The red and green dots represent 30 sample points that were randomly selected in order to check the accuracy of how they were classified in last week's lab. I located them in a way to reduce bias, by creating and locating them in roughly equal proportions according to each classification type. Then, using Street View in Google Maps, I examined each site and recorded whether it was accurate or not, and if it was not, what classification it should have been. Finally, I calculated the % accuracy of the sample points. Because we generalized in making the polygons and classifying them originally, the accuracy was not very high. Sometimes the point landed on a structure that was commercial rather than residential, although overall the polygon seemed to be the correct type. In one case, what had been a sandy area when the photograph was taken had been built up with several houses. What I had thought might have been an academic complex turned out to be several businesses and the Jackson State Fairgrounds. Several areas that seemed forested were actually residential. A closer reading of the classification descriptions also prompted me to change one or two classifications.
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