9MinDistPowerpnts

9MinDistPowerpnts - – Many clusters small cluster...

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Review of the Supervised Classification Process Appropriate classificaiton scheme adopted Training fields that represent all classes of spectral information selected – Nearly homogeneous in tone – Typical, not unusual examples of land-cover – Number of pixels in training field should be 10 x the number of bands – Consideration of temporal and spatial considerations
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Review, Continued Statistics from training fields extracted and analyzed Appropriate classification method chosen Image classified Accuracy Assessment – Spatial sample – Ground truthing – Accuracy asessment – Analysis of Structure of errors – Reclassify: Second iteration
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Ideal sequence for Training Field Selection Assemble ancillary data – DRG, DOQQ, county hwy maps – Examine image, find landmark features Unusual spectral signatures Typical spectral signatures Unsupervised to determine broad spectral areas – Many clusters, small cluster radiuses, etc.
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