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Natural grasslands across mainland France: A dataset including a 10 m raster and ground reference points
The data provided here include the first 10 m raster of natural grasslands across mainland France and related ground reference points. The latter consist of 1770 field observations that describe natural and artificial grasslands from respectively a compilation of hundreds of field-based vegetation m...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10336393/ https://www.ncbi.nlm.nih.gov/pubmed/37448734 http://dx.doi.org/10.1016/j.dib.2023.109348 |
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author | Panhelleux, Léa Rapinel, Sébastien Hubert-Moy, Laurence |
author_facet | Panhelleux, Léa Rapinel, Sébastien Hubert-Moy, Laurence |
author_sort | Panhelleux, Léa |
collection | PubMed |
description | The data provided here include the first 10 m raster of natural grasslands across mainland France and related ground reference points. The latter consist of 1770 field observations that describe natural and artificial grasslands from respectively a compilation of hundreds of field-based vegetation maps and the European Union Land Parcel Identification System (LPIS). Based on analysis of aerial images, ground reference points were manually extracted from grassland polygons of the field-based vegetation maps and the LPIS within herbaceous areas larger than 30 × 30 m. The raster data of natural grasslands were derived from five annual 10 m land cover maps of France from 2016−2020. Pixels classified as ``grassland'' every year from 2016−2020 were considered natural grasslands, while those classified as ``crop'' at least once were considered artificial grasslands. Validation using the ground reference points revealed that natural and artificial grasslands were accurately mapped (overall accuracy = 86%). The ground reference points, publicly available in GeoJSON vector format, can be used as training or test samples for spatial modeling. The natural grassland map, publicly available in GeoTIFF raster format, can be used as a predictor variable for spatial modeling or as a base map for landscape ecology analyses. |
format | Online Article Text |
id | pubmed-10336393 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103363932023-07-13 Natural grasslands across mainland France: A dataset including a 10 m raster and ground reference points Panhelleux, Léa Rapinel, Sébastien Hubert-Moy, Laurence Data Brief Data Article The data provided here include the first 10 m raster of natural grasslands across mainland France and related ground reference points. The latter consist of 1770 field observations that describe natural and artificial grasslands from respectively a compilation of hundreds of field-based vegetation maps and the European Union Land Parcel Identification System (LPIS). Based on analysis of aerial images, ground reference points were manually extracted from grassland polygons of the field-based vegetation maps and the LPIS within herbaceous areas larger than 30 × 30 m. The raster data of natural grasslands were derived from five annual 10 m land cover maps of France from 2016−2020. Pixels classified as ``grassland'' every year from 2016−2020 were considered natural grasslands, while those classified as ``crop'' at least once were considered artificial grasslands. Validation using the ground reference points revealed that natural and artificial grasslands were accurately mapped (overall accuracy = 86%). The ground reference points, publicly available in GeoJSON vector format, can be used as training or test samples for spatial modeling. The natural grassland map, publicly available in GeoTIFF raster format, can be used as a predictor variable for spatial modeling or as a base map for landscape ecology analyses. Elsevier 2023-06-27 /pmc/articles/PMC10336393/ /pubmed/37448734 http://dx.doi.org/10.1016/j.dib.2023.109348 Text en © 2023 Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Panhelleux, Léa Rapinel, Sébastien Hubert-Moy, Laurence Natural grasslands across mainland France: A dataset including a 10 m raster and ground reference points |
title | Natural grasslands across mainland France: A dataset including a 10 m raster and ground reference points |
title_full | Natural grasslands across mainland France: A dataset including a 10 m raster and ground reference points |
title_fullStr | Natural grasslands across mainland France: A dataset including a 10 m raster and ground reference points |
title_full_unstemmed | Natural grasslands across mainland France: A dataset including a 10 m raster and ground reference points |
title_short | Natural grasslands across mainland France: A dataset including a 10 m raster and ground reference points |
title_sort | natural grasslands across mainland france: a dataset including a 10 m raster and ground reference points |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10336393/ https://www.ncbi.nlm.nih.gov/pubmed/37448734 http://dx.doi.org/10.1016/j.dib.2023.109348 |
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