Lab 3

Comparison of Image Perspectives, Scales, and Spectral Bands

Geog 418/518, Fundamentals of Remote Sensing

Lab Goals

 

The goals of this lab are to:

 

a)      provide you a brief introduction to using ERDAS Imagine for viewing images;

b)      have you use think about some of the relative advantages and disadvantages of using different image perspectives, image scales, and spectral resolutions; and

c)      challenge you to think about some applications for the different image types.

 

This will probably be the shortest lab of the quarter.  Following labs are significantly longer and will require more time to complete.

 

Lab Procedures:

 

I want you to work in pairs on this lab and turn in only one lab per team.  Many studies and my own personal experience have shown that working in pairs maximizes the amount of learning that occurs.  Even if you feel you understand the materials perfectly, the act of discussing and explaining the materials with your partner or comparing answers will improve your understanding and your ability to articulate your knowledge to another user – a key skill in remote sensing.  As a remote sensing professional, you will often find yourself in the position of having to explain the imagery and the analysis to novices.  This is a good starting point for acquiring those verbal presentation skills.

 

Your team is also encouraged to talk to other teams if you get stuck.  You must, however, fill in the answers with your own words.

 

Write answers in complete sentences, except where the question specifies otherwise.  Please be legible.

 

Lab Activities and Questions:

 

Make a folder in your private data directory called Myname_Lab02.  Then go into the Geog418/Lab_02class folder and copy all the files to your Myname_lab02 folder.  In ERDAS imagine, go to the menu and specify under Session/Preferences that you want the Default Data Directory and Default Output Directory to be the Myname_Lab02 folder.

 

 

You will now have a number of image files in Myname_Lab02.  These images are:

 

·        Lamar_closeup_oblique, which is an closeup digital shot of the gravel flats along side the Lamar River, Yellowstone National Park.  The shot is looking upstream (east) to a high terrace above the river.  This is a .jpg image.

·        Lamar_landscape_oblique, which is a panorama shot looking downstream (west) from the bluff top that you can see in the closeup shot.  This is a .jpg image.

·        Lamar_1m_BW, a 1 m pixel resolution aerial image of the Lamar River in panchromatic (black and white) taken on August 3, 1999.  This is a .jpg image.

·        Lamar_1m_color, a 1 m pixel resolution aerial image of the Lamar River in color taken on August 3, 1999. This is a .jpg image.

·        Lamar_1m_TM5, a 1 m pixel resolution 6 band (similar to the thematic mapper sensor on the Landsat satellite) aerial  image taken on August 3, 1999.  This is an .img image, the default for ERDAS imagine.

·        Lamar_8m_color, a 8 m pixel resolution color aerial image of the Lamar River and the lower ends of Soda Butte and Cache Creeks, collected on July 5, 1999. This is a .jpg image.

·        Lamar_high_oblique, a Space Shuttle image looking off to the side.  This is a .jpg image.

 

The table below summarizes the characteristics of the images:

 

 

 

Image

 

 

Perspective

 

Spatial Resolution

Spectral characteristics

Number of bands

Spectral Coverage

Lamar_closeup_oblique

Oblique

~3 cm

3

Visible: Red, Green, Blue

Lamar_landscape_oblique

Oblique

~25 cm

3

Visible: Red, Green, Blue

Lamar_1m_BW

Vertical

1 m

1

Visible: Gray tones

Lamar_1m_color

Vertical

1m

3

Visible: Red, Green, Blue

Lamar_1m_TM5

Vertical

1

6

Visible (Red, Green, Blue)  & 3 bands of NearIR

Lamar_8m_color

Vertical

8 m

3

Visible: Red, Green, Blue

Lamar_high_oblique

Oblique

~500 m

3

Visible: Red, Green, Blue

 

You will open the images in different viewing windows in ERDAS and compare them to one another.  Note that you must specify that the images are .jpg format for the Viewer window to “find” them.

 

As you answer the questions below, provide a brief summary of:

1)      what information is gained or lost as you use different perspectives:

2)      What information is gained or lost as you use different spatial scales;

3)      what information is gained or lost as you use different spectra to view the landscape; and

4)      what applications each image might be used for.

 


Name 1                                                       Name 2                                            

 

1.  What information is gained or lost as you use different spatial scales?

 

a) Finer resolution (large scale) imagery:

 

 

 

 

 

 

 

b) Coarser resolution (small scale) imagery:      

 

 

 

 

 

 

 

 

2.      What information is gained or lost as you use:

 

a)      Oblique views?

 

 

 

 

 

 

 

b)      vertical perspectives?

 

 

 

 

 


3.  Bring up the 1 m resolution black and white, true color, and 6 band images in three different views.    Visually compare what features appear similar or dissimilar based purely on shades of gray or color.  Then use the spectral profile tool to compare the spectra of two or more features  (e.g., a tree tops, gravel, wood, water) on Lamar_1m_TM5 image (the profiler tool will not work on the other two images, which do not have spectral attribute data files associated with them). In the spaces below, discuss what advantages/disadvantages might occur (e.g., what information is gained or lost)  as you use different spectra to view the landscape 

 

a) Black&White

 

 

 

 

 

 

b) True color:

 

 

 

 

 

 

c) False color infrared (using the Lamar_TM5_1m image, assign band 4 to red, band 3 to green, and band 2 to blue):

 

 

 

 

 

 

 

 

 

4.  Provide examples of how different images could be used:

 

a)      3 and 25 cm, ground-based oblique photos: 

 

 

 

 

 

b)      Airborne black and white, 1 m image.

 

 

 

 

 

c)      True color images, 1 and 8 m resolution.

 

 

 

 

 

d)      6 band image, false color composite, 1 m resolution.

 

 

 

 

 

e)      Oblique satellite imagery at 0.5 km resolution.