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A high-resolution canopy height model of the Earth

The model estimates canopy top height for every Sentinel-2 image pixel and was trained using sparse GEDI LIDAR data as a reference.
https://github.com/langnico/global-canopy-height-model

canopy-height-models deep-learning ensemble gedi sentinel-2 uncertainty

Last synced: 4 days ago
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This repository contains the code used in the paper: A high-resolution canopy height model of the Earth. Here, we developed a model to estimate canopy top height anywhere on Earth. The model estimates canopy top height for every Sentinel-2 image pixel and was trained using sparse GEDI LIDAR data as a reference.


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Last synced: 4 days ago

Total Commits: 5
Total Committers: 2
Avg Commits per committer: 2.5
Development Distribution Score (DDS): 0.2

Commits in past year: 5
Committers in past year: 2
Avg Commits per committer in past year: 2.5
Development Distribution Score (DDS) in past year: 0.2

Name Email Commits
nlang n****g@g****h 4
Nico Lang n****l@g****m 1

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Last synced: 5 days ago

Total issues: 3
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Average time to close issues: 3 minutes
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Total pull request authors: 0
Average comments per issue: 0.67
Average comments per pull request: 0
Merged pull request: 0
Bot issues: 0
Bot pull requests: 0

Past year issues: 3
Past year pull requests: 0
Past year average time to close issues: 3 minutes
Past year average time to close pull requests: N/A
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Past year pull request authors: 0
Past year average comments per issue: 0.67
Past year average comments per pull request: 0
Past year merged pull request: 0
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Past year bot pull requests: 0

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  • Rur1sama (3)

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Dependencies

environment.yml pypi
requirements.txt pypi
  • botocore *
  • ipython *
  • matplotlib *
  • numpy *
  • pathlib *
  • scikit-image *
  • scikit-learn *
  • sentinelhub ==3.9.0
  • tables *
  • tensorboard *
  • tqdm *
  • typing *
  • urllib3 *
  • wandb *
setup.py pypi

Score: 3.258096538021482