This is so nuts to me: one of my supervisors introduced me to Google Earth Engine, and we’ve been playing with it for our spatial analyses. It’s imagery/spatial analysis in the cloud, with the tagline “letting scientists focus on science instead of downloading and managing data.” Well, Google, you have my attention. The intro video right on the home page has some bullet points I’d like to pull out here…
- planetary scale analysis of massive data
- petabytes of remote sensing data including… (I won’t list them all here, just what made my mouth water)
- > 40 yrs Landsat
- twice-daily global coverage
- 36 bands
- non-satellite imagery
- land cover
- climate data
- full featured development environment: Python
- machine learning
- use cases…
- global forest change
- species habitat modeling
- global surface water
…and much more! Can you believe it? The FAQ seems a little outdated right now, so maybe this isn’t relevant anymore:
How does Earth Engine compare to the Landsat and Sentinel data in Google Cloud?
The Earth Engine team has worked in close collaboration with Google Cloud to bring the Landsat and Sentinel-2 collections to Google Cloud Storage as part of the public data program. The collections in Google Cloud are best suited to workflows where you need to access the data directly from Cloud services such as Google Compute Engine or Google Cloud Machine Learning. The Earth Engine Code Editor and the Earth Engine API do not access these Cloud collections but instead use the Earth Engine data catalog directly.
I also don’t know what this means:
Does Earth Engine work with my existing tools?
Imagery and data from other tools may be imported into Earth Engine for analysis. Any analysis performed in Earth Engine can be downloaded for use by other tools.
It’s cool that they have a data set request form, but in the meantime you can use your own data.
Vector data may be loaded into Google Fusion Tables and accessed in Earth Engine.