Short presentation
====================

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**GEOP4TH** (pronounced /ʤiɒpɑːθ/ jee-uh-pa-th, for *GEOspatial Python Pre-Processing Platform for Trajectories in Hydro-socio-ecosystems)* is a collection of python tools 
to facilitate the processing of geospatial data. It provides:

#. Simple, ergonomic and generic functions to manipulate space-time data
    - based on generic functions with the right dose of abstraction so that users do not have to worry about the specificities of the data formats
    - strongly simplifies the handling of space-time data (like |netCDF|)
    - especially useful for hydrological models preprocessing
	
#. A framework to collaboratively develop and share complete pre-processing workflows designed for specific datasets or applications
    - the generic functions can be easily combined into workflows
    - once a workflow has been developped for a particular dataset or application, it can be shared within the corresponding GEOP4TH modules
    - these workflows can then be run in one function call
    - so far, routines for some common French datasets (`SIM <https://www.data.gouv.fr/fr/datasets/donnees-changement-climatique-sim-quotidienne>`_, 
      `EXPLORE2 <https://www.drias-climat.fr>`_, `BNPE <https://bnpe.eaufrance.fr>`_, 
      `OSO <https://www.theia-land.fr/product/carte-doccupation-des-sols-de-la-france-metropolitaine>`_...) and for `CWatM <https://cwatm.iiasa.ac.at>`_ 
      preprocessing have been implemented 
    - this part is fundamentally collaborative and any contribution is more than welcome!

#. Additional tools such as graphical functions to visualize hydro-climatic trajectories and diagnostics 
    - so far these tools have been combined with corresponding data retrieving/processing workflows for France (based on 
      `SIM <https://www.data.gouv.fr/fr/datasets/donnees-changement-climatique-sim-quotidienne>`_ historical reanalysis and 
      `EXPLORE2 <https://www.drias-climat.fr>`_ projections datasets)

Today there are a vast amount of hydroclimatic or geographic datasets publicly available, as well as a wide choice 
of applications (models, softwares, web apps...) using such types of data. Nevertheless, interfacing these data with their applications 
is far from straightworward and can sometimes require a lot of time and skills beyond those of the application field (`Knoben et al., 2022`_). The 
toolbox *GEOP4TH* aims to facilitate this interface between data and applications.

Many tools are available nowadays to process geospatial data.
GEOP4TH takes advantage of existing tools to combine a genuine python interface, simplicity of use, modular functions and collaborative sharing in the
same free software. 

For more details, have a look at :doc:`How does GEOP4TH compare to existing tools?<originality>`




.. _`Knoben et al., 2022`: 1_

.. [1] Knoben, W. J. M., Clark, M. P., Bales, J., Bennett, A., Gharari, S., Marsh, C. B.,
       et al. (2022). Community Workflows to Advance Reproducibility in Hydrologic Modeling: Separating model-agnostic
       and model-specific configuration steps in applications of large-domain hydrologic models. Water Resources Research,
       58, e2021WR031753. https://doi.org/10.1029/2021WR031753



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  <abbr title="network Common Data Form">netCDF</abbr>
  

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