IBM has launched a beta version of its Environmental Intelligence (EI) platform, offering application developers and data scientists AI-powered environmental insights, along with access to open-source geospatial and satellite data.
This cloud-based platform provides a wide range of geospatial, weather, and climate APIs, enabling users to build applications that tackle sustainability challenges, climate change, and regulatory requirements. IBM designed the platform to help businesses manage financial risks linked to climate disruptions, which affect both public and private sectors through operational disruptions, asset damage, and supply chain vulnerabilities. With its combination of geospatial data, advanced models, and AI-driven insights, IBM EI aims to support organizations in addressing these critical issues.
“Environmental Intelligence is a new product, but some aspects of it have been years in the making. Our extensive IBM research community of sustainability and climate scientists has been tackling forward-thinking industry and climate-related problems for years,” said David Blanch, director of product management, ESG, and Environmental Intelligence at IBM, in an interview with TechNewsWorld.
Versatile API Suite Powers Environmental Insights
IBM’s EI platform offers an API suite that helps developers and data scientists collect and analyze Earth’s surface data to generate predictive insights and enable proactive decision-making. The platform simplifies the use of public satellite data by processing, normalizing, and organizing it into geospatial layers, ready for analysis and visualization. Through APIs and a Python software development kit (SDK), users can access high-resolution imagery, global weather data, and other critical datasets to take quicker actions. The platform also features a foundation model co-developed with NASA to pre-process and clean geospatial data.
Key features include seamless access to environmental and geospatial datasets via user-friendly APIs for real-time analysis. The platform’s geospatial-temporal querying capabilities, powered by an advanced insights engine, help analyze both spatial and temporal data to enhance application functionality. On-demand historical weather data is available to inform predictive models and optimize operations. The platform also supports advanced querying on environmental datasets, allowing users to tailor spatial and temporal resolutions to their needs.
Additionally, the platform automates greenhouse gas (GHG) emissions calculations for internal and supply chain emissions, enabling users to track and manage their carbon footprints.
The beta version of the platform is available for free, with future pricing and packaging decisions to be made based on market feedback.
Market Trends Reveal New Uses for Climate Data
IBM is targeting technical builders, developers, and data scientists, recognizing trends in how climate change is affecting business operations across various sectors. According to Blanch, these users are not necessarily climate scientists or meteorologists but benefit from innovative climate data provided through APIs and embeddable use cases in their applications.
The platform taps into datasets like high-resolution satellite imagery, updated every five days by European satellites, and meteorological data such as historical records, real-time updates, and short-term forecasts. These datasets support applications ranging from environmental monitoring to regulatory compliance. For example, satellite imagery can be used for monitoring land use changes, while weather data can inform business operations, disaster risk assessments, and sustainability efforts.
Blanch highlighted the challenge of accessing raw satellite imagery, which requires significant processing to remove cloud cover. The EI platform solves this by offering pre-processed and curated data, ready for analysis.
Sustainability Solutions Across Industries
Blanch emphasized that IBM aims to expand the use of the EI platform beyond traditional applications, with success already seen in agriculture, where it supports crop monitoring, yield prediction, and precision farming. The platform is also helping businesses comply with new environmental regulations, such as the European Union’s deforestation rules, which require companies to assess their supply chains and avoid suppliers violating land-use regulations.
One example of EI’s impact is in animal growth and nutrition. Companies have developed predictive models using weather data from the platform to assess mycotoxin levels in crops, which can influence nutrition adjustments. These use cases show how third-party, remote imaging and curated environmental data can improve business operations, without the need for specialized climate expertise.
“The potential for remote imaging and access to curated data is immense. Our goal is to make this data available through easy-to-follow tutorials, samples, and guides, so businesses can seamlessly integrate it into their applications, models, and workflows,” Blanch explained.
Author: shadjavist
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