Keynote Speakers

Ryan Abernathey

Earthmover PBC / Columbia University


Title The Future of Earth-System Data Infrastructure


Responding to the climate crisis requires a coordinated mobilization of academic research, government agencies, and a rapidly growing suite of private companies (broadly described as “climate tech”) aimed at addressing climate change adaptation and mitigation through commercial products and services. At the heart of this work is data: exabytes of data about the earth system, originating from satellites, sensors, and simulations and passing through many stages of processing and refinement as they reach end-user applications.

The growth of AI is fueling an insatiable demand for data across the board while also producing new sources of data, as AI-driven forecasts begin to emerge. Earth system data has many more users and use cases than it did a decade ago. 

 These trends require us to rethink our approach to data infrastructure, which has traditionally emphasized a one-way exchange of data files from a few large data providers to data consumers. My talk will review exciting recent progress in moving towards a cloud-native earth-system-data ecosystem, incorporating lessons from my work on open-source software such as Xarray, Zarr, and Pangeo. I’ll conclude with a vision for how a truly frictionless global data infrastructure can enable a radically more effective response to the climate crisis while also empowering those most impacted by climate change—largely in the developing world—to play a greater role in solutions.

Dr. Thomas Blaschke

University of Salzburg, Department of Geoinformatics – Z_GIS


Title Earth Observation at our fingertips: from science to startup ecosystems


Satellite-based Earth observation (EO) is changing noticeably. The EU/ESA Copernicus programme increases the availability of satellites and advanced sensors. Commercial market sectors from upstream (launchers, hardware) to downstream (data) that utilize established and new data sources from radar, optical, thermal, hyperspectral imaging, and atmospheric monitoring are bourgeoning. 

Open access policy and increasing spatial and temporal resolutions provide unprecedented opportunities to combat grand environmental challenges and enable novel and expanded commercial applications and open new markets for startups and corporates. Additionally, efforts to improve data sharing and collaboration in the form of constellations aim for more coherent EO networks while the development of smaller satellites, such as CubeSats, democratizes access to space, allowing researchers, startups, and educational institutions to conduct EO missions. 

I will report on the integration of artificial intelligence and machine learning into satellite data analysis, enhanced automation of data processing and an increasing startup ecosystem by briefly analysing 1000+ European downstream startups. I conclude that these developments may enable an evolution from scientific research to solutions, and that these advancements may amplify our understanding of the planet's dynamics and may facilitate sustainable development.

Dr. Philippe Ciais

Laboratoire des Sciences du Climat et de l'Environnement


TitleBig data and remote sensing to monitor forests from tree to globe


Dr. Inge Jonckheere

FAO Forestry and Climate Group


TitleHow can big data and AI help protect and sustain ecosystems and the people: way forward


Environmental change has always been a very important research topic to understand our changing planet, but now its importance is more than ever, in the actual climate crisis in which it is clear that we only have a small time window to act in order to reduce the global warming before bringing the temperature to catastrophic heights. Flooding, fires and extreme temperatures make it a real challenge to adapt, both for nature and people.

Ecosystems provide critically important ecosystem services, i.e., the benefits humans derive from ecosystems, which ultimately contribute to overall human well-being.

In this talk, a possible roadmap is laid out in order to discuss pros and cons of the use of big data and AI in the context of environmental change. A state of the art is given and an outlook done to solutions and options to bridge the knowledge gaps in using big data and AI  for the environmental change in order to protect and sustain ecosystems and the people in this very challenging era.