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Land Cover Classification with eo-learn

Pankaj Dey

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  • Institute : Indian Institute of Science
  • Programming language : MATLAB, R
Land Cover Classification with eo-learn
« on: January 09, 2019, 05:31:35 PM »
The availability of open Earth Observation (EO) data through the Copernicus and Landsat programs represents an unprecedented resource for many EO applications, ranging from land use and land cover (LULC) monitoring, crop monitoring and yield prediction, to disaster control, emergency services and humanitarian relief. Given the large amount of high spatial resolution data at high revisit frequency, frameworks able to automatically extract complex patterns in such spatio-temporal data are required. eo-learn aims at providing a set of tools to make prototyping of complex EO workflows as easy, fast, and accessible as possible.

Link to blog post chronologically:

1. https://medium.com/sentinel-hub/introducing-eo-learn-ab37f2869f5c

2. https://github.com/sentinel-hub/eo-learn
   https://eo-learn.readthedocs.io/en/latest/
   https://github.com/sentinel-hub

3. https://medium.com/sentinel-hub/land-cover-classification-with-eo-learn-part-1-2471e8098195

4. https://medium.com/sentinel-hub/land-cover-classification-with-eo-learn-part-2-bd9aa86f8500
Pankaj