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Dataset Open Access

A Deep Learning-Based Hybrid Model of Global Terrestrial Evaporation

Koppa, Akash; Rains, Dominik; Hulsman, Petra; Miralles, Diego G.


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.5220753", 
  "language": "eng", 
  "title": "A Deep Learning-Based Hybrid Model of Global Terrestrial Evaporation", 
  "issued": {
    "date-parts": [
      [
        2021, 
        8, 
        19
      ]
    ]
  }, 
  "abstract": "<p>This repository contains the codes and datasets used in the research article &quot;A Deep Learning-Based Hybrid Model of Global Terrestrial Evaporation&quot;.</p>\n\n<p>The repository contains the following files: 1) Codes - contains scripts used for training the deep learning models used in the study, and for creating the figures in the article. 2) Input - contains all the processed input used for training the deep learning models and the datasets used for creating the figures in the article. 3) Output - contains the final deep learning models and the outputs (evaporation and transpiration stress factor) outputs from the hybrid model developed in the study.</p>\n\n<p>Formats: All scripts are in the programming language Python. The datasets are in HDF5 and NetCDF formats</p>", 
  "author": [
    {
      "family": "Koppa, Akash"
    }, 
    {
      "family": "Rains, Dominik"
    }, 
    {
      "family": "Hulsman, Petra"
    }, 
    {
      "family": "Miralles, Diego G."
    }
  ], 
  "type": "dataset", 
  "id": "5220753"
}
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