Hello, World.

An introduction to Snapsat, the easiest way to acquire and parse Landsat imagery.

Obligatory plug for the beautiful state of Maine.

If you put me on the spot and asked me what Snapsat is, I’d tell you that it’s the fastest way to build custom Landsat composites. Which is true! But in writing this, I’ve realized that while that might be an accurate answer, it also misses what makes this project special.

Over the last decade, the cost of working with geospatial data has plummeted thanks to:

  • Technological innovation. Processes that used to take multiple days and expensive hardware can now be run with a single command on an everyday laptop.
  • Organizations like Maptime are making it incredibly easy to learn geospatial tools and processes.
  • The amount of freely available data has exploded, and so have tutorials and examples on how to use it.

It’s getting easier. We’re moving in the right direction. But there are still some rough spots, and working with satellite imagery feels like one of them. The learning curve remains relatively high, so we built Snapsat to flatten it. Which is why I absolutely love the following bit of feedback that one of our users submitted.

Brilliant. this is the greatest leap in facilitating the use of satellite data I’ve ever seen. In 1990, it was a US$50K SGI workstation (three colours!), a separate US$20 K machine to run the tapes + US$20K of software. Oh, and each image cost US$625.

We spent the last few weeks refining our UI, trying to make it even more accessible to users new to the concept of remote sensing and what Landsat can be used for. For folks who are more experienced, we’ve developed an API that allows for programmatic access to the functionality currently provided by the Snapsat web interface.

If you want to learn more about what we’ve done and where we’re planning on going, send us an email. We’ll all be at the CUGOS Spring Fling — if you’re in Seattle, come and say hi!

Finally, this project wouldn’t have happened without the constant support of Cris Ewing, Jed Sundwall and the AWS Open Data team, Development Seed, The Landsat program, Constantine, Jake, Joel, and Mark.

Jacques


PS: We’ve come a long way to make this process more efficient, but it does cost money. If you’re a fan of what we’ve done and are in a position to give us a bit of financial support, or would like us to build something similar for you, we’d certainly love to talk!