Introducing EarthAI Notebook

A New Environment for Geospatial Analytics

Astraea Earth AI
Dec 23, 2019 · 5 min read

Geospatial intelligence is evolving at a new pace. As machine learning has advanced to the point where insights can be reliably derived from raster data, the limits imposed by human-driven, single-file-at-a-time workflows are being blown away by new methods of extracting insight at an unprecedented scale. New platforms are emerging as the legacy paradigm of desktop-centric Geographic Information Systems (GIS) confronts the new paradigm of cloud-native machine learning. In this post, we will explore the history of analyzing Earth-observing raster data and present our newest contribution to the geospatial community.


The Legacy Paradigm of Geospatial Analytics

Enter Machine Learning.

What once required a great deal of analyst time and resources can now be accomplished quickly and cost-efficiently by machines in the cloud. This is not to say that it is easy — merely possible.


The New Geospatial Paradigm

Largely, these use cases have come from industries that could afford to invest significantly for the chance of gaining this edge over the competition. Asset management and agriculture, industries where a small informational advantage on the price of a stock or the yield of a farm make a large bottom-line impact, have been early adopters of new geospatial technology.

While these early use cases have proven that Earth-observation imagery can provide a valuable source of information for decisionmakers, they have not yet solved the challenges presented by the legacy paradigm. In fact, they have introduced others.

Computer vision algorithms are greedy. Requiring hundreds to thousands of examples to train object detection algorithms, imagery analysis can quickly overwhelm an individual computer or server.

Furthermore, training neural network models takes a tremendous amount of computational resources before they are sufficiently accurate. Because raster data are intrinsically large and computer vision algorithms require so much computational power to train, the only practical way to address these challenges is through cloud computing and Graphics Processing Unit (GPU) technologies.

While widely available from numerous companies, cloud computing remains very complex. Savvy engineers spend countless hours configuring and managing computational clouds to achieve the performance required to manage and process imagery data. This specific challenge is likely the most significant barrier to leveraging computer vision. While data scientists seeking to apply machine learning algorithms to traditional tabular data can quickly and easily scale their analytics, the tools required to process imagery at scale have matured far more slowly.


EarthAI Notebook

With that goal in mind, we set out to develop EarthAI: a fully integrated, cloud-native platform to enable experts and non-experts alike to leverage the full power of Earth-observing data. Our platform provides a suite of products focused on removing the complexities of discovering, processing, and analyzing Earth-observation data at scale. In July 2019, we released Earth OnDemand, which enables users to access and explore over 8PB of free public satellite imagery in an intuitive interface.

Now, we’re releasing the next product on our roadmap: EarthAI Notebook. Notebook is a hosted JupyterLab environment fully loaded with geospatial analysis libraries and API access to the Earth OnDemand catalog.

Perhaps the most significant advantage of EarthAI Notebook is the ability to seamlessly scale an analysis. Our push-button provisioning simplifies cloud infrastructure, allowing users to access cloud resources with a single click (GPUs coming soon!). With access to Earth OnDemand, EarthAI Notebook comes “batteries-included” with free satellite imagery from NASA and ESA. Now, data scientists can spend less time searching for data, less time waiting for results, no time on DevOps, and more time on generating insights from pixels.

Start a free trial of EarthAI Notebook: https://astraea.earth/earth-ai-notebook/

At Astraea, we believe the answers to some of the world’s most important questions reside in imagery data. The EarthAI platform was built to democratize access to earth observing data and enable a much broader segment of users to unlock the answers to these questions. We are removing the barriers of data access, cloud computing, and insufficient analysis tools to empower the curious. We hope that EarthAI Notebook enables a broad community of data scientists, analysts, and developers to begin working with satellite imagery.

To learn more about EarthAI Notebook, visit our website or start a free trial (no credit card required).

Astraea.Earth

See the Earth as it could be. Astraea’s EarthAI platform provides a suite of products focused on removing the complexities of discovering, processing, and analyzing EO data at scale.

Astraea Earth AI

Written by

See the Earth as it could be.

Astraea.Earth

See the Earth as it could be. Astraea’s EarthAI platform provides a suite of products focused on removing the complexities of discovering, processing, and analyzing EO data at scale.

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