A primer on understanding Google Earth Engine APIs
DOI:
https://doi.org/10.34629/ipl.isel.i-ETC.81Keywords:
Google Earth Engine, Javascript, PythonAbstract
This article is build on the experience of using Google Earth Engine as a development framework for a previous work by the same authors.Being primarily a distributed parallel computing platform, it is designed around a functional language pattern, even though supported on an object model, and a map / reduce distributed workload paradigm.
Leveraging the sheer computing power delivered by the Google infrastructure and a multi petabyte remote sensing data repository, Google
Earth Engine is an efficient development framework that presents itself in two basic flavors: one online integrated development environment which uses the browser Javascript engine; two APIs that can be deployed to a Python or a NodeJS environment.
This work emphasizes the comparison between the Javascript browser
based implementation and the Python environment packages.
Downloads
References
Jeffrey Dean and Sanjay Ghemawat. Mapreduce: Simplified
data processing on large clusters. In OSDI’04: Sixth Symposium on Operating System Design and Implementation, pages 137–150, San Francisco, CA, 2004.
ESA. Sentinel 2 user guide, 2019. [Online; accessed 2019-01-15].
Google. Share your analyses using earth engine apps, 2018.[Online; accessed 2019-11-03].
Google. Earth engine data catalog, 2019. [Online; accessed 2019-11-03].
Google. Google earth engine guides, python installation, 2019.[Online; accessed 2019-10-30].
Google. Google earth engine guides, band math, 2020. [Online;accessed 2020-01-15].
Noel Gorelick, Matt Hancher, Mike Dixon, Simon Ilyushchenko, David Thau, and Rebecca Moore. Google earth engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202:18–27, 2017.
Python Software Foundation. pickle — python object serialization. https://docs.python.org/3/library/pickle.html, 2019. [Online; accessed 2019-06-10].
Rui S. Reis, Celia Gouveia, Nuno Datia, and M. P. M. Pato. Modelo preditivo de recuperação da vegetacão afetada por incêndios florestais. In INForum 2019 Atas do 11o Simpósio de Informática, page 461–472. NOVA.FCT Editorial, 2019.
Wikipedia contributors. World geodetic system — Wikipedia, the free encyclopedia, 2020. [Online; accessed 2020-02-03].
Downloads
Published
Issue
Section
License
Authors of articles published in the ISEL Academic Journal of Electronics, Telecommunications and Computers retain copyright of their work, without restriction, licensing it under the Creative Commons Attribution-NonCommercial 4.0 Unported License. This license allows free download of the articles from the i-ETC website, as well as re-use and re-distribution without restriction, as long as the original work is properly cited and not used for commercial purposes.