5.1.1 Sampling Design
A remote camera can be deployed at a location for a short or long period of time. One or several units can be deployed at a single location for years, swapping out the batteries and SD cards every 6 months to a year, or the unit(s) can be moved to a new location after a predefined sampling period has lapsed, depending on the research question and intended data use. This flexibility provides great benefit to a user or researcher, as the only limitation to data collection is storage space and battery life. Depending on the length of time these units will be in the field prior to being serviced, camera settings can be changed to optimize battery life. When developing a remote camera sampling design for questions related to density estimation, relative abundance, occupancy modeling, etc., strong considerations should be made regarding the length of time in the field, number of units to install and the distance between units. Resources on camera deployment methods, sampling protocols and analytical approaches can be found in the Resources
5.1.2 Artificial intelligence
The use of remote cameras can lead to the capture of hundreds, thousands or even hundreds of thousands of images in a single set. The large set of data collected is a benefit to the user, however it is also usually the bottleneck to the production of meaningful data in a timely manner. Processing time by humans to go through each image and assess if an animal is present can be incredibly time consuming and inefficient. To minimize the number of images a tagger must view and tag, WildTrax project administrators can choose to implement the following 2 methods in their project settings:
- Computer AI in the form of the Microsoft Megadetector. This AI detects images with nothing, humans, vehicles, cattle, and animals. Only those images with an animal are presented to the tagger to tag. Please note, it won’t identify the animal species for you, it’ll just tell you what images have them. This can reduce the number of images for processing significantly.
- Auto-tagging staff setup images.
5.1.3 Tagging protocol
Tagging images inWildTrax is relatively flexible in that the user can be as general or as detailed as your question requires. Tagging currently entails the application of one or more tags, composed of a species, sex, age and number of individuals, to each image. In the future, WildTrax will allow for the application of additional tags such as coat colour, snow depth, etc.
A task in WildTrax is a unique combination of an image set and an observer, in this case, a WildTrax project member. WildTrax currently has the ability to process images with a single tagging method defined by project settings.
The filters the default view to only tasks assigned to you. You can toggle to view all tasks in a project like this: .
5.1.5 Recommend equipment
The following equipment is recommended for processing camera image data. Proper equipment will enhance your experience and data quality using WildTrax.
Contact WildTrax Info if you have any questions.