Remote Sensing
Remote sensing is a useful tool for monitoring and quantifying processes at large temporal and spatial scales. In the BCL, we harness this data to answer a variety of questions at large geographic scales.
With remote sensing, we can access decades of daily observations across the globe, some of which have precision at sub-meter definitions. We employ cloud computing to give us the vast computational power to manage this considerable flow of information.
Desktop methods
– Habitat mapping
– Spatial modelling
– Hydrological modelling
– Environmental assessments
– Carbon stock assessments
Field-based methods
– Drone surveys
– Real-Time Kinematic (RTK) positioning
Case Study: AusDams
Farm dams are a ubiquitous feature of any agricultural landscape and have disproportionally large effects on biodiversity, nutrient cycling, greenhouse gas emissions, and more. Yet their small size and wide dispersal range has made it difficult to study farm dams, hindering our ability to study their influence at a global scale on processes such as greenhouse gas emissions, as well as potential hotspots and gradients across the environment.
To remedy this issue, the Blue Carbon Lab, working in collaboration with the WA Dept. of Primary Industries and Regional Development, generated the first national census of Australian farm dams. We deployed deep-learning models to analyse 7.692 million square kilometers of remote sensing data and three decades of historical records from federal and local authorities. This effort led to the creation of the AusDams.org platform, where the size, location, and water capacity of 1,765,152 farm dams in Australia (11.5% previously undocumented) are now available to stakeholders.
Project partners
Project partners include Corangamite Catchment Management Authority; Southern Cross University; Australian Govt – Dept. of Industry, Science, Energy and Resources; Govt of Western Australia – Department of Primary Industries and Regional Development, Sustainability and Biosecurity.
