Automatic Storage and Analysis of Camera Trap Data

The invention of the camera trap by George Shiras in the late 1890s and its widespread adoption by hunters 100 years later has armed scientists and managers with a powerful noninvasive tool to collect data on wildlife (Sanderson and Trolle 2005). Imagery from camera traps supports ecological investigations, inventory and monitoring networks, and cataloging biodiversity (e.g., Karanth and Nichols 1998, MacKenzie et al. 2005, Trolle et al. 2007, Stein et al. 2008). Such use of camera traps continues to expand in the number of cameras deployed and images taken (Kays and Slauson 2008, Kays et al. 2009). Yet this increase creates a paradox. While practitioners seek more data to improve analyses, they buckle under mounds of imagery piling up before them. This situation engenders four problems. First, because cataloging imagery is slow, image identification lags behind acquisition, and many images remain unidentified. Second, user entry is tedious, causing errors (Maydanchik 2007). Third, inconsistent filing and naming conventions complicate data retrieval and sharing (Chaudhary et al. 2010). Fourth, the struggle to keep pace with the acquisition and management of data from existing camera traps slows the deployment of additional cameras (and subsequent data acquisition).