1. Select Basic Tools  Preprocessing  Data-Specific Utilities  View HDF Global Attributes.

    2.  

  2. When the file selection dialog appears, select the desired HDF SD file.

Any global attributes contained in the HDF file appear on-screen in a text report.

Saving Reports to ASCII Files
  1. In the Report window, select File  Save Text to ASCII.

    2.  

  2. Enter or choose an output filename and click OK.

    3.  


    Note
    To exit the report without saving the information to a file, select File  Cancel.

ASTER Utilities

Use ASTER Utilities to extract and apply calibration information from HDF attributes, compute sea surface temperatures, use information in the data for georeferencing, and to orthorectify data.

Building ASTER Geometry Files

Use ASTER Build Geometry File to calculate the geometry values for each pixel. You may select which values to calculate: latitude, longitude, solar zenith, and/or sensor zenith angles.

For detailed instructions, see Building ASTER Geometry Files.

Georeferencing ASTER Data

The ASTER data, calibration results, and sea surface temperature image can be georeferenced using information from the ASTER data themselves. Each line of data has 51 latitude and longitude values that can be used in the georeferencing.

For detailed instructions, see Georeferencing ASTER Data.

Orthorectifying ASTER Data

Use Orthorectify ASTER or Orthorectify ASTER with Ground Control to orthorectify ASTER data. For details, see Orthorectification Using RPCs.

AVHRR Utilities

Use AVHRR Utilities to read and display information from the AVHRR header, calibrate AVHRR data to percent reflectance and brightness temperature, compute sea surface temperatures, and to use information in the data for georeferencing. The AVHRR utilities support NOAA-12 through 17.

For details, see the following references:

Di, L. and D. C. Rundquist, 1994. A one-step algorithm for correction and calibration of AVHRR Level 1b data, Photogrammetric Engineering & Remote Sensing, Vol. 60, No. 2, pp. 165-171.


Note
The calibration and sea surface temperatures should be calculated before georeferencing.

Displaying AVHRR Header Information

To display the header information from the AVHRR header:

  1. Select Basic Tools  Preprocessing  Data-Specific Utilities  AVHRR  Display Header Information.

    2.  

  2. Select the desired input AVHRR data file and click OK.

The AVHRR File Information dialog appears. The header information displays.

Saving Header Info to ASCII Files

To save the header information to an ASCII file, select from the AVHRR File Information dialog, File  Save Text to ASCII, and enter an output filename.

Calibrating AVHRR Data

Use Calibrate Data to calibrate AVHRR data from the NOAA 12 though 17 satellites. Bands 1 and 2 are calibrated to percent reflectance and bands 3, 4, and 5 are calibrated to brightness temperature, in degrees Kelvin.

  1. Select Basic Tools  Preprocessing  Data-Specific Utilities  AVHRR  Calibrate Data.

    2.  

  2. Select the desired input AVHRR data file and perform any spatial and spectral subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  


    Note
    AVHRR data that has been scaled to 8-bit depth cannot be used to compute SSTs because NOAA does not modify the calibration coefficients stored in the file's 1b header.

     

  3. When the AVHRR Calibrate Parameters dialog appears, select the satellite number from the Satellite drop-down button.

    4.  

  4. Select either File or Memory output.

    5.  

  5. Click OK to start the calibration.

Output bands 1 and 2 are in % reflectance, and output bands 3, 4, and 5 are in brightness temperature, in degrees Kelvin.

Building AVHRR Geometry Files

Use AVHRR Build Geometry File to calculate the geometry values for each pixel. You may select which values to calculate: latitude, longitude, solar zenith, and/or sensor zenith angles.

For detailed instructions, see Building AVHRR Geometry Files.

Georeferencing AVHRR Data

The AVHRR data, calibration results, and sea surface temperature image can be georeferenced using information from the AVHRR data themselves. Each line of data has 51 latitude and longitude values that can be used in the georeferencing.

For detailed instructions, see Georeferencing AVHRR Data.

Computing Sea Surface Temperature

A sea surface temperature image, in degrees Celsius, is computed using AVHRR bands 3, 4, and 5. Currently, ENVI does not use a cloud or land mask in the sea surface temperature calculation. Four algorithms are available, one for daytime data and three for nighttime data: Day MCSST Split; Night MCSST Split; Night MCSST Dual; and Night MCSST Triple. These algorithms differ in which bands are used to correct for the atmosphere, Split-window uses bands 4 and 5, Dual-window uses bands 3 and 4, and Triple-window uses bands 3, 4 and 5. The coefficients used for the NOAA 12 and 14 satellites are based on March 1995 global drifting buoy and tropical Pacific fixed buoy matchups. The coefficients used for the NOAA 15, 16, and 17 satellites are based on values provided in the NOAA KLM User's Guide (see Appendix D in http://www2.ncdc.noaa.gov/docs/klm for more information).

  1. Select Basic Tools  Preprocessing  Data-Specific Utilities  AVHRR  Compute Sea Surface Temperature.

    2.  

  2. Select the desired input AVHRR data file and perform any spatial subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.The AVHRR Sea Surface Temperature Parameters dialog appears.

    3.  


    Note
    The input file must contain AVHRR bands 3, 4, and 5.

     

  3. From the Satellite drop-down button, select the satellite name.

    4.  

  4. From the SST Algorithm pull-down menu, select the desired algorithm.

    5.  

  5. Select either File or Memory output.

    6.  

  6. Click OK.

The output sea surface temperature image is in degrees Celsius.

ENVISAT Utilities

Use Georeference AATSR, Georeference ASAR, or Georeference MERIS to georeference your ENVISAT AATSR, ASAR, or MERIS data with the geolocation information included in the ENVISAT file. ENVISAT imagery contains geolocation tie points that correspond to specific pixels in the image. These tie points can be used to automatically georeference the ENVISAT data without building a geometry file. For detailed instructions, see Georeference ENVISAT.

IKONOS Utilities

Use Orthorectify IKONOS or Orthorectify IKONOS with Ground Control to orthorectify IKONOS data. For details, see Orthorectification Using RPCs.

Landsat MSS Utilities

Use Landsat MSS utilities to correct aspect ratios and to deskew Landsat Multispectral Scanner (MSS) data.

Deskewing Data

Landsat MSS image data processed prior to 1978 typically contains systematic distortions caused by earth rotation and scan skew. Use MSS Deskewing to remove the skew by offsetting groups of scan lines based on the relationship between the orbital characteristics and latitude-dependent earth rotation characteristics.

  1. Select Basic Tools  Preprocessing  Data-Specific Utilities  Landsat MSS  Deskew.

    2.  

  2. When the Deskewing Input File dialog appears, select an input file and perform any spatial and spectral subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  

  3. Click OK.

    4.  

  4. When the Deskewing Parameters dialog appears, enter the latitude of the MSS scene center into the text boxes labeled Latitude Degrees, Latitude Minutes, and Latitude Seconds.

    5.  

  5. Select either File or Memory output.

    6.  


    Note
    To close the function at any time, click Cancel.

     

  6. Click OK to start the function.

A status window appears with the output filename listed and the percent completed displayed.

Correcting Aspect Ratio

Use MSS Aspect Ratio Correction to adjust the aspect ratio by applying nearest neighbor resampling to a regular grid. Landsat MSS image data typically contains geometric distortions caused by oversampling in the scan direction. The actual pixel sizes are approximately 79 x 79 meters, but the instrument samples at 57 meter intervals in the scan direction. Because of this oversampling, an adjustment of the aspect ratio by the factor 57/79=0.72 is required.

  1. Select Basic Tools  Preprocessing  Data-Specific Utilities  Landsat MSS  Aspect.

    2.  

  2. When the Aspect Correction Input File dialog appears, select the input file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset.

    3.  

  3. Click OK.

    4.  

  4. When the Aspect Correction Parameters dialog appears, select output to File or Memory.

    5.  

  5. Click OK to start the function.

No other interaction is required. The status window appears with the output filename listed and the percent completed displayed.

Landsat MSS Data Calibration

Use Landsat MSS Calibration to convert Landsat MSS digital numbers to radiance or exoatmospheric reflectance (reflectance above the atmosphere) using published post-launch gains and offsets. For detailed instructions, see Landsat MSS Calibration.

Landsat TM Utilities

Use Landsat TM Calibration to convert Landsat TM digital numbers to radiance or exoatmospheric reflectance (reflectance above the atmosphere) using published post-launch gains and offsets. For detailed instructions, see Landsat TM Calibration.

MODIS Utilities

Use Georeference Data to georeference your MODIS Level 1B and Level 2 data sets and apply correction for the MODIS bow tie effect. ENVI extracts latitude and longitude values from the header information to georeference the data. For detailed instructions, see Georeferencing MODIS.

OrbView-3 Utilities

Use Orthorectify OrbView-3 or Orthorectify OrbView-3 with Ground Control to orthorectify IKONOS data. For details, see Orthorectification Using RPCs.

QuickBird Utilities

Use the QuickBird Radiance utility to convert QuickBird relative radiance into absolute radiance in units of []. For detailed instructions, see QuickBird Radiance Calibration.

Use the Orthorectify QuickBird or Orthorectify QuickBird with Ground Control to orthorectify QuickBird data. For details, see Orthorectification Using RPCs.

SeaWiFS Utilities

Use SeaWiFS Utilities to calculate geometry information for and to georeference HDF and CEOS format SeaWiFS data. Geometry information includes latitude, longitude, sensor azimuth, sensor zenith, solar azimuth, solar zenith, and UTC time. The georeferencing function produces a full precision geocoding based on a complete geometry model of the earth and satellite orbits.

Build Geometry File

Use Build Geometry File to calculate the geometry for HDF and CEOS format SeaWiFS data. For detailed instructions see Building SeaWiFS Geometry Files.

Georeference SeaWiFS Data

Use Georeference Data to georeference your SeaWiFS data. For detailed instructions, see Georeferencing SeaWiFS Data.

SPOT Utilities

Build Geometry File

Use Build Geometry File to build a SPOT geometry file to calculate the X and Y coordinates for each pixel. For detailed instructions, see Building SPOT Geometry Files.

Georeference SPOT Data

Use Georeference Data to georeference SPOT data based on header information. See Georeferencing SPOT Data.

Orthorectify SPOT Data

Use the Orthorectify SPOT or Orthorectify SPOT with Ground Control to orthorectify SPOT data. For details, see Orthorectification Using RPCs.

TIMS Utilities

Thermal IR Atmospheric Correction

Use Thermal Atm Correction to approximate and remove the atmospheric contributions to thermal infrared data. TIMS data must be converted to radiance before performing the Thermal Atm Correction. ENVI provides a tool for converting TIMS data to radiance (see Radiance Calibration). For best results, perform this correction before converting your data to emissivity. The atmospheric correction algorithm used in ENVI is similar to the In-Scene Atmospheric Compensation algorithm, ISAC. This algorithm assumes that the atmosphere is uniform over the data scene and that there is an occurrence of a near-blackbody surface within the scene. The location of the blackbody surface is not required. A single layer approximation of the atmosphere is used and it is assumed that there is no reflected downwelling radiance.

The algorithm first determines the wavelength that most often exhibits the maximum brightness temperature. This wavelength is then used as the reference wavelength. Only spectra that have their brightest temperature at this wavelength are used to calculate the atmospheric compensation. At this point, for each wavelength, the reference blackbody radiance values are plotted against the measured radiances. A line is fitted to the highest points in these plotted data and the fit is weighted to assign more weight to regions with denser sampling. The compensation for this band is then applied as the slope and offset derived from the linear regression of these data with their computed blackbody radiances at the reference wavelength.

Upwelling atmospheric radiance and atmospheric transmission are approximated using the following method: first, the surface temperature of every pixel is estimated from the data and used to estimate the brightness temperature using the Planck function and assuming an emissivity of 1; next, a line is fitted, using one of two methods, to a scatterplot of radiance versus brightness temperature. The atmospheric upwelling and transmission are then derived from the slope and offset of this line.

Johnson, B. R. and S. J. Young, "In-Scene Atmospheric Compensation: Application to SEBASS Data Collected at the ARM Site", Technical Report, Space and Environment Technology Center, The Aerospace Corporation, May 1998.

Hernandez-Baquero, E., "Characterization of the Earths Surface and Atmosphere from Multispectral and Hyperspectral Thermal Imagery", Ph.D. Dissertation, Rochester Institute of Technology, Chester F. Carlsom Center for Imaging Science, Rochester, NY, 2000.

  1. Select one of the following paths:
    • Basic Tools  Preprocessing  Calibration Utilities  Thermal Atm Correction, or

      •  

    • Basic Tools  Preprocessing  Data-Specific Utilities  Thermal IR  Thermal Atm Correction, or

      •  

    • Basic Tools  Preprocessing  Data-Specific Utilities  TIMS  Thermal Atm Correction.

     

  2. Select the input file and perform any spatial or spectral subsetting, as desired. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset. The Thermal Atm Correction Parameters dialog appears.

    3.  

  3. Enter the Data Scale Factor needed to scale your data to units of W/m2/mm/sr.

    4.  

  4. Select the Wavelength Units from the pull-down menu button.

    5.  

  5. Use the arrow toggle button to select either All or Max Hit to determine which pixels are used in the surface temperature estimation regression.

    6.  

    Selecting All will estimate the surface temperature for each pixel by using the maximum value of the brightness temperatures found throughout the input wavelengths. Selecting Max Hit will estimate the surface temperature for only those pixels that have their maximum brightness temperatures at a particular wavelength. The wavelength used is the wavelength that has the largest number of pixels with a maximum brightness temperature value.

     

  6. Use the arrow toggle button to select either Top of Bins or Normalized Regression for the scatter plot fitting technique.

    7.  

    Selecting Top of Bins will fit a line to the top of the scatter plot of radiance vs. brightness temperature. The top of the scatter plot corresponds to those pixels whose emissivity is closest to 1. This Top of Bins fit is achieved by doing a standard least squares regression on the top 5% of the data in the scatter plot.

     


    Note
    This technique is susceptible to sensor noise which may occur at the top of the scatter plot.

     

    Selecting Normalized Regression will first fit a line to the scatter plot of radiance vs. brightness temperature by doing a standard least squares regression. The residuals of this fit are then compared to a normal probability plot. Another regression is done on the residuals in the normal plot. Points that are 3 times the noise equivalent sensor response (NESR) away from the regression line are deemed outliers and are removed. A final regression is done on the scatter plot using this reduced set of pixels.

     


    Note
    This method uses all the points in the scatter plot that are not outliers and does not fit to only the top of the scatter plot where the emissivity values are closest to 1.

     

    If you choose Normalized Regression, enter the Noise Equivalent Sensor Response in the text box.

     

  7. Enter a gain and offset output filename, if desired.

    8.  

  8. Use the arrow toggle button to select whether to plot the resulting atmospheric transmission and upwelling spectra.

    9.  

  9. Enter an output filename and click OK.

    10.  

    The results will appear in the Available Bands List.

See the following references for more information.

Johnson, B. R. and S. J. Young, "In-Scene Atmospheric Compensation: Application to SEBASS Data Collected at the ARM Site", Technical Report, Space and Environment Technology Center, The Aerospace Corporation, May 1998.

Hernandez-Baquero, E., "Characterization of the Earths Surface and Atmosphere from Multispectral and Hyperspectral Thermal Imagery", Ph.D. Dissertation, Rochester Institute of Technology, Chester F. Carlsom Center for Imaging Science, Rochester, NY, 2000.

Radiance Calibration

Use Radiance Calibration to calibrate raw data from the NASA Thermal Infrared Multispectral Scanner (TIMS) to radiance in units of W/m2/mm/sr. Data from on-board black bodies, and two internal reference sources, are stored within the first 60 bytes of each image line. The reference data can be smoothed. Gain and offset values are calculated for each TIMS spectral band using Plank's radiation law and the reference data and are used to calibrate the raw DN values to radiance. See the following reference for more information:

Palluconi, F. D. and Meeks, G. R., 1985. "Thermal Infrared Multispectral Scanner (TIMS): An Investigator's Guide to TIMS Data," JPL Publication 85-32, p. 14.

  1. Select one of the following:
    • Basic Tools  Preprocessing  Data-Specific Utilities  TIMS  Radiance Calibration

      •  

    • Basic Tools  Preprocessing  Calibration Utilities  TIMS Radiance

     

  2. Select the desired TIMS input file (must contain the 60 bytes per line of reference information). The TIMS Calibration Parameters dialog appears.

    3.  

  3. Enter the number of lines of reference data to smooth.

    4.  

  4. Enter an output filename and click OK.

The resulting bands appear in the Available Bands List and contain radiance values in W/m2/mm/sr.

Thermal IR Utilities

Use Thermal IR utilities to apply an atmospheric correction, and to convert the data set from radiance to emissivity and temperature using one of three methods: Reference Channel Emissivity, Emissivity Normalization, and Alpha Residuals. Thermal image data must be converted to radiance before performing the atmospheric correction. Perform this correction before converting your data to emissivity for best results.

Atmospheric Correction for Thermal IR Data

Use Thermal Atm Correction to approximate and remove the atmospheric contributions from thermal infrared radiance data. Thermal image data must be converted to radiance before performing the atmospheric correction. TIMS data should be converted to radiance using TIMS Radiance tool before performing the atmospheric correction. TIMS Radiance tools apply the correct band coefficients to convert to radiance in the appropriate units. No data scale factor is then required during the atmospheric correction. Perform the correction before converting your data to emissivity for the best results.


Note
ENVI does not check to make sure the images are thermal infrared data. Be sure that your data wavelengths measure between 8 and 14 mm before applying this correction.

The atmospheric correction algorithm used in ENVI is similar to the In-Scene Atmospheric Compensation algorithm, ISAC (see references at the end of this section). This algorithm assumes that the atmosphere is uniform over the data scene and that a near-blackbody surface exists within the scene. The location of the blackbody surface is not required for this correction. A single layer approximation of the atmosphere is used. No reflected downwelling radiance is also assumed.

The algorithm first determines the wavelength that most often exhibits the maximum brightness temperature. This wavelength is then used as the reference wavelength. Only spectra that have their brightest temperature at this wavelength are used to calculate the atmospheric compensation. At this point, for each wavelength, the reference blackbody radiance values are plotted against the measured radiances. A line is fitted to the highest points in these plotted data and the fit is weighted to assign more weight to regions with denser sampling. The compensation for this band is then applied as the slope and offset derived from the linear regression of these data with their computed blackbody radiances at the reference wavelength.

Upwelling atmospheric radiance and atmospheric transmission are approximated using the following method. First, the surface temperature of every pixel is estimated from the data and used to approximate the brightness temperature using the Planck function and assuming an emissivity of 1. Next, a line is fitted (using one of two methods) to a scatter plot of radiance vs. brightness temperature. The atmospheric upwelling and transmission are then derived from the slope and offset of this line.

  1. Select one of the following paths:
    • Basic Tools  Preprocessing  Calibration Utilities  Thermal Atm Correction

      •  

    • Basic Tools  Preprocessing  Data-Specific Utilities  Thermal IR  Thermal Atm Correction

      •  

    • Basic Tools  Preprocessing  Data-Specific Utilities  TIMS  Thermal Atm Correction

     

  2. Select the input file and perform any spatial or spectral subsetting, as desired. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset. The Thermal Atm Correction Parameters dialog appears.

    3.  

  3. Enter the Data Scale Factor needed to scale your data to units of W/m2/mm/sr.

    4.  


    Note
    The image output from this atmospheric correction uses the same units as the input image. For example, if the results of the correction are used to calculate emissivity and temperature, then the same scale factor must be specified.

     

  4. Select the Wavelength Units from the pull-down menu button.

    5.  

  5. Use the arrow toggle button to select either All or Max Hit to determine which pixels are used in the surface temperature estimation regression.

    6.  

    Selecting All will estimate the surface temperature for each pixel by using the maximum value of the brightness temperatures found throughout the input wavelengths. Selecting Max Hit will estimate the surface temperature for only those pixels that have their maximum brightness temperatures at a particular wavelength. The wavelength used is the wavelength that has the largest number of pixels with a maximum brightness temperature value.

     

  6. Use the arrow toggle button to select either Top of Bins or Normalized Regression for the scatter plot fitting technique.

    7.  

    Selecting Top of Bins will fit a line to the top of the scatter plot of radiance vs. brightness temperature. The top of the scatter plot corresponds to those pixels whose emissivity is closest to 1. This Top of Bins fit is achieved by doing a standard least squares regression on the top 5% of the data in the scatter plot.

     


    Note
    This technique is susceptible to sensor noise which may occur at the top of the scatter plot.

     

    Selecting Normalized Regression will first fit a line to the scatter plot of radiance vs. brightness temperature by doing a standard least squares regression. The residuals of this fit are then compared to a normal probability plot. Another regression is done on the residuals in the normal plot. Points that are 3 times the noise equivalent sensor response (NESR) away from the regression line are deemed outliers and are removed. A final regression is done on the scatter plot using this reduced set of pixels.

     


    Note
    This method uses all the points in the scatter plot that are not outliers and does not fit to only the top of the scatter plot where the emissivity values are closest to 1.

     

    If you choose Normalized Regression, enter the Noise Equivalent Sensor Response in the text box.

     

  7. Enter a gain and offset output filename, if desired.

    8.  

  8. Use the arrow toggle button to select whether to plot the resulting atmospheric transmission and upwelling spectra.

    9.  

  9. Enter an output filename and click OK.

    10.  

    The results will appear in the Available Bands List.

See the following references for more information.

Johnson, B. R. and S. J. Young, "In-Scene Atmospheric Compensation: Application to SEBASS Data Collected at the ARM Site", Technical Report, Space and Environment Technology Center, The Aerospace Corporation, May 1998.

Hernandez-Baquero, E., "Characterization of the Earths Surface and Atmosphere from Multispectral and Hyperspectral Thermal Imagery", Ph.D. Dissertation, Rochester Institute of Technology, Chester F. Carlsom Center for Imaging Science, Rochester, NY, 2000.

Converting to Emissivity and Temperature

The radiation emitted from a surface in the thermal infrared wavelengths is a function of both the surface temperature and emissivity. The emissivity relates to the composition of the surface and is often used for surface constituent mapping.

ENVI has three techniques that are used to separate the emissivity and temperature information in radiance data measured with thermal infrared sensors. Both the Reference Channel Emissivity and Emissivity Normalization techniques assume a fixed emissivity value and produce emissivity and temperature outputs. The Alpha Residuals technique does not provide temperature information.

See the following references for more information:

Hook, S. J., A. R. Gabell, A. A. Green, and P. S. Kealy, 1992. A comparison of techniques for extracting emissivity information from thermal infrared data for geologic studies. Remote Sensing of Environment, Vol. 42, pp. 123-135.

Kealy, P. S. and S. J. Hook, 1993., Separating temperature and emissivity in thermal infrared multispectral scanner data: Implications for recovering land surface temperatures. IEEE Transactions on Geoscience and Remote Sensing, Vol. 31, No. 6, pp.1155-1164.

Using Reference Channel Emissivity

Use Reference Channel Emissivity to calculate emissivity and temperature values from thermal infrared radiance data. The reference channel emissivity technique assumes that all the pixels in one channel (band) of the thermal infrared data have a constant emissivity. Using this constant emissivity, a temperature image is calculated and those temperatures are used to calculate the emissivity values in all the other bands using the Planck function. You can select the band to keep constant and enter the desired emissivity value for that band. See the previous references for more information.

  1. Select one of the following:
    • Basic Tools  Preprocessing  Data-Specific Utilities  Thermal IR  Reference Channel Emissivity

      •  

    • Basic Tools  Preprocessing  Calibration Utilities  Calculate Emissivity  Reference Channel

     

  2. Select the input radiance data file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset. The Calculate Emissivity parameters dialog appears.

    3.  

  3. Enter a data scale factor, if needed, to scale the radiance values into the units of W/m2/mm/sr (for example, if your data is in microflicks (mW/cm2/mm/sr) enter a scale factor of .01).

    4.  

  4. Enter a wavelength scale factor, if needed, to scale the wavelengths that are read from the header into units of mm.

    5.  

  5. From the Emissivity Band drop-down list, select which band to set to a constant emissivity value.

    6.  

  6. In the Assumed Emissivity Value text box, enter the desired emissivity value for the constant band.

    7.  

  7. Click the Output Temperature Image? arrow toggle button to designate whether or not to output a temperature image. Enter an output filename if needed.

    8.  

  8. Enter an output filename for the emissivity data and click OK.

The temperature image (single band) and emissivity data cube (same number of bands as input radiance data) appear in the Available Bands List.

Using Emissivity Normalization

Use Emissivity Normalization to calculate emissivity and temperature values from thermal infrared radiance data. The emissivity normalization technique calculates the temperature for every pixel and band in the data using a fixed emissivity value. The highest temperature for each pixel is used to calculate the emissivity values using the Planck function. You can enter the desired fixed emissivity value. See the references in the introduction to Thermal IR Utilities for more information.

  1. Select one of the following:
    • Basic Tools  Preprocessing  Data-Specific Utilities  Thermal IR  Emissivity Normalization

      •  

    • Basic Tools  Preprocessing  Calibration Utilities  Calculate Emissivity  Emissivity Normalization

     

  2. Select the input radiance data file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset. The Calculate Emissivity parameters dialog appears.

    3.  

  3. Enter a data scale factor, if needed, to scale the radiance values into the units of W/m2/mm/sr (for example, if your data is in microflicks (mW/cm2/mm/sr) enter a scale factor of .01).

    4.  

  4. Enter a wavelength scale factor, if needed, to scale the wavelengths (read from the header) into units of mm.

    5.  

  5. In the Assumed Emissivity Value text box, enter the desired fixed emissivity value to use to calculate the temperatures.

    6.  

  6. Click the Output Temperature Image? arrow toggle button to designate whether or not to output a temperature image. Enter an output filename if needed.

    7.  

  7. Enter an output filename for the emissivity data and click OK.

The temperature image (single band) and emissivity data cube (same number of bands as input radiance data) appear in the Available Bands List.

Using Alpha Residuals

Use Alpha Residuals to produce alpha residual spectra that approximate the shape of emissivity spectra from thermal infrared radiance data. Wien's approximation of the Planck function is used so the equation can be linearized with logarithms. The temperature and emissivity terms are separated and means are used to subtract the temperature term out.

The alpha residual spectra are a function of emissivity only and have a similar shape as emissivity spectra but have a zero mean. Therefore emissivity spectra must be scaled for direct comparison to alpha residual spectra. Emissivity spectra can be calculated from alpha residual spectra using empirical data as described in the Kealy, 1993 reference mentioned in the introduction to Thermal IR Utilities.

  1. Select one of the following:
    • Basic Tools  Preprocessing  Data-Specific Utilities  Thermal IR  Alpha Residuals

      •  

    • Basic Tools  Preprocessing  Calibration Utilities  Calculate Emissivity  Alpha Residuals

     

  2. Select the input radiance data file and perform any subsetting. For subsetting details, see "Selecting a Spatial Subset" and Selecting a Spectral Subset. The Calculate Emissivity parameters dialog appears.

    3.  

  3. Enter a data scale factor, if needed, to scale the radiance values into the units of W/m2/mm/sr (for example, if your data is in microflicks (mW/cm2/mm/sr) enter a scale factor of .01).

    4.  

  4. Enter a wavelength scale factor, if needed, to scale the wavelengths (read from the header) into units of mm.

    5.  

  5. Enter an output filename and click OK.

The alpha residual data cube (same number of bands as input radiance data) filename is listed in the Available Bands List.

  ENVI Online Help (August 12, 2005)