Project Description: The primary objective of this project is to classify wildlife targets from high-resolution aerial imagery collected by AMAPPS to the lowest possible taxonomic level (Family, Genus, Species) and identify attributes for each target, when possible, such as age, sex, and behavior. These classifications and attributes will be conducted using an imagery annotation tool developed at USGS-UMESC (CVAT). Importantly, the results of image classification and annotation will provide the foundational elements for developing machine learning algorithms to automate species identification and enumeration.
Lead Principal Investigator: Dr. David Mizrahi, New Jersey Audubon
Partner Institution: New Jersey Audubon
Federal Agency: Bureau of Ocean Energy Management
Federal Agency Technical Contact: Dr. Timothy White
Project Type: Research
Project Discipline: Natural Resources
Project Sub-Discipline(s): Biological (Ecology, Fish, Wildlife, Vegetation, T&E), Water (FW & Marine)
Start Year: 2022
End Year: 2025
Initial Funding Amount: $323,237.74
Federal Grant Number: M23AC00001