How can scientists model Earth’s complex systems and make sense of measurements from Earth Observation (EO) technology to answer important questions for society? Can they learn from one another’s different ‘fit-for-purpose’ methods? And what can they learn from other domains like design, engineering, art and social science to address complex global challenges?
Recently, an international panel of Earth system scientists and modellers, including collaborators with NCRIS-enabled projects AuScope and TERN discussed these questions in GEO Week 2019 in Canberra.
Multispectral sensors on drones efficiently capture high-resolution images of the remote Palmyra Atoll (with trees coloured in blue) and coral reefs, which help scientists to conduct earth systems research (Image courtesy of USGS)
The group of scientists, who represent geoscience, environmental science and engineering domains, employ different methodologies to address challenges over different time and spatial scales. These include models that explain the state of the natural environment (Earth System Models), models that use artificial intelligence (AI) to quickly categorise geospatial data (Machine Learning Models), and models that use systems thinking to simulate interactions between human and natural systems (Complex System Models).
Panellists (L—R): Dr Rebecca Farrington, Anastasia Wahome, Dr James Cleverly, Dr Sara Morón, Dr Narendra Kumar Tuteja, Dr Robert S. Chen, and As Prof Danielle Wood (Image courtesy of Group on Earth Observations)
Leading the discussion, Assistant Professor Danielle Wood, Director of the Space Enabled Research Group within the MIT Media Lab, explained how her Space Enabled Research Group pursues projects using all three types of models — Earth Systems, Machine Learning and Complex Systems — alongside partners from regions around the world.
The Space Enabled Research Group is pursuing projects to apply satellite-based earth observation technology to support coastal water ecosystem management and urban development in Benin, Ghana, Tanzania and Brazil, in collaboration with local government or university partners.
In their work, the Space Enabled Research Group uses Machine Learning models to categorize the observations of long term historical datasets for important ecosystems such as mangrove forests, in collaboration with partners from NASA Goddard Space Flight Center. They also build Complex Systems Models to analyze how people are influenced by the health of coastal environments and to estimate how human decisions for environmental management, such as preserving mangroves or removing invasive plants, impacts the health of ecosystems.
Danielle and her team have been working to understand deforestation in West Africa, and help governments and non-profit groups find a balance between using mangrove wood for fuel and allowing it to regenerate and support aquaculture in vulnerable communities. Images (L—R) show a mangrove forest, an aerial map of mangroves produced by drone imaging, and a google map highlighting areas of relatively severe deforestation (red) that was produced using AI-coded satellite data (Images courtesy of Danielle Wood)
Taking a complex systems approach to understanding complexly intertwined human and environmental challenges: Danielle and her team propose expanding the interlinked environmental and technology design model to contain two additional components: A human vulnerability and social impact model (social impact can be positive or negative) and a human decision-making model (Image courtesy of Danielle Wood / Jack Reid, Space Enabled, MIT Media Lab). Learn more from this recent publication.
Panellists then presented lightning talks on their work using different modelling methods:
Anastasia Wahome explains her work to support flood vulnerable communities and promote sustainable agricultural water use in Kenya and neighbouring East African nations (Image courtesy of Group on Earth Observations)
To the panellists’ delight, a near-full room of scientists listened closely and asked questions about how ‘shallow’ and deep time interact; what challenges remain to further integrate detailed satellite data
into various models; and how scientists can best advance evidence-based policy.
Dr Sara Morón reflects on challenges for scientists working in deep time:
Snapshots from models of (tectonic plate) subduction zones (left) and paleotopography (right) in Australia using AuScope-enabled Underworld and Badlands software (Images courtesy of Dr Rebecca Farrington (left) and Dr Tristan Salles (right))
Dr James Cleverly reflects on implications for ecosystem scientists and data providers:
Assoc Prof Danielle Wood leads the discussion at GEO Week 2019 (Image courtesy of Group on Earth Observations)
And, to close, Assoc Prof Danielle Wood reflects on technical and policy challenges for the modelling community:
Visit the NEPS website for dates and details: https://science.uq.edu.au/neps
Published in TERN newsletter December 2019 - Produced by Jo Condon (AuScope) and Mark Grant (TERN).