Next-generation ocean current forecasting to improve maritime safety . This project aims to measure upper ocean currents at scales of 10-100 km in Australia's marine estate using pioneering satellite radar technology. The Surface Water and Ocean Topography (SWOT) mission will map currents at 10 times the resolution of present-day satellites and revolutionise our understanding of ocean dynamics. Expected outcomes include validation of SWOT data in Australian waters and merging this data into Bure ....Next-generation ocean current forecasting to improve maritime safety . This project aims to measure upper ocean currents at scales of 10-100 km in Australia's marine estate using pioneering satellite radar technology. The Surface Water and Ocean Topography (SWOT) mission will map currents at 10 times the resolution of present-day satellites and revolutionise our understanding of ocean dynamics. Expected outcomes include validation of SWOT data in Australian waters and merging this data into Bureau of Meteorology ocean models. Downstream benefits include improved ocean forecasts for maritime safety, search-and-rescue, spill modelling, and marine conservation. At the same time, the project will build sovereign capability in emerging remote sensing technology with a legacy beyond the life of the SWOT mission.Read moreRead less
Early Career Industry Fellowships - Grant ID: IE230100578
Funder
Australian Research Council
Funding Amount
$355,208.00
Summary
Next generation soil carbon satellite-based measurement for carbon markets. Soil carbon sequestration is a federal government priority to offset greenhouse gas emissions. Efforts to advance this opportunity are hindered by the high technical costs of soil carbon quantification. This project will develop an innovative and potentially commercialisable technology that integrates ground data, unmanned aerial vehicles (UAVs), satellites, Eddy covariance CO2 flux towers, soil carbon (C) models, and ar ....Next generation soil carbon satellite-based measurement for carbon markets. Soil carbon sequestration is a federal government priority to offset greenhouse gas emissions. Efforts to advance this opportunity are hindered by the high technical costs of soil carbon quantification. This project will develop an innovative and potentially commercialisable technology that integrates ground data, unmanned aerial vehicles (UAVs), satellites, Eddy covariance CO2 flux towers, soil carbon (C) models, and artificial intelligence (AI) to improve the accuracy of satellite-based soil C modelling. The project will provide an accurate and cost-effective solution to quantification of soil C changes to unlock a large potential of carbon offsets in rangelands in Australia and worldwide.Read moreRead less
Digitally-Integrated Smart Sensing of Diverse Airborne Grass Pollen Sources. Grass pollen is the main outdoor allergen source globally, triggering hayfever and asthma in up to 500 million people. With over 10,000 species, the influence of grass type, location and climate on pollen in the air is not yet known. This is a key issue since subtropical and temperate grasses differ in response to environmental factors. The project aims to use artificial intelligence on digital camera images to learn to ....Digitally-Integrated Smart Sensing of Diverse Airborne Grass Pollen Sources. Grass pollen is the main outdoor allergen source globally, triggering hayfever and asthma in up to 500 million people. With over 10,000 species, the influence of grass type, location and climate on pollen in the air is not yet known. This is a key issue since subtropical and temperate grasses differ in response to environmental factors. The project aims to use artificial intelligence on digital camera images to learn to see local grass flowers and integrate this with air sensors trained to detect grass pollen types. The expected outcomes are new capacities to track airborne grass pollen types. These outcomes can transform how pollen can be monitored to reduce the burden of allergies, and provide evidence of changing airborne pollen loads.
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