The Landcare Led Bushfire Recovery Grants Program, which is supported by the Australian Government’s Bushfire Recovery Program for Wildlife and their Habitat, provided funding for the establishment of a drone monitoring network for wildlife enabled by artificial intelligence (AI). The drone monitoring network is led by Queensland University of Technology (QUT) in conjunction with major partners Noosa & District Landcare and Watergum Community Inc. The project will develop the capacity of existing Landcare and other community groups to conduct drone surveys for wildlife detection, and create an AI powered hub for remote, rapid analysis of the wildlife monitoring data that is collected.A key activity of the project was to conduct an initi...
The active collection of wildlife sighting data by trained observers is expensive, restricted to sma...
Biodiversity loss and sparse observational data mean that critical conservation decisions may be bas...
Biodiversity loss and sparse observational data mean that critical conservation decisions may be bas...
The Environment Restoration Fund – Threatened Species Strategy Action Plan – Priority Species Grants...
Noosa Council has partnered with Queensland University of Technology (QUT) to establish a koala moni...
Noosa Council is seeking to establish a reliable baseline and monitoring program for koala distribut...
In this thesis a new method for monitoring wildlife using drones and machine learning was developed ...
Koalas (Phascolarctos cinereus) are cryptic and currently face regional extinction. The direct detec...
Koalas (Phascolarctos cinereus) are cryptic and currently face regional extinction. The direct detec...
Effective management of threatened and invasive species requires regular and reliable population est...
Effective wildlife management relies on the accurate and precise detection of individual animals. Th...
Cost-effective surveys of low density koala populations are challenging, but technological developme...
Drones and machine learning-based automated detection methods are being used by ecologists to conduc...
Forests on private land have a wide range of uses that span activities such as recreation, primary p...
Abstract Context Drones, or remotely piloted aircraft systems, equipped with thermal imaging tech...
The active collection of wildlife sighting data by trained observers is expensive, restricted to sma...
Biodiversity loss and sparse observational data mean that critical conservation decisions may be bas...
Biodiversity loss and sparse observational data mean that critical conservation decisions may be bas...
The Environment Restoration Fund – Threatened Species Strategy Action Plan – Priority Species Grants...
Noosa Council has partnered with Queensland University of Technology (QUT) to establish a koala moni...
Noosa Council is seeking to establish a reliable baseline and monitoring program for koala distribut...
In this thesis a new method for monitoring wildlife using drones and machine learning was developed ...
Koalas (Phascolarctos cinereus) are cryptic and currently face regional extinction. The direct detec...
Koalas (Phascolarctos cinereus) are cryptic and currently face regional extinction. The direct detec...
Effective management of threatened and invasive species requires regular and reliable population est...
Effective wildlife management relies on the accurate and precise detection of individual animals. Th...
Cost-effective surveys of low density koala populations are challenging, but technological developme...
Drones and machine learning-based automated detection methods are being used by ecologists to conduc...
Forests on private land have a wide range of uses that span activities such as recreation, primary p...
Abstract Context Drones, or remotely piloted aircraft systems, equipped with thermal imaging tech...
The active collection of wildlife sighting data by trained observers is expensive, restricted to sma...
Biodiversity loss and sparse observational data mean that critical conservation decisions may be bas...
Biodiversity loss and sparse observational data mean that critical conservation decisions may be bas...