Simplifying the process of refining geospatial models

Spread the love



IBM Research and NASA have collaborated to develop geospatial base models for analyzing Earth’s climate change and its impacts, with the Prithvi series being a popular choice among researchers and educators worldwide. IBM Research recently introduced the Time and Weather model, which features a flexible architecture suitable for various applications, such as personalized energy forecasting for wind farms.

The ability of these models to automate tasks and visualize complex data could revolutionize industries such as energy management, supply chain logistics, and disaster response. However, customizing these models for specific applications often requires fine-tuning, a process that traditionally involves data curation, model training, and integration of multiple data sources.

To streamline the fine-tuning process, IBM Research developed the Geospatial Studio, a cloud-native toolset that guides users through data preparation, model tuning, and deployment. The Studio is built on the Earthly Torch framework, allowing users to experiment with geospatial models at different levels of abstraction. It simplifies tasks such as image segmentation and per-pixel regression, while also offering tools for optimizing model hyperparameters.

The Studio’s graphical interface enables users to visualize model results and track the training process, ensuring accuracy and performance optimization. Additionally, the Studio houses open source models from IBM, NASA, and other research institutions, making cutting-edge geospatial models accessible to a wider audience.

Overall, the development of advanced geospatial base models represents a significant step forward in AI applications for Earth’s climate and weather. With the potential to revolutionize industries and empower researchers, these models offer a promising future for tackling complex environmental challenges.

Article Source
https://research.ibm.com/blog/img-geospatial-studio-think