Imagery Method. It is possible to use pixel-based statistics for each ITO in order to identify tree species. Known trees and corresponding ITCs can be used as training sites which will form the unique signatures for each tree species that a classification algorithm will use. The input for each ITC consists of a single multispectral vector, containing signatures for: Mean intensity value The Standard Deviation of this mean Mean-lit value [ave. of all pixels in an ITO that have a pixel value above the mean intensity of all pixels in the object] Tree top value, which is the brightest pixel in the ITO
Appears in 2 contracts
Samples: www.dnr.wa.gov, www.dnr.wa.gov
Imagery Method. It is possible to use pixel-based statistics for each ITO in order to identify tree species. Known trees and corresponding ITCs can be used as training sites which will form the unique signatures for each tree species that a classification algorithm will use. The input for each ITC consists of a single multispectral vector, containing signatures for: • Mean intensity value • The Standard Deviation of this mean • Mean-lit value [ave. of all pixels in an ITO that have a pixel value above the mean intensity of all pixels in the object] • Tree top value, which is the brightest pixel in the ITO
Appears in 2 contracts
Samples: www.dnr.wa.gov, nrsig.org