AirborneLogic Pty Ltd

AirborneLogic utilizes hyperspectral imagery and other data to assist farmers, private companies and government agencies in uncovering environmentally sustainable solutions for efficient water use. Using machine learning and contemporary data analytics, AirborneLogic’s team of industry experts provides our clients with advice to minimize water use and discover innovative environmental solutions. Our drone-mounted hyperspectral and infra-red sensors afford us a unique perspective on water infrastructure, crops and natural vegetation. Data from these sensors is analyzed and combined with information from satellites and other sources to produce actionable advice for farmers and others working in agriculture and the natural resources industries.

Organisational Capability

AirborneLogic utilizes hyperspectral imagery and other data to assist farmers, private companies and government agencies in uncovering environmentally sustainable solutions for efficient water use. Using machine learning and contemporary data analytics, AirborneLogic’s team of industry experts provides our clients with advice to minimize water use and discover innovative environmental solutions. Our drone-mounted hyperspectral and infra-red sensors afford us a unique perspective on water infrastructure, crops and natural vegetation. Data from these sensors is analyzed and combined with information from satellites and other sources to produce actionable advice for farmers and others working in agriculture and the natural resources industries.

Projects

Remote Sensing for Biosecurity Surveillance in Urban and Peri-Urban Environments
The project investigated the benefit of applying machine learning to remote sensing data to improve the surveillance of potential disease-host trees in urban environments. The ground truth data set used was from an outbreak of Citrus Canker in the Northern Territory where hundreds of trees were monitored and their GPS locations recorded. The remote sensing imagery included • Multispectral Satellite • RGB & Multispectral Aircraft • Hyperspectral Helicopter Machine learning methods investigated included • Semantic segmentation using a fully convolutional neural network • Bounding box detection using a convolutional neural network • Object classification using Random Forests, SVM and XGBoost
Remote sensing of water stress in grape vines
Working with a range of Australia's leading wineries, AirbonreLogic has been helping vineyard managers determine water stress in vineyard before it is visible to the human eye and assisting in reduction of water needs
Discrimination of canopy area dn species using remote sensing
Working with Greening Australia the AirborneLogic team has been investigating the use of remote sensing techniques to rapidly assess carbon biodiverse planting canopy area and species success
Pasture biomass assessments
Working with graziers to develop technology assesment approaches to biomass assessment to assist grazing cell rotation.
Almond tree water stress
Developing a rapid assessment technique using drone imagery to assess water stress on almond trees and orchards.
Using tree detection AI and machine learning methods we assisted Council's to understand the canopy area of street trees and plantable space for new trees as a method to achieving cooler streets - a climate change adaptation approach.