Machine Learning from Space

by Vas Mylko

Recently we have engineered features for a new ML module for Curiosio, and one of the features was elevation. The elevation of a geographic location is its height above or below a mathematical model of the Earth’s sea level. The task sounded as easy as writing a “Hello World” in unknown programming language.

Hello World

I prepared a list of ~70 manually sampled locations, and started to pull their elevations from the OSM, Wikidata, and Wikipedia. Almost instantly I noticed diversity how/where the elevation data was present. It resembled me the diversity of the naming the basic things in different spoken languages (e.g. dog, rain, food) because they evolved independently. Elevation was present under different names and forms in them all, but in most cases it was absent at all:

I decided to link more data sets, so looked in the GeoNames. Elevation was supposed to be there, it was there, but not for all locations from the sampled list:

Here I felt that this mission was not even close to the “Hello World” by complexity and notified Roman about potential surprises with the elevation data point… He found the data. What to do in such situations? Raise abstraction level. How high? Until it starts working for our problem. So we have raised the bar by ~240 kilometers (150 miles) above the Earth to Space.

Space Tech

The Shuttle Radar Topography Mission (SRTM) was an international project spearheaded by the National Imagery and Mapping Agency and NASA, with participation of the German Aerospace Center DLR. Its objective was to obtain the most complete high-resolution digital topographic database of the Earth. SRTM consisted of a specially modified radar system that flew onboard Endeavour during its 11-day mission in February 2000. This radar system gathered around 8 terabytes of data to produce high-quality 3D images of the Earth’s surface.

60-meter mast (by NASA)

To acquire topographic data, the SRTM payload was outfitted with two radar antennas. One antenna was located in the Shuttle’s payload bay, the other on the end of a 60-meter (200-foot) mast that extended from the payload bay once the Shuttle was in space. SRTM mission covered approximately 80% of the Earth’s surface (71% of Earth’s surface is water-covered), with a global resolution of 90 meters, and a resolution of 30 meters over the USA.

STS-99 Space Shuttle Mission Crew

Terra (EOS AM-1) multi-national NASA scientific research satellite was launched in 1999. It is the flagship of the Earth Observing System (EOS). It is equipped with the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) - a Japanese sensor which is one of five remote sensory devices on board. It has been collecting data since February 2000. ASTER Global Digital Elevation Model (GDEM) data of good quality was released in October 2011 as v2, better than SRTM over rugged mountainous terrain.

On September 2014 NASA released improved version of SRTM. Previously, SRTM data for regions outside the United States were sampled for public release at 3 arc-seconds, which is 1/1200th of a degree of latitude and longitude, or about 90 meters (295 feet). The new data has been released with a 1 arc-second, or about 30 meters (98 feet), sampling that reveals the full resolution of the original measurements.

We will use the new SRTM for elevation data as one of the data points for machine learning for one module in Curiosio.

Big thanks to the astronauts, JSC JPL mapping engineers, and NGA/NIMA! OK, back to Earth…


STS-99 mission was successfully completed by the Space Shuttle Endeavour. Here is a link to STS-99 launch. Here is a link to STS-99 flight story, which contains the footage and description how the mapping machinery worked in orbit (starts from 4m00s and again from 10m07s with a glitch and tears). It was the biggest rigid structure in space by that time. It took 330 big tape cassettes to record the data. Endeavour accomplished 25 missions between May 1992 and June 2011. It was formally decommissioned and put to California Science Center in Los Angeles. Endeavour’s road to the science center was the mission itself.

Endeavour moving through Los Angeles


Curiosio is a superguide for travel geeks. We envision independent travel when the world unlocks. We build fundamental technology for the new world of travel. Curiosio is a computational knowledge engine + search engine + answer engine. Curiosio is neat + clean + cool on the screen. Curiosio is advanced and cutting-edge behind the browser. We do ML for the knowledge graph mainly. We do Evolutionary AI for the artificial smartness. Be safe and curious, stay tuned!

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