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2011 Sheldon M Ross Stochastic Process 2nd Edition Solution Manual
the following 10 metrics are used to compare a kappa map with a ground truth map. for each location in the true kappa map, a circle is drawn at the center of the tile containing that location. if the ground truth map contains a species, it is assigned a value of 1 to this kappa feature. if the ground truth map does not contain a species, the corresponding kappa feature is assigned a value of 0. if no species are present in the ground truth map, all kappa features are assigned a value of 0. all other kappa features are assigned a value of -1. the kappa metric is then calculated as the sum of kappa features minus the sum of (kappa features)*0. all of these features are well-defined and can be used to compare the performance of the lidar-based and acoustic monitoring techniques.
the following 10 metrics are used to compare the species maps generated by the acoustic and lidar techniques. for each species, if the ground truth map contains a pixel with that species present, we assign a value of 1 to this species location. if the ground truth map does not contain any pixels with that species, the corresponding species location is assigned a value of 0. for all other species, the species location is assigned a value of 0.
the species accuracy metric is the number of species locations in the ground truth map where the species is correctly predicted. this metric does not take into account if the species is present in the lidar-based or acoustic monitoring techniques.
the false alarms metric is the number of species locations per pixel predicted by the correct process, but not in the ground truth species map. this metric includes both false positives (a species is predicted where a species is not present) and false negatives (a species is not predicted where a species is present).
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