Making Planetary SETI Respectable

Over the decades, the SETI community has been successful in distinguishing itself from the fringe. Even scientific critics of SETI generally acknowledge that it is a a valid scientific enterprise and not fringe or pseudoscience. Planetary SETI, or SETI in the solar system, on the other hand has been significantly less successful in this regard.

There are figures within the emerging planetary SETI community who have been able to distinguish themselves from the fringe, such as Jason Wright in his 2017 paper arguing for the merit of a search for planetary technosignatures, but a cursory review of self-described planetary SETI organizations reveals little attempt to distinguish itself from the fringe. The now debunked face on Mars doesn’t help…

The key to making planetary SETI respectable is developing a robust set of tools that can be used for rigorous research and collect high quality data which could actually rule out hypotheses, as was eventually done with the face on Mars when higher resolution imagery revealed it to be a natural feature. What if we are already had tools that were being actively used in archaeology which could be readily applied to planetary science contexts which could answer both SETI related research questions and questions of more general interest to the planetary science community?

For several decades now, archaeologists have used photogrammetry to search for hidden archaeological sites that were previously not apparent in the field. Photogrammetry is simply creating a 3-D structure based on multiple 2-D images using the principle of stereographic projection. Using this method, archaeologist have been able to more accurately reconstruct ancient structures, such as temples in ancient Greece. The photogrammetry based on aerial photographs or satellite imagery is most analogous to the remote sensing approaches of planetary science.

In recent years, archaeologists have also employed machine learning and deep learning to identify archaeological sites. A recent example of artificial intelligence advancing archaeological surveying is the use of AI models to help identify new Nazca figures in the Atacama Desert.

Photogrammetry and AI models certainly have value in planetary science. Reconstructing 3-D models of surface features would help to interpret geologic structures that could tell us about the history of planetary surfaces, like proposed rock glaciers on Mars and possible cryovolcanic domes on icy moons and dwarf planets. Machine learning would certainly be helpful in dating planetary surfaces based on crater counting as it can accelerate crater counting.

And of course, more detailed reconstruction of features identified on planetary surfaces could also be used to determine the nature of anomalous features, which could be of interest to a planetary SETI search. Based on our sample of 1, reasonable assumptions could be made that spacefaring civilizations would make structures similar to structures made by humans, such as solar panels. After all, they will likely need to power their technology. Anomalous features could be detected using a method not drastically different from methods used by space archaeologists to detect hidden archaeological sites under the canopy of the Amazon rainforest.

It should be made clear that just because a feature is anomalous or cannot be positiely identified as a natural feature does not mean that it is an artificial structure built by a non-terrestrial intelligence. The ability to characterize anomalous structures would still be valuable to planetary exploration even if they turn out to be completely natural.

We have found no evidence of non-terrestrial intelligence in our solar system, and the odds of finding evidence in the solar system are low, but just like interstellar SETI, we will not really know unless we do an actual search. Such a search using remote sensing methods already used in terrestrial archaeology would allow for a search that is productive and produces interesting testable results rather than endless, often counter-productive speculation.

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