Poster Number 824
See more from this Division: A11 BiometrySee more from this Session: General Biometry: II
Monday, November 1, 2010
Long Beach Convention Center, Exhibit Hall BC, Lower Level
Supervised classification for estimating ground cover helps streamline the process of digital image analysis and removes user bias. This is especially true when large numbers of samples are taken. However software to conduct such classification may be expensive as well as limited to only a few type of analysis. To overcome this problem the authors have developed methods to create training, apply different classification strategies to batches of images, and cross validated these strategies using ArcMap and R.
See more from this Division: A11 BiometrySee more from this Session: General Biometry: II
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