ES 775 Lab 5

GROUND TRUTH
Cheyenne Bottoms, Kansas

James S. Aber


In this exercise, you will work once again with Ikonos imagery from the Nature Conservancy portion of Cheyenne Bottoms, Kansas--see exercise 3. As part of long-term enviromental monitoring, small-format aerial photographs have been taken during the growing seasons (spring, summer, autumn) during a period of several years. The goals of this enterprise are to establish ground truth concerning wetland conditions and to evaluate the effects of Nature Conservancy management practices. The kite and blimp airphotos were acquired from heights of 100-150 m above the ground mostly in oblique views.

Remote sensing research at Cheyenne Bottoms.

Idrisi Taiga has a photo layer capability for linking ground-truth photographs to base maps or satellite images. See Idrisi Tutorial, exercise 1-7, p. 37. Read about photo layer in the Idrisi Help section on digitizing. The objective of this exercise is to create photo layers using an Ikonos panchromatic image as the base.

Exercise

Download the file NC_CB_PAN into your student working folder. This file is derived from the same Ikonos multispectral dataset that you used in exercise 3. The original panchromatic band had 1 meter resolution. The image dataset was windowed to the specific study area of Nature Conservancy marshes, and cell resolution was contracted to 2 meters to reduce file size. Note: even with these reduction steps, the RST file is still >3 MB.

Examine the metadata for details. Now display NC_CB_PAN with the grey palette, no title, and no legend. Hit the "end" key to maximize the display window. You can also "zoom" and move about the image to view details.

1. What parts of the spectrum are included in the pan band?

2. What are the smallest objects or features that you can visually identify in this image?

There are only a few ways to improve the appearance of a single-band, gray-tone image, such as this, namely with the STRETCH module (under Image Processing, Enhancement). Experiment with various stretch options to enhance this panchromatic image. Save your prefered version as the base image for the photo layer.

3. How did you create the enhanced base image?

Ikonos panchromatic stretched sample image of the Nature Conservancy study area. For the photo layer, the "nature trail" site has been used repeatedly over the years for small-format aerial photography. Kansas highway 4 runs across the top of the scene along with a railroad. Click on small image to see a larger version.

SFAP images are selected to represent dry (drought) and wet (flood) conditions. Individual SFAP images are identified and described in the following tables. The approximate view direction (azimuth) is given for each oblique image.

Drought conditions during 2006
Browse image Name
Season 		Azimuth Features
dry01
spring
45°
Dry mudflats and meadows. Delta of
Deception Creek above scene center.
dry02
autumn
50°
Dry mudflats and meadows.
Nature trail, lower right.
dry03
autumn
130°
Dry meadows in foreground.
CBWA in far background.
dry04
spring
140°
Dry mudflats and meadows.
CBWA in far background.
dry05
spring
225°
Dry mudflats and meadows.
Blood Creek in background.
dry06
spring
300°
Dry mudflats and meadows.
Hoisington in far background.
dry07
autumn
315°
Dry mudflats and meadows.
Kite flyers at bottom of view.
Hoisington in far background.
dry08
autumn
360°
Dry mudflats have been plowed.
Tractor is mowing vegetation thatch.

Flood conditions in 2007 & 2008
Browse image Name
Year 		Azimuth Features
wet01
2007
45°
Flooded pools and meadows.
Delta of Deception Creek upper center.
wet02
2008
60°
Flooded pools and meadows.
Delta of Deception Creek upper left.
wet03
2007
90°
Flooded pools and meadows.
Kite flyers at right edge.
wet04
2008
140°
Flooded pools and meadows.
CBWA in far background.
wet05
2007
270°
Flooded pools and meadows.
Blood Creek in left background.
wet06
2007
300°
Flooded pools and meadows.
Hoisington in far background.
wet07
2008
320°
Flooded pools and meadows.
Hoisington in left background.
wet08
2008
360°
Flooded pools and meadows.

Download the SFAP images via FTP into your project working folder. You are now ready to create photo text layers using on-screen digitizing. Read and follow procedures in the Idrisi Help section on digitizing photo layers. Note in particular the procedure for editing or changing existing photo-layer vector files.

You will make two photo text layers--one for drought conditions and the other for flood conditions. First display your stretched Ikonos image in gray tones and maximize the display window (end key). Digitize a point on the nature trail as the position for the text to appear on the Ikonos base map.

Entering the caption can be tricky for multiple photos. It's best to write out the whole caption as a text file, as in the following partial example for the wet (flood) photo layer. Then copy and paste the text into the digitize-options caption box.

Nature Trail <wet01.jpg>{45}<wet02.jpg>{60}<wet03.jpg>{90}<wet04.jpg>{140} ...

In order to activate the photo layer function, click "Feature Properties" button in the Composer window. Now move the cursor to a text label and click to show the associated SFAP images. Examine the SFAP images displayed using each photo layer.

Screenshot of the wet (flood) photo layer displayed on the Ikonos base image. Notice how the small-format aerial photos appear around the nature trail in the appropriate viewing (azimuth) directions. Individual photos can be highlighted, enlarged, or repositioned, as was done for this example.

Notes: You can display only one photo layer at a time on the base image. You must "remove" one photo layer before you can "add" the other. Some of the SFAP images may overlap each other; click on one to move it away or resize it. Unfortunately the composer does not allow saving the complete map composition with the photo layer displayed. The image above was created by taking a digital photograph of the computer monitor.

4. Based on SFAP imagery, describe the appearance of Cheyenne Bottoms under dry conditions. Take note especially of water, vegetation, and soil moisture conditions.

5. Based on SFAP imagery, describe the appearance of Cheyenne Bottoms under wet conditions. Take note especially of water, vegetation, and soil moisture conditions.

Now compare the SFAP images with the panchromatic Ikonos image. In addition, compare these images with the multispectral composites and other images you made in exercise 3 for the same vicinity in Cheyenne Bottoms. The Ikonos dataset was acquired in July 2003 and represents typical low-water conditions in which small pools of water occupy marshes, mudflats are partly moist, and stream channels also contain water. In other words, the Ikonos images depict conditions in between completely dry (drought) and full pools (flood).

Many types of land cover are represented in the SFAP and Ikonos imagery: clean water, muddy water, moist mudflat, dry mudflat, emergent wetland vegetation, wet meadow, dry meadow, etc. The images depict these types of land cover in complicated mosaic patterns that change through time.

6. How effective is the Ikonos dataset for displaying, classifying, and interpreting different kinds of land cover at Cheyenne Bottoms? Explain your answer.

7. How could the effectiveness of Ikonos, Landsat, or other types of satellite imagery be increased for land-cover classification at Cheyenne Bottoms?

8. Explain the usefulness of SFAP for interpreting satellite imagery of land-cover conditions at Cheyenne Bottoms.

As your final task, create a photo-layer composition including the Ikonos panchromatic image (with scale bar) and the dry (drought) photo text layer. Reposition and resize individual photos to provide a good view of each, but without completely covering the Ikonos base image (see example above).

Collect a screenshot of your photo-layer composition. The easiest way to do this is the keyboard "Print Screen" function. Paste the print-screen image into Paint for further processing; crop off unnecessary margins and save an image to turn in.

Turn in

Return to course schedule.
ES 775 © J.S. Aber (2011).