Google Earth Engine: Democratizing Global Geospatial Analysis with Cloud Computing
that combines a public data catalog with a large-scale computational
facility optimized for parallel processing of geospatial data. The data
catalog is a multi-petabyte archive of georeferenced datasets that include
images from Earth observing satellite and airborne sensors (examples: USGS
Landsat, NASA MODIS, USDA NAIP), weather and climate datasets, and digital
elevation models. Earth Engine supports both a just-in-time computation
model that enables real-time preview and debugging during algorithm
development for open-ended data exploration, and a batch computation mode
for applying algorithms over large spatial and temporal extents. The
platform automatically handles many traditionally-onerous data
management tasks, such as data format conversion, reprojection, and
resampling, which facilitates writing algorithms that combine data from
multiple sensors and/or models. Although the primary use of Earth Engine,
to date, has been the analysis of large Earth observing satellite datasets,
the computational platform is generally applicable to a wide variety of
use cases that require large-scale geospatial data analyses. The cloud-based
nature of the platform effectively gives anyone with a web browser
access to a supercomputer tuned specifically for geospatial analysis.
This talk will focus on how Earth Engine has been used by organizations to
educate the public about environmental challenges, and by educators bringing
real time satellite image display and analysis into their classroomes.
