Goal and Objective
This lab is designed to introduce you to a very important image pre-processing exercise known as geometric correction. The lab is structured to develop your skills on the two major types of geometric correction that are normally performed on satellite images as part of the pre-processing activities prior to the extraction of biophysical and socio-cultural information from satellite images.
Methods
In part 1 image to map rectification was used. In part 1 of this lab, we were given a topographic map of the greater Chicago area and a LandSat image of the same area. Our objective was to geometrically correct the topographic map to fit the LandSat image by using ground control points. Ground control points are used to stretch the image or map. Control points have latitude and longitude coordinates to provide a an accurate correction to the image. In part 1, we used first polynomial correction. In first polynomial correction only three GCP's are needed. The rectified image had a root mean square .4379. This is an accepted value because anything under .5 is really good. The second method used was image to image rectification. In the second part we were given a LandSat image of Sierre Leone that needed to be corrected. In part 2, we used third polynomial correction. In third polynomial correction we needed at least 10 ground control points. We used 12 ground control points to get better accuracy. My root mean square error was .1576. This an acceptable value of error for correction.
Results
The first image below is a screen shot of the Root Mean Error and Ground Control Points for the first part of the lab.
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| The image above is a screen shot of the first part of the lab using first order polynomial equation. |
The second part of the lab was Image-to-Image correction. Using a third degree polynomial equation, we placed 12 ground control points to have better accuracy.
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| The image above is of the second part of the lab, where we used a third degree polynomial equation to have better accuracy. |
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