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In the spring term (duration 13 weeks) the course SATK2 is 
offered. This is more specialized, and is aimed primarily at 
students of mapping sciences. In this course ERDAS is used in 
all the four following exercises: 
Satellite image geometry. 
Determination of terrain elevation from a single 
oblique SPOT scene. 
Special image-processing procedures. 
Colour-hardcopy production, Unsupervised 
classification (clustering) and Field-control 
(collection of ground-truth). 
All the exercises have in common that they are based on 
subsets taken from different types of satellite-scenes in digital 
format. After processing of the initial data-sets by the various 
ERDAS-functions according to the guidelines given in the 
exercise text, the result will be one or more new image files. It 
will often be important to compare two or more images. This 
is obtained by displaying the images on the RGB-screen 
simultanously. In addition to a written description of the work 
carried out during the exercise, the students also deliver a copy 
of the "Result Screen-Images" on a diskette. PIC is useful for 
saving the "Result Screen-Image" as an image file. 
The descriptions of the exercises given below are accompanied 
by illustrations of such "Result Screen-Images”. The 
illustrations in this paper are produced as B/W hard-copies on 
the Tektronix plotter at reduced scale. The quality of these 
illustrations is of course much lower here than on the screen, 
but it is hoped that they will contribute to a better 
understanding of the use of ERDAS in the exercises. 
SATKI. Exercise 1. Digital image processing. 
In this exercise the students get in touch with ERDAS for the 
first time. The aim of the exercise is to familiarize the students 
with ERDAS and with basic concepts and procedures within the 
field of digital image processing. The main emphasis in this 
exercise is on image enhancement methods. 
The initial satellite image is a subset of a panchromatic SPOT 
scene covering the area where the University is located. The 
subset measures 768 lines by 768 pixels. The first step is to 
show the image on the screen using READ. (The file 
containing the statistics for this initial image has already been 
generated). Using CURBOX and SUBSET, a secondary subset 
of 200 x 200 pixels is produced. A -.STA-file is generated by 
BSTATS, and the functions DHISTOEQ, STRETCH and 
DCONVLV are then used to produce enhanced derivatives of 
the original. These images are then compared in the "Result 
Screen-Image" as shown in Figure 1a. CURSES is used for the 
comparison of corresponding pixel-values in the differently 
stretched images. 
  
  
Figure la. Various types of contrast stretch enhancement of a 
panchromatic SPOT subscene. 
In the second part of this exercise, the initial image is a subset 
of a Landsat TM scene. The data-set contains 6 bands, as the 
thermal band with the coarser resolution is removed. For further 
processing, as in the first part, a secondary subset is generated. 
In addition to apply the skill obtained during the first part of 
the exercise, the principal components transform PRINCE is 
used. The "Result Screen-Image" is shown in Figure 1b. Text 
is written by ANNOTAT. 
Figure 1b. False Colour Composite and single band display of 
selected original and principal components Landsat 
TM data.