Methodology

Our first step is to survey the present public and academic usage of Google Earth, since they represent the end user’s perspective. Although there were some papers and analysis on Google Earth, studies of the software, particularly for remote sensing, is seldom, which increases the importance of this paper because it suggests that Google Earth is not being used to its full potential in the remote sensing space. To expand our search for literature we also looked for discussion on the use of cloud computation in remote sensing, as well as other remote sensing computation engine.

Once we gain preliminary understanding on the present field, our next step in our project was to acquire access to Google Earth Engine Beta, since this will reveal to us where Google is in their development in this field, and the provider’s perspective. We applied too this program, suggesting that we were in the academic remote sensing space, wanting to survey their Data Catalog, and their current techniques for remote sensing analysis.

EE’s data catalog was then compared against freely available remote sensing data through governmental databases such as USGS, NOAA and their sundry satellites (e.g. Landsat, GOES, EOG, etc.).

We then surveyed Earth Engine’s capability. We looked at its ability to deal with remote sensing from their front end graphical user interface, as well as their programming API. In order to learn more, we also considered the present use of Earth Engine.

Survey of Google Earth Engine for academia and in comparison with existing platforms and publicly available data.