Key Takeaway
Advancements in Earth observation (EO) are transforming climate intelligence through enhanced satellite and AI integration. EO relies on satellite remote sensing to collect crucial data, with over half of essential climate variables measurable only from space. By 2032, the sector is projected to generate over two exabytes of data. Technological improvements are overcoming past limitations, as modern satellite sensors provide more detailed observations, and AI/ML platforms process vast datasets in near real-time. These advancements enable rapid climate insights, with machine learning models delivering predictions up to 1,000 times faster than previous methods, making EO more accessible to various organizations.
Advancements in Satellite and AI Integration
Earth observation (EO) entails gathering and analyzing data about the planet’s systems, primarily through satellite remote sensing.
Over half of all critical climate variables can only be measured from space, positioning EO at the core of climate intelligence.
The sector is projected to produce more than two exabytes of data by 2032.
Historically, the utilization of this data was hindered by slow processing speeds and limited accessibility.
Technological advancements are eliminating these obstacles, with improved satellite sensors offering more detailed and frequent observations.
Modern AI and machine learning platforms can now analyze these vast datasets in near real-time, transforming raw satellite images into climate insights within minutes.
Machine learning models can provide predictions up to 1,000 times faster than previous techniques.
The emergence of smaller satellites also allows more organizations, including SMEs, to access and deploy their own systems.
Leave a Comment