2021 Machine Learning for Earth Observation Market Map Release

Now featuring 250+ organizations that focus on machine learning applications with satellite data

Radiant Earth Foundation
Oct 5 · 2 min read

By Louisa Nakanuku-Diggs, Marketing and Communications Manager, Radiant Earth Foundation

The latest interactive Machine Learning for Earth Observation Market Map, a curated list of organizations focused on different machine learning aspects with a satellite data pipeline, is available for download.

This release includes an additional list of 100+ organizations, thanks to a crowdsourcing effort on social media. Earlier in September, we asked our followers on Twitter and LinkedIn to identify organizations that we missed in the earlier version of the market map or were established since then. The large number of contributions from people in such a short period speaks of the niche area of machine learning (ML) for Earth observation (EO). The entries hint toward the incredible aptitude of organizations to optimize these innovative technologies and expand them in the service of humanity.

The ML4EO market map remains divided into two groups — Commercial and Non-Commercial — and five categories. We only included organizations that provide geospatial machine learning analysis and technologies as a service. The specific description of the categories are:

  1. Data Analysis and Services: Organizations that develop machine learning models and analytical solutions for various geospatial applications using EO.
  2. Analytics Platforms: Organizations that provide software or platform to process EO data and build customized applications.
  3. Labeling Platforms: Organizations that provide a solution for generating labels on satellite imagery and creating training data catalogs.
  4. Competition Platform: Organizations that help you run challenges on your training dataset to outsource modeling solutions.
  5. Data Access and Storage: Organizations that provide satellite imagery and geospatial training data to facilitate machine learning analytics pipelines.

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