One of the major challenges encountered by state and federal natural resource management agencies is the lack of information on the occupancy, distribution and population trends of species of concern, many of which are cryptic, small bodied, and idiosyncratic in habitat selection over large extents of remote areas. And yet these same species are the most threatened due to the rapidly changing environmental conditions they are facing across space and time. At the same time, there is an equally urgent need to obtain information on feral and pest species that are contributing to the threat to Australia’s native wildlife.
Conventional monitoring of small mammal species typically involves the use of VHF radio collaring and telemetry. The current application of VHF tracking systems is time consuming, labour intensive and expensive due to the manpower needs of covering extensive, remote and inaccessible terrains. Additionally, low animal recapture rate often necessitates repeated surveys, further compounding the data limitation problem and high research costs. Although GPS collars are available, they are typically not suitable for small wildlife species due to their size and weight, short lifespan, and limited signal penetration power.
In this project, we seek to combine VHF telemetry, tracking technologies and drone platforms to develop an integrated wildlife intelligence and monitoring system that is low-cost, user friendly and easily deployable.
This research is a collaboration between the Auto-ID Lab and URAF at the University of Adelaide. The project is supported by the Department of Environment, Water and Natural Resources (DEWNR).
Link to code at GitHub: https://github.com/AdelaideAuto-IDLab/TrackerBots