Access to the latest climate data remains a significant challenge in climate science where environmental conditions change almost daily, making it difficult to detect and mitigate the impact of climate change on consumers, governments, investors and businesses.
The geospatial analytics capabilities within the IBM® Environmental Intelligence Suite offer a store of geospatial temporal data used by an analytics engine for conducting complex and efficient queries to reveal relationships between layers of data.
The new Geospatial Foundation Model offers AI-driven geospatial solutions. Powered by NASA's Harmonized Landsat Sentinel-2 data, this remote-sensing spatial data helps to ensure precise asset damage verification and protection across vast terrains. The foundation model’s uniqueness lies in its adaptability, accuracy, self-supervised learning abilities and its reliance on a blend of high-resolution satellite imagery and LiDAR for predictive insights.
Built from IBM’s collaboration with NASA, the model is designed to convert satellite data into high-resolution maps to reveal our planet’s past and hint at its future.
The Geospatial Foundation Model is pre-trained on an extensive portfolio of remote-sensing data, allowing you to direct your efforts towards fine-tuning and seamless inference.
Effortlessly save time and resource allocation without compromising precision. Designed to achieve task-specific geospatial AI model creation, such as flood mapping and biomass estimation, with just half of the labeled data typically required.
Tailor and fine-tune models to align with specific business requirements. The IBM geospatial AI capabilities offer customized solutions that seamlessly adapt to a wide range of specific business use cases.
The Geospatial AI capability is designed for massive geospatial-temporal query and analytics services, freeing your team from cumbersome processes and providing access to valuable insights. The Geospatial Foundation Model offers advanced features by leveraging NASA's robust Earth-satellite datasets in sophisticated self-training mechanisms, ensuring precision and adaptability in environmental analysis.
Widening access to NASA earth science data can be used for geospatial intelligence and accelerate climate-related discoveries through spatial analysis.
Hendrik Hamann, chief science officer for climate and sustainability at IBM Research, explains how foundation models can help us measure, mitigate and adapt to a changing climate.
Built from IBM’s geospatial technology collaboration with NASA, the IBM® watsonx.ai™ model can help reveal our planet’s past and hint at its future.
Geospatial data plays a key role in protecting wildlife, creating a healthier planet and a more resilient economy.
Geospatial data can provide insights into relationships between variables and reveal patterns and trends.
Weather-decision technologies built with advanced analytics help you better predict how and when weather will affect your business.
Combined geospatial, GHG emissions and industry-specific data delivers accurate, actionable information about your complete environment.
A robust catalog of cloud-based, industry-standard APIs provides accurate and precise hyperlocal weather data and imagery.
A modeling framework and application builder enables you to customize climate adaptation solutions that fit your business needs.
Interested in learning more about how the Environmental Intelligence Suite can help you forecast and mitigate extreme weather events? Explore features in a free trial or request your personalized Environmental Intelligence Suite demo.