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Formulating a Big Data Science Challenge for Land Imaging Time-Series Data

In early 2020, the U.S. Geological Survey (USGS) requested that the Landsat Advisory Group (LAG), a subcommittee of the National Geospatial Advisory Committee (NGAC), provide input regarding the initiation of a Big Data Science Government Challenge to explore the benefits of computer vision and Machine Learning (ML), specifically Deep Neural Network (DNN)/ Convolutional Neural Network (CNN) methods for the purposes of exploiting Landsat Analysis Ready Data for time-series analysis and land change forecasting applications.

These LAG high level recommendations seek to provide support and encouragement for the development of an initial challenge to be conducted in 2021. Based on the outcomes of this initial challenge, the LAG encourages USGS to consider creating a series of follow-on challenges in 2022 and beyond in recognition of the 50th anniversary of the Landsat program.

  • Author(s):
  • National Geospatial Advisory Committee Landsat Advisory Group
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Formulating a Big Data Science Challenge for Land Imaging Time-Series Data
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Website:Visit Publisher Website
Publisher:United States Geospatial Intelligence Foundation (USGIF)
Published:April 1, 2021
License:Public Domain

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