Google Earth Engine

Nilesh Khandalkar
3 min readMar 24, 2023

GEE or Google Earth Engine is a groundbreaking product that has been available for researches and government use for more than a decade, recently about a year ago, Google Cloud launched GEE for commercial use. I had an opportunity to attend Partner Sustainability Hackathon for GEE where I learned the power of GEE which can be a real game changer in today’s sustainability challenges.

With GEE, Public and private sector leaders can improve operations to become more sustainable by analyzing and mitigating climate risks to their organizations. GEE offers 70+PB [40 years of imagery and scientific 900+ datasets] of analysis-ready geospatial data which has ability to perform powerful analytics with tools like BigQuery and Vertex AI. GEE is a powerful tool to analyze and visualize earths data at scale.

Earth Engine is integrated with Google Cloud, enabling provisioning and permissions to be configured and monitored like other Google Cloud services. GEE comes with a web based code editor for writing and running scripts which are mostly in java script or python.

For accessing GEE — https://code.earthengine.google.com/ you need to be associated with Google Cloud project.

GEE UI

EE Datasets can be searched on the search bar, left side of the panel will then display the list of datasets, code editor allows you to write the code and accordingly the MAP image is displayed for analysis. There is already many Client libraries with hundreds of functions which includes JavaScript and Python wrapper functions to translate complex geospatial analysis into Earth Engine requests. GEE can also be integrated within BigQuery’s SQL allowing SQL users to get access to and value from the vast amount of data available within Earth Engine.

The pricing model is based on consumption of Earth Engine resources (compute units and storage) and a monthly subscription fee.

GEE can be accessed as a no-code solution by using Earth-Blox. It gives you a code-free interface to Earth Engine’s entire data catalogue. It provides pre-built workflows, and the ability to build your own workflows using the drag and drop blocks.

Conclusion: GEE can be very promising in near future by committing to a sustainable future and improve the social, economic and environmental well being of the community.

Thank You!

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Nilesh Khandalkar

Passionate about Data and Cloud, working as Data Engineering Manager at Capgemini UK. GCP Professional Data Engineering Certified Airflow Fundamentals Certified