Essential Site Maintenance: Authorea-powered sites will be updated circa 15:00-17:00 Eastern on Tuesday 5 November.
There should be no interruption to normal services, but please contact us at [email protected] in case you face any issues.

loading page

DELTA: An Open-Source Framework to Simplify Machine Learning with Satellite Imagery
  • Michael von Pohle,
  • Brian Coltin,
  • Scott McMichael
Michael von Pohle
NASA Ames Research Center [USRA]

Corresponding Author:[email protected]

Author Profile
Brian Coltin
NASA Ames Research Center
Author Profile
Scott McMichael
NASA Ames Research Center
Author Profile

Abstract

DELTA (Deep Earth Learning, Tools, and Analysis) is an open-source framework developed at NASA to simplify running and training machine learning (ML) models on satellite imagery. Users new to machine learning can run existing ML models on satellite imagery with minimal setup and configuration. For experienced ML users, DELTA helps simplify data engineering, preprocessing steps, and reduces the need for boilerplate code that needs written to make satellite imagery datasets palatable for machine learning. This lets data scientists focus on model development while DELTA handles the imagery manipulation. This presentation will demonstrate DELTA’s functionality and share some examples from an active project using it for flood mapping using imagery from multiple satellite sources.