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@sepal-contrib

SEPAL contrib

A collection of SEPAL modules maintained by SEPAL team.
README.md
  • If you want to help, here is the list of all the repositories issues
  • Applications already available on SEPAL are documented here

Popular repositories

  1. se.plan se.plan Public

    tool to provide infomation on restoration planning

    Jupyter Notebook 9 4

  2. bfast_gpu bfast_gpu Public

    GPU implementation of the BFAST algorithm in a voila notebook

    Python 6 3

  3. bfastspatial bfastspatial Public

    Shiny interface for BFAST spatial

    R 5 14

  4. eSBAE_notebooks eSBAE_notebooks Public

    This repository holds a set of notebooks that allows to follow an optimised workflow for creating Sample Based Area Estimates resulting from an ensemble classification of various time-series and re…

    Jupyter Notebook 5 2

  5. sepal_mgci sepal_mgci Public

    Measure the extend and the changes of green vegetation in mountain areas

    Python 4 3

  6. sdg_15.3.1 sdg_15.3.1 Public

    monitor SDG indicators at plot level

    Python 3 3

Repositories

Showing 10 of 38 repositories
  • se.plan Public

    tool to provide infomation on restoration planning

    Jupyter Notebook 9 MIT 4 25 (1 issue needs help) 0 Updated May 13, 2024
  • sepal_mgci Public

    Measure the extend and the changes of green vegetation in mountain areas

    Python 4 MIT 3 5 0 Updated Apr 25, 2024
  • wcmc-mgci Public

    Tools to calculate the Mountain Green Cover Index in R an QGIS. Developed by FAO and WCMC.

    Python 0 CC-BY-SA-4.0 5 0 3 Updated Apr 18, 2024
  • gfc_wrapper_python Public

    translation and adaptation of the openforis gfc wrapper in python

    Python 2 MIT 3 2 0 Updated Apr 17, 2024
  • bfastspatial Public

    Shiny interface for BFAST spatial

    R 5 14 0 0 Updated Apr 17, 2024
  • planet_active_fires_explorer Public

    Display active fire locations and Planet daily data

    Python 2 MIT 2 6 0 Updated Apr 12, 2024
  • eSBAE_notebooks Public

    This repository holds a set of notebooks that allows to follow an optimised workflow for creating Sample Based Area Estimates resulting from an ensemble classification of various time-series and remote sensing products over a very dense set of points using some optimized stratification strategy based on the Kozak-Neyman stratification.

    Jupyter Notebook 5 2 0 1 Updated Apr 2, 2024
  • fcdm Public

    Mapping all kind of canopy disturbances (natural or human induced) within (semi-)evergreen forests

    Python 2 MIT 1 4 0 Updated Mar 7, 2024
  • weplan Public

    a GUI for the weplan products

    Python 0 MIT 1 4 0 Updated Mar 7, 2024
  • gee_source Public

    extract sources code from any gee app url

    Python 2 MIT 7 2 0 Updated Mar 7, 2024
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