Dataset Open Access
Koppa, Akash;
Rains, Dominik;
Hulsman, Petra;
Miralles, Diego G.
<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <dc:creator>Koppa, Akash</dc:creator> <dc:creator>Rains, Dominik</dc:creator> <dc:creator>Hulsman, Petra</dc:creator> <dc:creator>Miralles, Diego G.</dc:creator> <dc:date>2021-08-19</dc:date> <dc:description>This repository contains the codes and datasets used in the research article "A Deep Learning-Based Hybrid Model of Global Terrestrial Evaporation". 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. Formats: All scripts are in the programming language Python. The datasets are in HDF5 and NetCDF formats</dc:description> <dc:identifier>https://zenodo.org/record/5220753</dc:identifier> <dc:identifier>10.5281/zenodo.5220753</dc:identifier> <dc:identifier>oai:zenodo.org:5220753</dc:identifier> <dc:language>eng</dc:language> <dc:relation>info:eu-repo/grantAgreement/EC/H2020/869550/</dc:relation> <dc:relation>info:eu-repo/grantAgreement/EC/H2020/715254/</dc:relation> <dc:relation>doi:10.5281/zenodo.5220752</dc:relation> <dc:rights>info:eu-repo/semantics/openAccess</dc:rights> <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights> <dc:subject>Deep learning</dc:subject> <dc:subject>Hybrid Modeling</dc:subject> <dc:subject>Evaporation</dc:subject> <dc:subject>Evaporative Stress</dc:subject> <dc:subject>Transpiration</dc:subject> <dc:subject>GLEAM</dc:subject> <dc:subject>Machine Learning</dc:subject> <dc:subject>Earth System Modeling</dc:subject> <dc:title>A Deep Learning-Based Hybrid Model of Global Terrestrial Evaporation</dc:title> <dc:type>info:eu-repo/semantics/other</dc:type> <dc:type>dataset</dc:type> </oai_dc:dc>
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