Burn Indices Tutorial
This tutorial shows how to create various burn index images from Landsat 8 imagery,
using the May 2014 San Diego County wildfires as a case study. You will learn how to
perform the following tasks:
l
Create binary masks to exclude water pixels
l
Calibrate multispectral data to top-of-atmosphere reflectance
l
Calibrate thermal data to brightness temperatures
l
l
Create a layer-stacked image that includes the corrected multispectral and
thermal bands
Create burn index images using ENVI's Spectral Index tool
The tutorial also includes a code example that shows how to perform these tasks in
batch mode using the ENVI application programming interface (API).
The estimated time to complete this tutorial is two hours. Use ENVI 5.2 or later. See
the following sections:
l
Files Used in this Tutorial
l
Case Study: San Diego County Wildfires in 2014
l
Background on Burn Indices
l
Open and Display the Post-Fire Image
l
Preprocessing
l
l
Create a Water Mask
l
Calibrate Multispectral Bands to Reflectance
l
Calibrate Thermal Bands to Brightness Temperatures
l
Create a Layer-Stacked Image
Create Burn Index Images
l
Burn Area Index
l
Normalized Burn Ratio
Page 1 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
l
l
Normalized Burn Ratio - Thermal
l
Differenced Normalized Burn Ratio
ENVI API Code Example
Files Used in this Tutorial
Tutorial files are available from the Exelis website or on the ENVI Resource DVD in the
LandsatCaseStudies\BurnIndices directory. Copy the files to a local drive.
File
Description
PostFireOLISubset.dat (and .hdr)
Landsat 8 OLI bands (seven total), acquired on
May 25, 2014, saved to ENVI raster format.
Landsat 8 TIR thermal bands (two total), acquired
on May 25, 2014, saved to ENVI raster format.
Normalized Burn Ratio image from May 9, 2014
PostFireTIRSubset.dat (and .hdr)
PreFireNBR.dat (and .hdr)
Data are available from the U.S. Geological Survey.
Case Study: San Diego County Wildfires in 2014
In May of 2014, close to 20 different wildfires erupted in San Diego County, triggered
by Santa Ana winds and a heat wave. The first fire started on May 5, and the last
remaining fires were extinguished by May 22. By May 18, the fires had burned more
than 27,000 acres (42 square miles) of land (Figueroa and Winkley, 2014). Some of
the communities affected by the fire included Camp Pendleton, Carlsbad, San Marcos,
and Escondido.
Reference:
Figueroa, T., and L. Winkley. "Fires in North County closer to being out." San Diego
Union Tribune, updated 19 May 2014.
http://www.utsandiego.com/news/2014/may/18/Regions-wildfires-closer-to-outas-weather-shifts/. Accessed June 2014.
Page 2 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
Background on Burn Indices
Land resource managers and fire officials use burn severity maps from remote
sensing instruments to predict areas of potential fire hazards, to map fire perimeters,
and to study areas of vegetation regrowth after fires. Landsat imagery has
traditionally been used to create indices that indicate burn severity because of its
repeated coverage, ease of access, and spectral wavelengths.
In this tutorial, you will create burn severity images using a variety of different
indices.
Burn Area Index
The Burn Area Index (BAI) highlights burned land in the red to near-infrared (NIR)
spectrum, by emphasizing the charcoal signal in post-fire images. The index is
computed from the spectral distance from each pixel to a reference spectral point,
where recently burned areas converge. Brighter pixels indicate burned areas. BAI is
computed as follows (Martín, 1998):
Normalized Burn Ratio
This index highlights burned areas in large fire zones greater than 500 acres. The
formula is similar to a normalized difference vegetation index (NDVI), except that it
uses near-infrared (NIR) and shortwave-infrared (SWIR) wavelengths (Lopez, 1991;
Key and Benson, 1995).
The NBR was originally developed for use with Landsat TM and ETM+ bands 4 and 7,
but it will work with any multispectral sensor (including Landsat 8) with a NIR band
between 0.76-0.9 µm and a SWIR band between 2.08-2.35 µm.
Normalized Burn Ratio - Thermal
This index uses a thermal band to enhance the NBR. It results in a better separability
between burned and unburned land (Holden et al., 2005).
Page 3 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
NBRT1 was originally developed for use with Landsat TM and ETM+ bands 4, 7, and 6.
However, it will work with any multispectral sensor (including Landsat 8) with bands
that fall within the following ranges:
l
NIR: 0.76 to 0.9 µm
l
SWIR: 2.08 to 2.35 µm
l
Thermal: 10.4 to 12.5 µm
References
Holden, Z., et al. "Evaluation of Novel Thermally Enhanced Spectral Indices for
Mapping Fire Perimeters and Comparisons with Fire Atlas Data." International Journal
of Remote Sensing 26 (2005): 4801-4808.
Key, C. and N. Benson. "Landscape Assessment: Remote sensing of severity, the
Normalized Burn Ratio; and ground measure of severity, the Composite Burn Index."
In FIREMON: Fire Effects Monitoring and Inventory System, RMRS-GTR, Ogden, UT:
USDA Forest Service, Rocky Mountain Research Station (2005).
Lopez Garcia, M.J., and Caselles, V. "Mapping Burns and Natural Reforestation using
Thematic Mapper Data. Geocarto International 6 (1991): 31-37.
Martín, M. Cartografía e inventario de incendios forestales en la Península Iberica a
partir de imágenes NOAA AVHRR. Doctoral thesis, Universidad de Alcalá, Alcalá de
Henares (1998).
Set Preferences and Display the Post-Fire Image
Follow these steps to begin:
1. From the menu bar, select File > Preferences.
2. Click the Directories item on the left side of the Preferences window.
3. Click in the white space next to Output Directory.
4. Click the right-facing arrow.
Page 4 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
5. Choose a folder where you want to save the various files that will be created in
this tutorial.
6. Click OK in the Preferences dialog.
7. From the menu bar, select File > Open.
8. Select the file PostFireOLISubset.dat, and click OK.
9. Right-click on the layer name in the Layer Manager and select Zoom to Layer
Extent. This multispectral image shows the California coastline from San
Clemente in the north to Del Mar in the south. You can see some of the larger
burn scars near Camp Pendleton in the upper-left part of the image; they have a
distinct grey color. If you cannot clearly see them, choose a different stretch
type from the drop-down list in the toolbar:
Tip: This image is a spatial subset of a full Landsat 8 scene. To open full scenes distributed by the U.S.
Geological Survey, select the *MTL.txt metadata file. The seven OLI bands are grouped separately from
the two TIR thermal bands, Cirrus band, and Quality band. This particular image was created by selecting
File > Save As from the menu bar, selecting the OLI band group, defining a spatial subset, and saving the
result to ENVI raster format. The thermal bands were similarly saved to a separate file for use with the
Calibrate Thermal Bands section of this tutorial.
Page 5 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
Preprocessing
The following preprocessing steps ensure that the images are properly masked and
calibrated before computing burn indices. Not all of these steps are required in every
case study; exceptions are noted below.
Create a Water Mask
Scenes that contain oceans or other large water bodies should be masked to exclude
these pixels, as they can interfere with calibration and atmospheric correction. Full
Landsat 8 scenes also contain black background pixels that should be excluded from
processing. The sample images you will use in this tutorial have already been
spatially subsetted and do not include any background pixels.
Masking large water bodies is also a prerequisite for using the QUick Atmospheric
Correction (QUAC) tool.
An effective way to create a water mask is to create a band-thresholded region of
interest (ROI), using the near-infrared (NIR) band. Water has an extremely low
reflectance in the NIR region, so those pixels are nearly black. You can isolate those
pixels with the ROI Tool.
1. Right-click on the PostFireOLISubset.dat layer name in the Layer Manager,
and select New Region of Interest.
2. Change the ROI Name to Water.
3. In the ROI Tool, click the Threshold tab.
4. Click the Add New Threshold Rule button
.
5. In the File Selection dialog, select the Near Infrared (NIR) band and click OK.
A histogram of the NIR band is displayed in the Choose Threshold Parameters
dialog. You will identify the water pixels by selecting the range of low pixel
values in the histogram.
6. Click and drag the red line on the left edge of the plot toward the right, covering
the data values from 0 to approximately 10,000.
Page 6 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
7. Click the Preview option. The pixels that fall within this range are highlighted in
red.
Page 7 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
8. Some of the pixels in the Camp Pendleton burn scar also have extremely low
NIR values, but we do not want to mark these pixels. You will need to move the
slider in the histogram further to the left so that you highlight water pixels but
no other features. To do this, hold down your middle mouse button to draw a
box in the histogram around the area indicated in blue:
This zooms into the data value range of 6,000-10,000 so that you can see the
histogram in more detail.
Page 8 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
9. Move the right-most red slider to the left, until the red "Data" label is
approximately 7769:
Note how this highlights the water pixels in the image without highlighting other
features.
Tip: You can also use ROI thresholds to highlight clouds, using the highest data values in the
histogram. However, you will ignore the sporadic cloud cover for this tutorial.
10. Click OK in the Choose Threshold Parameters dialog.
11. In the search window of the Toolbox, type build mask and double-click the
Build Mask tool name that appears.
12. In the Build Mask Input File dialog, select PostFireOLISubset.dat, and click
OK.
13. Click the Options drop-down list in the Mask Definition dialog and select
Import ROIs.
14. Select the Water ROI from the list, and click OK.
15. Click the Options drop-down list again in the Mask Definition dialog and select
choose Selected Areas "Off". By doing this, the water pixels will have values
of 0, and all other pixels will have values of 1.
16. Enter the output filename OLIMask.dat.
Page 9 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
17. Click OK in the Mask Definition dialog. The mask image is displayed.
When you apply this mask to the image in the next step, the black pixels
(values of 0) will be excluded from further processing, while the white pixels
(values of 1) will be processed.
18. In the search window of the Toolbox, type apply mask. Double-click the Apply
Mask tool name that appears.
19. In the Apply Mask Input File dialog, select PostFireOLISubset.dat. Do not
click OK yet.
20. Click the Select Mask Band button, then select Mask Band and click OK.
Page 10 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
21. Click OK in the Apply Mask Input File dialog.
22. In the Apply Mask Parameters dialog, keep the Mask Value of 0.
23. Enter an output filename of PostFireOLISubsetMasked.dat.
24. Click OK.
25. When the masked image displays, click the Cursor Value icon
toolbar.
in the
Page 11 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
26. Move the cursor over the ocean and water pixels to verify that they are 0 in the
red, green, and blue bands.
Next, you will need to tell ENVI to ignore these 0 values:
27. In the Toolbox, type the words edit envi. Double-click the Edit ENVI Header
tool name that appears.
28. In the Edit Header Input File dialog, select PostFireOLISubsetMasked.dat,
and click OK.
29. In the Header Info dialog, click the Edit Attributes drop-down list and select
Data Ignore Value.
30. Enter 0 for the Data Ignore Value, then click OK.
31. Click OK in the Header Info dialog. The masked image closes and is removed
from the display.
32. Close the ROI Tool and Cursor Value dialogs.
33. Right-click on the View entry in the Layer Manager and select Remove All
Layers.
Calibrate OLI Bands to Reflectance
To create spectral index images such as Burn Area Index and Normalized Burn Ratio,
the source images should be calibrated to top-of-atmosphere (TOA) reflectance,
where pixel values range from 0 to 1.0 or 0 to 100.
Page 12 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
Tip: Using rigorous, model-based atmospheric correction methods such as FLAASH and QUAC to create
apparent surface reflectance images is usually unnecessary when creating burn index images from
multispectral imagery. If you wish to create a surface reflectance images, tools such as Dark Subtraction,
Flat Field, or IARR are often sufficient.
1. In the search window of the Toolbox, type calibration. Double-click the
Radiometric Calibration tool name that appears.
2. In the File Selection dialog, select the file PostFireOLISubsetMasked.dat, and
click OK.
3. In the Radiometric Calibration dialog, select Reflectance from the Calibration
Type drop-down list.
4. Keep the default selections for all other settings. Do not click the Apply
FLAASH Settings button.
5. Enter an output filename of PostFireReflectance.dat, and click OK.
6. Wait for the RadiometricCalibration process to complete in the Process Manager
(in the lower-right corner of the interface):
Calibrate Thermal Bands to Brightness Temperatures
This step is only required for creating a "Normalized Burn Ratio - Thermal" image,
which this tutorial covers. Since Landsat thermal bands are not used for Burn Area
Index or Normalized Burn Ratio spectral indices, you do not need to calibrate the
thermal bands or perform layer stacking for these indices. You do not need to create
a water mask for the thermal bands.
Perform these steps to calibrate the thermal bands to brightness temperatures (in
Kelvins):
1. From the menu bar, select File > Open.
2. Select the file PostFireTIRSubset.dat, and click Open. The Thermal Infrared
1 band appears in the display.
3. In the search window of the Toolbox, type calibration. Double-click the
Radiometric Calibration tool name that appears.
4. In the File Selection dialog, select the file PostFireTIRSubset.dat, and click
OK.
Page 13 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
5. In the Radiometric Calibration dialog, select Brightness Temperature from
the Calibration Type drop-down list.
6. Keep the default selections for all other settings. Do not click the Apply
FLAASH Settings button.
7. Enter an output filename of PostFireTIRCalibrated.dat, and click OK.
Create a Layer-Stacked Image
This step will combine the calibrated thermal and OLI bands into one file; this is only
required for creating a "Normalized Burn Ratio - Thermal" image. You do not need to
create a layer-stacked image when computing Burn Area Index or Normalized Burn
Ratio spectral indices.
Layer stacking not only combines different bands in a single file but also ensures they
are projected to a common grid.
1. In the search window of the Toolbox, type the words layer stack. Double-click
the Layer Stacking tool name that appears.
2. In the Layer Stacking Parameters dialog, click the Import File button.
3. Use the Ctrl key on your keyboard to select both PostFireReflectance.dat
and PostFireTIRCalibrated.dat. Click OK.
4. From the Resampling drop-down list, select Cubic Convolution.
5. Keep the remaining parameters at their default settings.
6. Enter an output filename of PostFireLayerStack.dat, and click OK.
7. When processing is complete, click the Data Manager icon
in the toolbar.
8. Verify that the layer stack includes seven OLI bands and two TIR bands.
Page 14 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
The band names are not that helpful, as they contain all of the pre-processing
steps that you have performed so far. You can rename them as follows:
9. In the search window of the Toolbox, type edit envi. Double-click the Edit
ENVI Header tool name that appears.
10. Select the file PostFireLayerStack.dat, and click OK.
11. In the Header Info dialog, click the Edit Attributes drop-down list and select
Band Names.
12. Select the first band in the list, and rename it to Coastal aerosol. Press the
Enter key to advance to the next band name. (Do not click OK, as this will exit
the dialog completely.)
13. Enter band names as follows, then click OK:
Page 15 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
14. Click OK in the Header Info dialog. The image closes and is removed from the
display.
Create Burn Index Images
ENVI's Spectral Index tool creates images that represent different indices such as
vegetation, burned areas, geologic, and built-up features. You must run this tool each
time you create an index image. Follow these steps to compute burn indices:
1. In the search window of the toolbox, type spectral indices. Double-click the
Spectral Indices tool name that appears.
2. Click the Browse button next to the Input Raster field.
3. Select the file PostFireLayerStack.dat, and click OK.
4. Click the Index drop-down menu and select Burn Area Index.
5. Unselect the Display Result option; you will view the indices in multiple views
later.
6. In the Output Raster field, enter a filename of BAI.dat and click OK.
Page 16 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
7. Repeat Steps 1-7 for the following indices:
l
Normalized Burn Ratio (output filename: PostfireNBR.dat)
l
Normalized Burn Ratio Thermal 1 (output filename: NBRT1.dat)
8. From the menu bar, select Views > 2x2 Views. Four empty views appear in
the display.
9. Click the Data Manager icon
in the toolbar.
10. Drag and drop the Burn Area Index band name from the Data Manager to the
upper-left view.
11. Drag and drop the Normalized Burn Ratio band name from the Data Manager
to the upper-right view.
12. Drag and drop the Normalized Burn Ratio Thermal 1 band name from the
Data Manager to the lower-left view.
13. From the menu bar, select Views > Link Views.
14. With the Geo Link option already selected, click Link All. Then click OK. All
three views center over the same geographic location.
15. In the Go To field of the toolbar, type the pixel coordinates 631p,472p and
press the Enter key. (The "p" tells ENVI that these are pixel coordinates, not
map or geographic coordinates.) The views center over the burned region near
Camp Pendleton.
Page 17 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
Notice that the brighter pixels in the Burn Area Index image (upper-left view)
indicate burned areas, while darker pixels indicate burned areas in the Normalized
Burn Ratio images.
1. Enter the following pixel coordinates in the Go To field to explore other burned
areas:
l
1214p,530p (Fallbrook)
l
1263p,1669p and 873,1260p (Carlsbad)
l
1246p,1253p (San Marcos)
l
58p,123p (Camp Pendleton)
Page 18 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
2. Use the navigation, zoom, and stretch tools in the toolbar to further explore the
images. How are the Normalized Burn Ratio and its thermal version different
from each other? Does one separate burned areas better than the other?
3. When you are finished, right-click on each View item in the Layer Manager and
select Remove View.
Differenced Normalized Burn Ratio
A differenced normalized burn ratio (ΔNBR) is another burn-severity product that
measures absolute change in the NBR. You can easily create a ΔNBR image by
performing these steps:
1. Create an NBR image immediately before the fire.
2. Create an NBR image during, or after the fire.
3. Subtract the post-fire NBR image from the pre-fire NBR image.
Brighter pixels indicate higher levels of burn severity.
You have to conduct all of the pre-processing steps for the pre-fire image that you did
for the post-fire image in this tutorial, except for thermal band calibration and layer
stacking. We have done all of these steps for you for the pre-fire image.
Follow these steps to create a ΔNBR image:
1. From the menu bar, select File > Open.
2. Select the file PreFireNBR.dat, and click OK. The pre-fire NBR image is
displayed.
3. Before you can subtract one image from the other, both must be in the same
spatial grid. While both images are in the same projection, they are offset by
one pixel. Layer stacking will ensure that they are in a common grid. In the
search window of the Toolbox, type layer stack. Double-click the Layer
Stacking tool name that appears.
4. In the Layer Stacking Parameters dialog, click the Import File button.
5. Use the Ctrl key to select the files PreFireNBR.dat and PostFireNBR.dat.
(The post-fire NBR image was created in Step 7 of Create Burn Index Images.)
Click OK.
6. Keep all of the remaining parameters at their default settings.
7. Enter an output filename of NBRLayerStack.dat, and click OK.
Page 19 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
8. In the search window of the Toolbox, type band math. Double-click the Band
Math tool that appears.
9. Enter the following in the Enter an expression field: float(b1 - b2). Click OK.
10. With B1 selected in the Variables to Bands Pairings dialog, click Layer
(Normalized Burn Ratio: PreFireNBR.dat).
11. Select B2 - [undefined].
12. Click Layer (Normalized Burn Ratio: PostFireNBR.dat).
13. Enter an output filename of DifferencedNBR.dat, and click OK. The following
image appears, with the white pixels indicating burned areas. (The masked
ocean pixels are also colored white.)
Page 20 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
The U.S. Geological Survey FIREMON program (Key and Benson, 2005) published
categories of burn severity, based on pixel values that have been scaled accordingly:
ΔNBR Values
Burn Severity
< -0.25
-0.25 to -0.1
-0.1 to 0.1
0.1 to 0.27
0.27 to 0.44
0.44 to 0.66
> 0.66
High post-fire regrowth
Low post-fire regrowth
Unburned
Low-severity burn
Moderate- to low- severity burn
Moderate- to high-severity burn
High-severity burn
We created a density color slice file that you can overlay on the ΔNBR image.
1. Right-click on the DifferencedNBR.dat layer in the Layer Manager and select
New Raster Color Slice.
2. Select the Band Math band name under DifferencedNBR.dat, and click OK.
3. Click the Clear Color Slices button
.
4. Click the Open button and select the file DNBRColorSlice.dsr. Click Open.
The image is dividied into different colors as defined by this color slice.
5. Click OK.
6. In the Go To field of the toolbar, type the pixel coordinates 631p,472p and
press the Enter key.
7. In the Zoom To drop-down menu in the toolbar, enter 125 (%). The display
centers over the Camp Pendleton burn area.
8. In the Layer Manager, click to deselect the purple, blue, and grey boxes. Only
the highest levels of burn severity are displayed. The following images show
examples of different levels of burn severity overlaid on the post-fire Landsat
image:
Page 21 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
Page 22 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
ENVI API Code Example
The following is a sample IDL program that creates a burn index image consisting of
three bands: Burn Area Index, Normalized Burn Ratio, and Normalized Burn Ratio Thermal 1. It shows how to open the original Landsat 8 scene (available for download
from the USGS EarthExplorer web site). It defines a spatial subset around the burned
area near Camp Pendleton, California. It performs the same calibration steps as the
tutorial. It does not create any masks, since the spatial subset does not contain any
ocean pixels. It saves the resulting file to disk as BurnIndices.dat. A copy of this
program (BurnIndicesExample.pro) is also available on the ENVI® Resource DVD
in the LandsatCaseStudies\BurnIndices directory.
To customize this program for a different image and location, change the input file
path and name, the geographic coordinates, and the directory on the
IndexRaster.Export command at the end of the program.
PRO BurnIndicesExample
COMPILE_OPT idl2
; Start the application
e = ENVI()
; Open the Landsat image. Select the MTL metadata file.
; Change the file path to your own directory
File = 'LC80400372014145LGN00_MTL.txt'
Raster = e.OpenRaster(File)
; Landsat 8 images are stored in a five-element
; array. Multispectral bands from the OLI sensor
; are stored in the first array element. Thermal
; bands from the TIR sensor are stored in the fourth
; array element.
OLIBands = Raster[0]
TIRBands = Raster[3]
; This Landsat image was downloaded from
; the USGS EarthExplorer web site and is already
; georeferenced to a UTM Zone 12N (WGS 1984) projection
; in units of meters.
;
; This is the area of interest:
UpperLeftLat = 33.38529349
Page 23 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
UpperLeftLon = -117.45646568
LowerRightLat = 33.28356850
LowerRightLon = -117.26327378
; Convert these coordinates from degrees to map coordinates
; in meters. Then define a spatial subset around the area of
; interest for the multispectral and thermal rasters.
OLISpatialRef = OLIBands.SPATIALREF
OLISpatialRef.ConvertLonLatToMap, UpperLeftLon, $
UpperLeftLat, MapX, MapY
OLISpatialRef.ConvertLonLatToMap, LowerRightLon, $
LowerRightLat, MapX2, MapY2
OLISubset = ENVISubsetRaster(OLIBands, $
SPATIALREF=OLISpatialRef, $
SUB_RECT=[MapX, MapY2, MapX2, MapY])
TIRSpatialRef = TIRBands.SPATIALREF
TIRSubset = ENVISubsetRaster(TIRBands, $
SPATIALREF=TIRSpatialRef, $
SUB_RECT=[MapX, MapY2, MapX2, MapY])
; Calibrate the multispectral bands
OLITask = ENVITask('RadiometricCalibration')
OLITask.Input_Raster = OLISubset
OLITask.Calibration_Type = 'Top-of-Atmosphere Reflectance'
OLITask.Output_Raster_URI = e.GetTemporaryFilename()
OLITask.Execute
OLIMSRaster = OLITask.Output_Raster
; Calibrate the thermal bands
TIRTask = ENVITask('RadiometricCalibration')
TIRTask.Input_Raster = TIRSubset
TIRTask.Calibration_Type = 'Brightness Temperature'
TIRTask.Output_Raster_URI = e.GetTemporaryFilename()
TIRTask.Execute
TIRThermalRaster = TIRTask.Output_Raster
; Create a band stack that includes the seven calibrated
; multispectral bands and the two calibrated thermal bands.
MSRaster = ENVIMetaspectralRaster([OLIMSRaster, $
TIRThermalRaster])
Page 24 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
; Create a raster that contains multiple burn indices
IndexTask=ENVITask('SpectralIndices')
IndexTask.Input_Raster = MSRaster
IndexTask.Index = ['Burn Area Index', $
'Normalized Burn Ratio', $
'Normalized Burn Ratio Thermal 1']
IndexTask.Output_Raster_URI = e.GetTemporaryFilename()
IndexTask.Execute
IndexRaster = IndexTask.Output_Raster
; Get the data collection
DataColl = e.Data
; Add the spectral index raster to the data
; collection (Data Manager)
DataColl.Add, IndexRaster
; Export the spectral index raster to ENVI format
newFile = e.GetTemporaryFilename()
IndexRaster.Export, newFile, 'ENVI'
; Display each index in a separate view
View = e.GetView()
View2 = e.CreateView()
View3 = e.CreateView()
Layer = View.CreateLayer(IndexRaster, BANDS=0)
Layer2 = View2.CreateLayer(IndexRaster, BANDS=1)
Layer3 = View3.CreateLayer(IndexRaster, BANDS=2)
View.PixelLink, /LINK_ALL
View.Zoom, /FULL_EXTENT
View2.Zoom, /FULL_EXTENT
END
Copyright Notice:
ENVI is a registered trademark of Exelis Inc.
Page 25 of 26
© 2014 Exelis Visual Information Solutions, Inc. All Rights Reserved. This information is not subject to the controls of the
International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may
be restricted from transfer to various embargoed countries under U.S. laws and regulations.
© Copyright 2024 ExpyDoc
