Environmental impacts of earth observation data in the constellation and cloud computing era

Area of Science:

• Environmental Science
• Remote Sensing
• Computer Science

Background:

• The number of Earth Observation (EO) satellites has grown exponentially, leading to massive data volumes.
• Data storage and processing have largely moved to the cloud, increasing energy and water consumption.
• The environmental impacts of EO data life cycles, including data centers and component manufacturing, are often overlooked.

Purpose of the Study:

• To provide the first assessment of the environmental footprint of the EO data life cycle.
• To estimate the carbon emissions associated with storing and processing EO data.
• To compare the environmental costs of cloud-based versus desktop EO data processing.

Main Methods:

• Estimating the total volume of global EO data collection and its annual increase.
• Calculating CO2 equivalent emissions from data storage.
• Analyzing the carbon footprint of specific EO functions performed on cloud platforms like Google Earth Engine (GEE).

Main Results:

• The global EO data collection is approximately 807 petabytes (PB), increasing by 100 PB annually.
• Data storage generates annual CO2 equivalent emissions of 4,101 tons.
• Cloud-based EO functions, such as band arithmetic on a Landsat 9 scene using GEE, produce measurable CO2e emissions, varying by data center location.

Conclusions:

• The environmental impact of EO data life cycles requires critical consideration by the EO community.
• Increased transparency from EO providers regarding data center locations and their specific environmental impacts is crucial.
• Developing tools to measure the environmental cost of cloud computation for EO is essential for sustainable practices.