Load the required libraries, then read in the deployment data CSV, and create a data frame with a column that contains the full path to the image and video files for each deployment. The key features of the file are: (1) the deployment ID, which matches the directory name where the image and video files live, and (2) the coordinates and elevation, obtained from an image of the deployment site taken on an iPhone, which will be used to create the missing GPS metadata for the trail camera files.Īlright, let’s get into the R code. The deployments.csv file looks like this: camera_id,deployment_id,latitude,longitude,elevationĮxcept that ‘XX’ is a decimal value in the real file – I’m not going to publish the locations of my cameras. Within each deployment directory are the image and video files retrieved from the camera. A deployment basically describes the placement and location of the camera and has an ID, corresponding to the directory name. Under the cameras directory is a directory for each camera and in those directories, a directory for each deployment. There’s an R script – more of that later, and a CSV file in the data directory – more of that later too. Here’s how I did it.įirst, I create a directory, ~/Documents/Campark85, containing files and directories that look like this: With a little research, I found a way to add this information to the images later using R and some additional software named exiftool. There is no GPS in the camera of course, but the EXIF data does not include the date/time of the image, nor the camera make. Unfortunately, images retrieved in this way have one major flaw: an almost-complete absence of metadata. One useful feature is the ability to transfer images and video to a phone wirelessly (albeit through a rather clunky phone app). The camera model I chose is the Campark T85 which for me, had the right combination of features and price point.

Exiftool metadata