|U.S. Coast Guard Station on Grand Isle, a barrier island of the Mississippi Delta complex, Louisiana. Kite aerial photo taken prior to Hurricane Katrina © S.W. and J.S. Aber.|
The Landsat archive spans four decades, beginning in the 1970s. This is particularly relevant for documenting the short-term consequences of major disasters: hurricanes, tornadoes, floods, earthquakes, volcanic eruptions, tsunamis, wildfires, etc. It is also quite useful for demonstrating the long-term impacts of human activities, such as deforestation and urban growth, as well as natural phenomena: glacier movement, shrinking pack ice, rising sea level, etc.
Begin by using one (or both) of the USGS search routines (above) to locate a suitable before dataset. Target your initial search for Landsat 4-5 TM datasets (on GloVis under Collections: Landsat Archive). Later you might extend your search to other Landsat datasets. Your goal is to identify two, largely cloud-free scenes depicting your subject before and after a major change took place in land use or cover. To place orders or download scenes, students may need to set up personal accounts with the U.S. Geological Survey. It's simple and free, as part of the online procedure at EarthExplorer or Glovis.
Once you have obtained a dataset file, observe that it is stored in an unusual, compressed format with a "tar.gz" extension. In order to extract this file into its components, special software is necessary. Download and install 7-Zip free shareware. Most students should need the "exe" 32-bit for Windows version (unless you have an unusual computer).
With 7-Zip, extract and decompress the files contained in the dataset. This requires a few steps to accomplish. Using 7-Zip, first "open" the file, which should remove the "gz" extension from the file name. Then "extract" the tar file. Double click on the resulting tar file, which should display the individual file contents. Select all files and "extract" again.
You should obtain several, large individual data files, one for each band (B10, etc.), plus some small metadata files. Once you have extracted these files, you may delete the tar.gz and tar files to save disk space. Each band is a "tif" file, or more specifically, a GeoTiff file. This is a basic image file type with the addition of georeferencing information.
Idrisi Taiga can import these files directly (under File, Import, Government, Landsat). Click GeoTiff as the data type, and enter the B10 file for band 1. All other bands will be added automatically. Click OK and wait for the large files to be imported. A sample image (band 4) should display with default settings, as the import routine continues to convert additional bands.
The downloaded dataset is georectified in the UTM projection, as you should notice upon initial display of the individual bands; check metadata for any band. Whole scenes are generally rotated several degrees clockwise to account for the satellite orbit. This rotation introduces black borders around the actual image. At this stage, the image is much too large for your purpose, and the black border is distracting.
As your next operation, create a small subscene for the particular ground area of interest—see Lake Benton for example. The exact size and shape of the subscene would depend on the particular feature. Locate the Window function (under Reformat). TM/ETM band 4 (near-infrared) has the best distinction between water and active vegetation, so it's often best to begin with this band. Enlarge it and determine row/column (or x/y) values to use for the window of the desired subscene. This may take a some trial windows to achieve one you like. This window, then, may be used as the template for extracting identical windows for the other bands. Create subscenes for bands 1, 2, 3, 4, 5 and 7; you may want to experiment with bands 6 (thermal) and 8 (ETM pan) also.
Having created a suitable subscene of the before dataset, follow the same procedure for the after dataset. You should end up with identical subscenes depicting two points in time. Make sure the two subscenes have exactly the same dimensions (rows and columns) and UTM positions. Now process various single-band and/or color-composite images for the before-and-after datasets. Select the image type that best displays the changed conditions, and save jpeg versions for part B of the exercise.
As an example, go to the Mississippi Delta webpage. Use the web browser to view the "page source" in order to see the actual html text/code. Students may copy and modify this html file as necessary to display your images. Following is the basic script format for displaying the before-and-after imagery:
Return to course schedule.
ES 775 © J.S. Aber (2013).