S5E01 Down to Earth: Forest Ecosystems

S5E01 Down to Earth: Forest Ecosystems

The Global Carbon Cycle refers to the continuous flow of carbon from the land and water, through the atmosphere and living organisms. Within the cycle there are carbon sinks and carbon emitters. As one of the largest reservoirs of carbon on Earth, forests play a huge role in the global carbon cycle. But how do we know? In this episode, we speak to geoscientist Dr. Ralph Dubayah to explore the applications of GEDI and NISAR in assessing carbon capture in Earth's forests. Dr. Dubayah sheds light on the incredible capabilities of GEDI, a lidar-based instrument on the International Space Station, which measures forest structure in three dimensions, providing precise estimates of biomass and carbon content. He also shares insights into NISAR, a forthcoming joint NASA-ISRO mission that uses synthetic aperture radar to track surface deformation and offer a comprehensive understanding of forest biomass changes. Throughout the episode, Dr. Dubayah showcases exciting discoveries made possible by these technologies, highlighting their potential for revolutionizing our understanding of forest carbon capture and its crucial role in mitigating climate change.

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Episoder(55)

S06E08 Down to Earth: Help or Hindrance? The Ethics of AI-Driven Geoscience

S06E08 Down to Earth: Help or Hindrance? The Ethics of AI-Driven Geoscience

After covering many of the exciting possibilities and potential challenges of AI in Earth Observation (EO), the question still remains: Is AI in EO going to be more of a help, or a hindrance? The answ...

6 Feb 202533min

S06E07 Down to Earth: AI to the Rescue: The Power of Partnership in AI4EO

S06E07 Down to Earth: AI to the Rescue: The Power of Partnership in AI4EO

As the previous episodes have highlighted, collaboration plays an important role when it comes to using AI to solve real-world problems. So how do we work across diverse stakeholders to do this work p...

30 Jan 202534min

S06E06 Down to Earth: Geospatial Foundation Models For Real-World Challenges

S06E06 Down to Earth: Geospatial Foundation Models For Real-World Challenges

Beyond the challenges inherent in using AI in earth observation, there are some incredibly valuable applications for tackling real-world problems. In particular, Geospatial Foundation Models are leadi...

23 Jan 202533min

S06E05 Down to Earth: Training scientists on high performance computing

S06E05 Down to Earth: Training scientists on high performance computing

Unlocking the full potential of scientific research requires more than just cutting-edge technology - it demands skilled scientists who can wield it effectively. In this episode, we delve into the wor...

16 Jan 202532min

S06E04 Down to Earth: Supercomputing and GeoAI

S06E04 Down to Earth: Supercomputing and GeoAI

Now that we have the basics of AI use in the geosciences, the question becomes, how do we use and maximize these tools? Enter the supercomputer! With Dr. Dalton Lunga, Senior R&D Scientist and GeoAI G...

9 Jan 202534min

S06E03 Down to Earth: Revving up AI in Geoscience: The Hardware Revolution

S06E03 Down to Earth: Revving up AI in Geoscience: The Hardware Revolution

When machine learning was first invented, the infrastructure for processing earth observation data was incredibly slow, often taking days or weeks to generate results. But recent breakthroughs in hard...

19 Des 202438min

S06E02 Down to Earth: AI’s Secret Sauce: Quality Data

S06E02 Down to Earth: AI’s Secret Sauce: Quality Data

We’ve heard repeatedly that reliable, validated training data is one of the most important, and also most challenging components of ensuring AI models provide accurate outputs. How are we overcoming t...

12 Des 202435min

S06E01 Down to Earth: Demystifying AI in Geoscience

S06E01 Down to Earth: Demystifying AI in Geoscience

AI is a hot topic these days, but when it comes to geoscience, how is it actually being used? To answer this question, we speak to Dr. Caleb Robinson, Principal Research Scientist, Microsoft AI for Go...

5 Des 202432min

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