In 1972, the crew of Apollo 17 captured what has become one of the most iconic images of the Earth: the Blue Marble. Biochemist Gregory Petsko described the image as “perfectly representing the human condition of living on an island in the universe.” Many researchers now credit the image as marking the beginning of environmental activism in the U.S.
Satellite images are part of the big data revolution. These images are captured through remote sensing technologies – like drones, aerial photographs and satellite sensors – without physical contact or firsthand experience. Algorithms refine these data to describe places and phenomena on the Earth’s surface and in the atmosphere.
As a geographer, I work with geospatial data, including satellite images. This imagery offers a powerful way to understand our world.
But I think it’s important for people to understand the limitations of this technology, lest they misunderstand what they see.
But there are some caveats that anyone working with satellite images – or viewing them – should consider.
Satellite images are only as good as their resolution. The smaller the pixel size, the sharper the image. But even high-resolution images need to be validated on the ground to ensure the trustworthiness of the interpretation. Should we question the images we see? Whose view of the world are we seeing?
What’s more, processing satellite images is computationally intensive. At best, satellite images are interpretations of conditions on Earth – a “snapshot” derived from algorithms that calculate how the raw data are defined and visualized.
This has created a “black box,” making it difficult to know when or why the algorithm gets it wrong.
As satellite images become more ubiquitous, we should reflect on where they come from, how they are created, and the purpose for their use.