IBM Advances Geospatial AI to Address Climate Challenges

30/11/2023

LONDON, UK, Nov 30, 2023 IBM (NYSE: IBM) today announced new efforts that apply its geospatial AI technologies, including IBM's geospatial foundation model developed in collaboration with NASA, to climate efforts including climate resiliency in the United Kingdom (UK); analysis of urban heat islands in the United Arab Emirates (UAE); and reforestation across Kenya.

IBM continues to advance its AI model strategy in part through the creation, training, fine-tuning and open-sourcing of foundation models models that can be used for different tasks and apply information from one situation to another designed for domains beyond natural language, including geospatial applications.

These models, which are trained on geospatial information such as satellite images, present a unique opportunity to address climate change because unlike traditional AI models tailored for specialised tasks, geospatial foundation models encompassing satellite and weather data create knowledge representations from petabytes and exabytes of climate-relevant data that can facilitate accelerated and streamlined discovery of environmental insights and solutions. These models can also be fine-tuned and applied across a multitude of areas driving or revealing climate change, from flood detection to fire scars.

Climate change is a real and pressing issue that we must find new ways to address as quickly and efficiently as possible, including through today's most advanced AI technologies, said Alessandro Curioni, IBM Fellow and Vice President, Accelerated Discovery at IBM. AI foundation models utilising geospatial data can be a game-changer because they allow us to better understand, prepare and address the many climate-related events effecting the health of our planet in a manner and speed never before seen. We are hopeful these technologies can help accelerate the rate at which we derive and apply solutions for a safer and healthier planet for future generations.

Elevating climate resiliency across the United Kingdom

In 2021, IBM and the Science and Technology Facilities Council's (STFC) Hartree Centre collaborated to explore the application of next-generation technologies including AI from IBM to address climate risk and resiliency across the UK.

Now, IBM, STFC and Royal HaskoningDHV, a global consulting engineering company, have collaborated to establish a new service, leveraging IBM's geospatial AI tools, that seeks to automate and scale climate risk assessment processes for organisations. The service's first use case will focus on the aviation sector, in which IBM's geospatial AI will assess impacts weather-related issues, including:

Short-term impact of extreme weather on aviation operations.

Long-term impact of climate change on future airport operations and infrastructure.

In addition, IBM and STFC Hartree Centre, through the Hartree National Centre for Digital Innovation, are advancing a new area of research with Dark Matter Labs and Lucidminds, as part of their TreesAI project. The research project will apply IBM geospatial AI technologies to their Green Urban Scenarios (GUS) model to map urban locations where trees can be planted to help alleviate the risk of surface water flooding. The effort will eventually inform an end-to-end digital planning platform for urban planners, project developers and green urban investors across the UK.

Kate Royse, Director at STFC's Hartree Centre, said: There has never been a more important time to prepare for the challenges posed by climate change, both from an industrial and societal perspective. Here at STFC's Hartree Centre we're excited to be working with IBM and Royal HaskoningDHV, using advanced AI technologies to help the aviation industry prepare for climate risks, and become more resilient against the effects of extreme weather. Equally, our collaboration with IBM and Dark Matter Labs on the TreesAI project through our HNCDI programme will enable smarter decisions based on accurately predicting and managing flood risk, which is critical to all future city planning. Advanced AI technologies are key drivers in enabling us to build a more resilient world against the adverse impacts of climate change.

Djeevan Schiferli, Climate Intelligence Business Strategist, Royal HaskoningDHV said: Operational and strategic planners in every company require a clear understanding of how weather and climate-related incidents affect their business operations. By harnessing AI and geospatial data, we will super charge our climate risk assessments on a global scale.

Chloe Treger, TreesAI UK Lead, said: Over 300,000 properties are at risk of surface-water flooding. Without action, this figure is set to almost double by 2055 due to climate change and urbanisation. Through our collaboration with IBM and STFC, we have been able to observe how trees contribute to reducing surface water flooding risks across the city under different scenarios, using GUS. This has enabled us and our partners to make the business case for tree planting and maintenance. After a successful pilot in Glasgow, we are now looking for further locations to embed this powerful data-enabled decision-making tool.

Analysing urban heat islands in the UAE

By the end of this century, many cities will likely experience disruptive and excessive heat waves if GHG emissions continue at high levels. To develop sustainable and equitable plans to keep cities habitable, the rising heat levels must be accurately mapped and addressed.

IBM and the Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) are pioneering an attempt to apply foundation models to the mapping of urban heat islands areas with significantly higher temperatures compared to surrounding locations. This innovative research specifically applies a fine-tuned version of IBM's geospatial foundati

LINK:	https://uk.newsroom.ibm.com/IBM-Advances-Geospatial-AI-to-Address-Clim...
	See more stories from ibm

IBM Advances Geospatial AI to Address Climate Challenges

More from IBM

06/02/2025

16/01/2025

15/01/2025

06/01/2025

09/12/2024

05/11/2024

04/11/2024

13/08/2024

30/07/2024

09/07/2024

17/06/2024

29/05/2024

23/05/2024

12/05/2024

30/04/2024

25/04/2024

05/04/2024

26/03/2024

21/02/2024

06/02/2024

18/01/2024

10/01/2024

13/12/2023

05/12/2023

30/11/2023

22/11/2023

16/11/2023

08/11/2023

02/11/2023

27/10/2023

18/10/2023

20/09/2023

13/09/2023

17/08/2023

14/08/2023

24/07/2023

20/07/2023

18/07/2023

27/06/2023

21/06/2023

19/05/2023

23/04/2023

17/04/2023

03/04/2023

14/03/2023

01/03/2023

22/02/2023

14/02/2023

09/01/2023

28/11/2022