Automatic data organization, storage, and analysis of camera trap pictures

  • Jim Sanderson 1. Small Wild Cat Conservation Foundation. 2. Wildlife Conservation Network.
  • Grant Harris US Fish and Wildlife Service


Networks of automatic cameras are producing many thousands of images over modest time periods. For example, 35 cameras at Sevilleta National Wildlife Refuge in New Mexico, USA have produced more than 1.9m useful images since June, 2009. A US Fish and Wildlife monitoring program is producing about 30,000 images per week. Although image file retrieval and storage is trivial, data entry and analysis are both time consuming and error prone since data is most often entered by hand from a keyboard into a spreadsheet. Our objectives were to increase data entry speed while minimizing data entry errors, easily run data analysis, and enable data from multiple locations to be concatenated and analyzed as a single data set. These objectives are achieved by eliminating the task of hand data entry via a keyboard, and managing user interactions with image file data through the use of a suite of open software tools. Error-checking is also automatic. Here we update the methodology described in Harris et al. (2010) by providing a step-by step guide for automatic camera trap data storage and analysis without entering data by hand from a keyboard. This methodology is already in use and is benefiting from an established user community. The programs are available free on

How to Cite
SANDERSON, Jim; HARRIS, Grant. Automatic data organization, storage, and analysis of camera trap pictures. Journal of Indonesian Natural History, [S.l.], v. 1, n. 1, p. 11-19, july 2013. ISSN 2685-5437. Available at: <>. Date accessed: 16 aug. 2022.
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