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Remote Sensing with Multispectral Scanners

Remote Sensing with Multispectral Scanners. Classification: a closer look. Phoenix classified image. Land Cover map of the Phoenix Area, 1998 Classification by W. Stefanov, ASU School of Geological Sciences.

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Remote Sensing with Multispectral Scanners

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  1. Remote Sensing with Multispectral Scanners Classification: a closer look

  2. Phoenix classified image Land Cover map of the Phoenix Area, 1998 Classification by W. Stefanov, ASU School of Geological Sciences

  3. An image with pixels classified into 6 categories – based on RS data with 2.5-m pixel size

  4. Ground truth • a process in which a pixel on a satellite image is compared to what is there in reality -- in order to verify the contents of the pixel on the image • Goal is to collect information that can be used to improve the accuracy of the classification, or at least to assess the amount & type of error • How could we “ground truth” this image?

  5. Ground truth exercise • Use either GPS, visual alignment with buildings, or distance measuring to find a sampling location • On data sheet, list the 4 pixels’ land covers, as identified by classification • For each pixel, give your best estimate of what is actually on the ground • When done, come back to class – we’ll look at results as a whole

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