https://github.com/saraivaufc/land-use-classification-using-encoder-decoder-lstm

Biweekly mapping of land use and land cover using MODIS time series (MOD13Q1) and LSTM Neural Networks.
https://github.com/saraivaufc/land-use-classification-using-encoder-decoder-lstm

land-cover land-use lstm modis neural-networks

Last synced: 5 months ago
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Biweekly mapping of land use and land cover using MODIS time series (MOD13Q1) and LSTM Neural Networks.

• Host: GitHub
• URL: https://github.com/saraivaufc/land-use-classification-using-encoder-decoder-lstm
• Owner: saraivaufc
• License: other
• Created: 2021-01-07T09:32:15.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2024-03-31T00:07:59.000Z (about 2 years ago)
• Last Synced: 2024-03-31T01:22:25.043Z (about 2 years ago)
• Topics: land-cover, land-use, lstm, modis, neural-networks
• Language: Jupyter Notebook
• Homepage:
• Size: 6.23 MB
• Stars: 5
• Watchers: 1
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
#### Land use classification using Encoder-Decoder LSTM

![watershed-segmentation](./docs/predicted.gif)

View on [![Kaggle link](./docs/kaggle.png)](https://www.kaggle.com/saraivaufc/land-use-classification-using-encoder-decoder-lstm)



    






This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.