Why Google Earth Engine?
Research in Remote Sensing has evolved drastically over the past few decades.
In the earliest years of remote sensing analysis, only a handful of governments had the capability to deploy satellites and reliably process the imagery, and their use was largely limited to the military and intelligence communities. In the late 1950s, the US and Europe established the National Aeronautics and Space Administration (NASA) and the origins of the European Space Agency (ESA) to support a civilian space program as well as space and aeronautics research. Even then, data access was unwieldy and costly - even if a researcher had identified the data they needed, they would have to go through the highly complicated and time-intensive steps of downloading the data onto a mainframe computer with sufficient storage and processing capability to perform a series of pre-processing steps (e.g. orthorectification and atmospheric corrections), all before they could start analysis.
As researchers involved in Remote Sensing, Google Earth Engine provides an invaluable toolset that you can use throughout your career.
License and Attribution
This work is licensed under a Creative Commons Attribution 4.0 International License. The foundation of these lab exercises were generously shared with us by Nicholas Clinton (Google) and Dr. David Saah (University of San Francisco, Geospatial Analysis Lab). We thank them for this great public good and take responsibility for any errors that arose from our adaptation.
Elinor Ben-Ami and Ozzy Campos have extended and customized these labs and exercise and incorporated them into the course taught at Virginia Tech, 'Remote Sensing for Social Science'.
We will also like to mention the extensive use of the
geemap package, developed by Qiusheng Wu.
- Wu, Q., (2020).
geemap: A Python package for interactive mapping with Google Earth Engine. The Journal of Open Source Software, 5(51), 2305. https://doi.org/10.21105/joss.02305