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GriddingMachine, a database and software for Earth system modeling at global and regional scales
Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9160223/ https://www.ncbi.nlm.nih.gov/pubmed/35650204 http://dx.doi.org/10.1038/s41597-022-01346-x |
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author | Wang, Yujie Köhler, Philipp Braghiere, Renato K. Longo, Marcos Doughty, Russell Bloom, A. Anthony Frankenberg, Christian |
author_facet | Wang, Yujie Köhler, Philipp Braghiere, Renato K. Longo, Marcos Doughty, Russell Bloom, A. Anthony Frankenberg, Christian |
author_sort | Wang, Yujie |
collection | PubMed |
description | Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim towards a standardized database and one-stop distribution method of global datasets. Here, we present the GriddingMachine as (1) a database of global-scale datasets commonly used to parameterize or benchmark the models, from plant traits to vegetation indices and geophysical information and (2) a cross-platform open source software to download and request a subset of datasets with only a few lines of code. The GriddingMachine datasets can be accessed either manually through traditional HTTP, or automatically using modern programming languages including Julia, Matlab, Octave, Python, and R. The GriddingMachine collections can be used for any land and Earth modeling framework and ecological research at the regional and global scales, and the number of datasets will continue to grow to meet the increasing needs of research communities. |
format | Online Article Text |
id | pubmed-9160223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-91602232022-06-03 GriddingMachine, a database and software for Earth system modeling at global and regional scales Wang, Yujie Köhler, Philipp Braghiere, Renato K. Longo, Marcos Doughty, Russell Bloom, A. Anthony Frankenberg, Christian Sci Data Article Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim towards a standardized database and one-stop distribution method of global datasets. Here, we present the GriddingMachine as (1) a database of global-scale datasets commonly used to parameterize or benchmark the models, from plant traits to vegetation indices and geophysical information and (2) a cross-platform open source software to download and request a subset of datasets with only a few lines of code. The GriddingMachine datasets can be accessed either manually through traditional HTTP, or automatically using modern programming languages including Julia, Matlab, Octave, Python, and R. The GriddingMachine collections can be used for any land and Earth modeling framework and ecological research at the regional and global scales, and the number of datasets will continue to grow to meet the increasing needs of research communities. Nature Publishing Group UK 2022-06-01 /pmc/articles/PMC9160223/ /pubmed/35650204 http://dx.doi.org/10.1038/s41597-022-01346-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wang, Yujie Köhler, Philipp Braghiere, Renato K. Longo, Marcos Doughty, Russell Bloom, A. Anthony Frankenberg, Christian GriddingMachine, a database and software for Earth system modeling at global and regional scales |
title | GriddingMachine, a database and software for Earth system modeling at global and regional scales |
title_full | GriddingMachine, a database and software for Earth system modeling at global and regional scales |
title_fullStr | GriddingMachine, a database and software for Earth system modeling at global and regional scales |
title_full_unstemmed | GriddingMachine, a database and software for Earth system modeling at global and regional scales |
title_short | GriddingMachine, a database and software for Earth system modeling at global and regional scales |
title_sort | griddingmachine, a database and software for earth system modeling at global and regional scales |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9160223/ https://www.ncbi.nlm.nih.gov/pubmed/35650204 http://dx.doi.org/10.1038/s41597-022-01346-x |
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