Lab 4 - Due 7 PM on Sept 27, 2011
Student name: _______________
Geo5053/4093 - Remote Sensing, UTSA
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http://www.utsa.edu/LRSG/Teaching/GEO5053_4093/GEO5053_4093Syllabus_2011.html
Digital Image Processing I: Atmospheric Correction,
Radiance, Reflectance, NDVI from Landsat Image
Objective: Learn about overlaying a vector file on an image, creating a Region of Interest
(ROI), using a ROI to make a mask, and doing a simple atmospheric correction (DOS).
Part I: Explain these basic concepts
(1) Refraction
(2) Atmospheric scattering
(3) Absorption and major atmospheric windows for remote sensing on Earth surface
(4) Reflectance, spectral reflectance, albedo
(5) Explain why we see blue sky in middle day and why we see orange and red sky in sunset or
sunrise
(6) Solid angle and radiance
(7) Explain the processes/path and interactions as energy transfer from sun to earth and back to
remote sensor
(8) Explain why we need to do atmospheric correction in land and ocean remote sensing
Part II: Lab
A. Preparation
(1) Go to the LRSG server (\\129.115.25.240\XIE_misc\Fall08-RS\) and copy the Lab4
folder into your sub-folder. [The server is accessible only from the UTSA lab computers].
Always remember to save all results to your lab directory (i.e. Lab4 for today’s lab), and not to
the default ENVI directory.
(2) Today we will use a new ETM+ image (p27r40_July8_2002.img). This image was
acquired just after a big flood event. The July 2002 floods in south Texas resulted from
unprecedented precipitation rates in excess of 3 inches per hour, much like a tropical system,
which resulted in 9 deaths, over 48000 homes damaged, and nearly one billion dollars in
damage. In future labs, you will classify and compute the flooded areas.
Lab 4 - Due 7 PM on Sept 27, 2011
Student name: _______________
Geo5053/4093 - Remote Sensing, UTSA
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http://www.utsa.edu/LRSG/Teaching/GEO5053_4093/GEO5053_4093Syllabus_2011.html
B. Get a sense of the image
(1) This image uses the same coordinate system as for Labs 2 and 3, but with a different
year and date. However this image includes band 6 (the thermal band at 11.45 μm) which
provides temperature information for each pixel (we will use it in later labs), and this image
covers an entire ETM+ scene (about 180 km x 180 km in dimension). The image from Labs 2
and 3 was a subscene covering only San Antonio.
(2) Load this image as RGB 742 (band 7 as red, band 4 as green, and band 2 as blue) for
Display 1 and RGB 321 for Display 2, and Link the two images. San Antonio is in the upper left
portion of the image. The figure below shows you a vector layer (highway) on top of the RGB
742 image, indicating the location of San Antonio.
Figure 1
(3) There are multiple ways to open a vector file (and also to perform various other useful
ENVI functions).
1 - Select the ENVI toolbar -> File menu -> Open Vector File.
2 - Select the ENVI toolbar -> Vector menu -> Open Vector File.
3 - Select the Image Display toolbar -> Overlay menu -> Vectors, which will open a Vector
Parameters popup window, and from there you can select the File menu -> Open Vector File.
Lab 4 - Due 7 PM on Sept 27, 2011
Student name: _______________
Geo5053/4093 - Remote Sensing, UTSA
Page 3 of 5
http://www.utsa.edu/LRSG/Teaching/GEO5053_4093/GEO5053_4093Syllabus_2011.html
Use method three. On the Select Vector Filenames popup window, navigate to your Lab4 data
location, choose the file road-UTM_.evf, then click OK. The will overlay the highway vector
file (*.evf for ENVI vector fomat), leaving the Vector Parameters popup window open.
Question 1: Explore the image and give a general interpretation about what you see. For
example, water (flooding), clouds, vegetation, etc, and their color differences between the RGB
742 and RGB 321 images.
C. Use Region of Interest (ROI) tool and make a mask
From figure 1 above, you can see there is a dark area surrounding your image. If you use the
Cursor Location/Value tool, you will find pixel values in that area are zero. So if you want to do
statistics or further image processing, you should exclude this area (otherwise these many zero
values will throw off your statistics values). One way to do this is to make a mask, telling ENVI
to process data only from specific areas (and to exclude the outside areas).
Step 1, select the Image Display toolbar -> Overlay menu -> Region of Interest, which will
open the ROI Tool popup window. Use this tool to build a ROI which covers only the image
area and not the dark area outside the image (you do not need to be exact). Figure 2 is my
example ROI selected. On the ROI Tool toolbar -> ROI_Type menu, observe the default is a
polygon. On the ROI Tool window, observe you can draw your ROI on the Image, Scroll, or
Zoom windows. For this lab, select either the Image or Scroll window. Drawing a ROI can be a
little challenging at first. You will use this tool in future labs, so please become familiar with it.
Some helpful tips: Left-clicking once at a corner will draw straight lines in between. Left-clickand-hold lets you draw a freehand curved shape. Right-clicking once will close a open polygon.
After drawing a polygon, pan around to the image corners and ensure you have not accidentally
included any of the black background areas. Right clicking inside a closed polygon will select it.
In the ROI Tool window, observe the number of pixels and polygons listed are NOT zero. [For
this lab, you do not need to save the ROI, but please feel free to explore this]
Figure 2
Lab 4 - Due 7 PM on Sept 27, 2011
Student name: _______________
Geo5053/4093 - Remote Sensing, UTSA
Page 4 of 5
http://www.utsa.edu/LRSG/Teaching/GEO5053_4093/GEO5053_4093Syllabus_2011.html
Step 2. Select the ENVI toolbar -> Basic Tools menu -> Masking -> Build Mask to
open a small popup window. Choose which display has your image laoded for masking (i.e
Display #1), then click OK to open the Mask Definition popup window. Next select the Mask
Definition toolbar -> Options -> Import ROIs, select the ROIs you just created, and click OK.
On the Mask Definition window, click the Choose button, navigate to your Lab4 folder, and
create an output filename: mask.img. Click Apply, and mask.img should appear in the Available
Bands List window. Open the mask image into a new display window.
Question 2: Show your mask image and show the pixel values for the mask image. What does
this value mean?
Question 3: Create statistics for your ETM+ image, using the mask.img to exclude the dark area
surrounding the image. Show the statistics, histograms, and legend for all 7 bands. Figure 3 is an
example I did based on my mask. Your mask might be different, so your statistics might be
different from what I have as well.
Figure 3
Lab 4 - Due 7 PM on Sept 27, 2011
Student name: _______________
Geo5053/4093 - Remote Sensing, UTSA
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http://www.utsa.edu/LRSG/Teaching/GEO5053_4093/GEO5053_4093Syllabus_2011.html
D. Atmospheric Correction
In the lectures, you learned about interactions between the atmosphere and EMR. And you know
remotely sensed radiance includes two parts: one from the target area (which we want), and the
other from the path (path radiance, which we do not want). The process to remove path radiance
is called atmospheric correction. There are two types of atmospheric correction: (1) absolute
atmospheric correction: radiative transfer-based atmospheric correction and empirical line
calibration and (2) relative radiometric correction: Dark Object Subtraction (DOS) and multipledata image normalization using regression. For this lab, we will do a simple DOS correction.
The principles for DOS include (1) find the darkest object in the image; (2) assume its spectral
reflectance should be all zero (target radiance); (3) assume the measured values above zero
represent the atmospheric noise (path radiance) and are uniformly distributed across the image
area; (4) subtract the path radiance from each pixel radiance of the image, then we should get a
relatively atmospheric free image. Usually these dark objects are water bodies (on figure 4, fresh
water has very low reflectance, meaning water absorbs most light, especially beyond 0.75 µm).
Figure 4. Spectrum signatures for different materials
In ENVI, the DOS routine is called Dark Subtract. Select the ENVI toolbar -> Basic Tools
menu -> Preprocessing -> General Purpose Utilities -> Dark Subtract to open a popup
window. Select your ETM+ image as the input file and click OK to open the Dark Subtraction
Parameters popup window. Select the User Value subtraction method. The default subtraction
value for each band is 0. Select each band one at a time and enter subtraction values matching
the band minimum values computed during question 3 (similar as figure 3). Save the corrected
image as a file in your Lab4 folder, with a filename p27r40_July8_2002DOS.img
Question 4: Show statistics for your new image, using the mask.img created above.