According to the World Economic Forum’s 2021 Global Risks Report, climate action failure, and extreme weather events represent the two most likely risks facing our planet. Climate change is already here, and organizations around the globe are recognizing the need to understand their climate risks to plan for the future. Investors are increasingly calling for climate-risk reporting, as part of ESG requirements or as outlined by initiatives like the TCFD and SASB.
Detailed physical climate risk assessments are expensive, time-intensive tasks. Regional-scale studies are rare, and the results are typically delivered as reports written using technical jargon, along with static maps. These risks must be understood so that they can be accurately evaluated and reported, or mitigation measures put in place. For this reason, we created GAIA, Minerva’s Climate Risk application.
Simply put, GAIA helps users identify high-risk assets, so they can plan for the future. GAIA is an AI-assisted application that reasons with numerous complex datasets, enabling users to understand their physical climate risk over wide areas. Our cognitive AI system mimics human-expert reasoning, and provides explainable assessments, making it easy for non-experts to understand the results.
Minerva has successfully produced landslide susceptibility maps for British Columbia, Canada and Veneto, Italy. The Veneto project recently won the “INSPIRE Helsinki 2019 Data Challenge” for the most innovative practical use of spatial data in the domains of sea, weather and cities. Applications for wildfires and floods are currently in development.
Minerva has developed unique AI-powered interactive webmaps for our GAIA Climate Change AI Suite. Our applications help users identify various climate risk factors so they can be dealt with before they become disasters.
A cognitive AI system that mimics expert reasoning to identify and explain high-risk assets
Case Study: Sea to Sky Highway, British Columbia, Canada
The Sea to Sky corridor north of Vancouver, British Columbia, Canada is a mountainous area that is prone to many types of landslides, ranging from minor soil slides that cause highway delays to devastating rock avalanches that wipe out wide swaths of forest. The highly variable landscape means that every slope must be evaluated against each type of landslide, based on its individual characteristics.
Mimicking the traditional process that professional geologists use to evaluate slopes, landslide susceptibility maps displayed on the user interface represent a new means of interrogating hazard data. The map is updated daily, accounts for local weather forecasts, and is an effective screening tool to evaluate the relative susceptibility of slopes to various types of landslides.
Case Study: Veneto, Italy
INSPIRE is a legislated directive in the EU that guides member states on the standardization spatial data. The 2019 Helsinki Data Challenge called for innovative and valuable applications of INSPIRE-aligned geospatial data. The challenge was to showcase how INSPIRE provides a framework to conduct complex geospatial data processing in a scalable and interoperable format.
We deployed the GAIA landslide solution and developed an interactive web-map application that assesses landslide susceptibility and hazard in the province of Veneto, Italy. We compared over 80,000 slopes and almost 10,000 creeks to three different expert-based landslide models, demonstrating how INSPIRE-aligned data can be leveraged for scalable AI applications.
Nathaniel Tougas, P. Eng.
“By using Minerva’s cognitive AI to identify relationships between various geomorphological parameters, we can essentially get an unbiased second opinion to augment our own geohazard assessment. The GAIA Landslide Map provides geological engineers with AI tools and insights that have never been available in our field, and this is truly exciting to me.”
“Minerva’s synergy of AI with the fruits of Earth science research is not limited to mineral exploration… its AI is powerfully applying geotechnical knowledge to natural hazards avoidance and risk management faster than is possible with humans alone. The results are transparent to stake-holders.”
“Minerva Intelligence provides knowledge for engineering, services and applications based on advanced AI. Through a semantic approach, they explain complex physical models to scientists, practitioners and non-experts.”
“The SLRD Emergency Program relies on quality hazard information to make informed decisions for public safety and Minerva Intelligence contributes to the field of innovative professionals.”
Brent Ward, P. Geo.
“Minerva is bringing cutting-edge technology to natural hazard management.”
John J. Clague
“Minerva Intelligence is bringing the power of artificial intelligence to geology. Their AI approach can help bridge the gap between scientists and decision-makers in fostering disaster risk reduction and emergency management.”
”Minerva Intelligence leverages standards and interoperable data to foster disaster risk reduction… an absolute game-changer in emergency management!”
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