diaLab7UnsupervisedClassificationInstructions110222

diaLab7UnsupervisedClassificationInstructions110222 - GIS...

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1 GIS 4037c Digital Image Analysis Dr. Charles Roberts Unsupervised Classification In this lab you will be performing an unsupervised classification in ERDAS IMAGINE. The IMAGINE software uses the ISODATA algorithm discussed in lecture. An unsupervised classification is the simplest way to classify spectral signatures because the signatures are automatically created by the algorithm. This is a useful first step in the classification process that can help you get to know your image so that you can set the spectral signatures when we perform supervised classifications in the next weeks. You will submit a screen capture of your evaluated ISODATA image along with a screen capture of your raw data image. Paste your screen captures to a MSWord document. Label above each of your screen captures a title that describes what you have pasted (i.e., your final image analysis). Submit only the one final PDF file via your Blackboard Lab Assignment submission. Name the PDF: lab7UC_(LastNameFirstName).pdf. Note: This is simply your final lab7UC_(LastNameFirstName).doc saved in a PDF format. Also, do not include the parenthesis, „(„ or ‟)‟, in your file name Type your full X: drive file path, which includes „X:‟ and your user folder name, into the “Comments” field of your BB Lab Assignment submission when submitting your final PDF via BB. Be sure to save your original work files to your X: drive
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2 Performing an Unsupervised Classification Step 1 . Open ERDAS IMAGINE, and set your Session Preferences. Step 2.
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This note was uploaded on 03/30/2011 for the course GISC 4037C taught by Professor Roberts during the Spring '10 term at FAU.

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diaLab7UnsupervisedClassificationInstructions110222 - GIS...

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