Cargando…
A 5 m dataset of digital terrain model derivatives across mainland France
A dataset of three digital terrain model (DTM) derivatives was produced at 5 m spatial resolution across mainland France. This dataset includes (i) a topographic wetness index (TWI) that characterizes potential soil wetness as a function of the contributing area and local slope, (ii) a multi-scale t...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10339187/ https://www.ncbi.nlm.nih.gov/pubmed/37456122 http://dx.doi.org/10.1016/j.dib.2023.109369 |
_version_ | 1785071797464465408 |
---|---|
author | Panhelleux, Léa Rapinel, Sébastien Lemercier, Blandine Gayet, Guillaume Hubert-Moy, Laurence |
author_facet | Panhelleux, Léa Rapinel, Sébastien Lemercier, Blandine Gayet, Guillaume Hubert-Moy, Laurence |
author_sort | Panhelleux, Léa |
collection | PubMed |
description | A dataset of three digital terrain model (DTM) derivatives was produced at 5 m spatial resolution across mainland France. This dataset includes (i) a topographic wetness index (TWI) that characterizes potential soil wetness as a function of the contributing area and local slope, (ii) a multi-scale topographic position color composite (MTPCC) that describes the position of a pixel relative to its neighborhood at three spatial scales, and (iii) a vertical distance to channel network index (VDCNI) that expresses the vertical height between the elevation of a pixel and the nearest channel. These three raster layers were derived from the French national airborne DTM at 5 m spatial resolution and the vector layer of the channel network of the national hydrological database. This unprecedented fine-scale dataset opens new insights for geomorphological analysis. It can be used for several purposes, such as environmental modeling, risk assessment, or water-resource management. |
format | Online Article Text |
id | pubmed-10339187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103391872023-07-14 A 5 m dataset of digital terrain model derivatives across mainland France Panhelleux, Léa Rapinel, Sébastien Lemercier, Blandine Gayet, Guillaume Hubert-Moy, Laurence Data Brief Data Article A dataset of three digital terrain model (DTM) derivatives was produced at 5 m spatial resolution across mainland France. This dataset includes (i) a topographic wetness index (TWI) that characterizes potential soil wetness as a function of the contributing area and local slope, (ii) a multi-scale topographic position color composite (MTPCC) that describes the position of a pixel relative to its neighborhood at three spatial scales, and (iii) a vertical distance to channel network index (VDCNI) that expresses the vertical height between the elevation of a pixel and the nearest channel. These three raster layers were derived from the French national airborne DTM at 5 m spatial resolution and the vector layer of the channel network of the national hydrological database. This unprecedented fine-scale dataset opens new insights for geomorphological analysis. It can be used for several purposes, such as environmental modeling, risk assessment, or water-resource management. Elsevier 2023-07-04 /pmc/articles/PMC10339187/ /pubmed/37456122 http://dx.doi.org/10.1016/j.dib.2023.109369 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Data Article Panhelleux, Léa Rapinel, Sébastien Lemercier, Blandine Gayet, Guillaume Hubert-Moy, Laurence A 5 m dataset of digital terrain model derivatives across mainland France |
title | A 5 m dataset of digital terrain model derivatives across mainland France |
title_full | A 5 m dataset of digital terrain model derivatives across mainland France |
title_fullStr | A 5 m dataset of digital terrain model derivatives across mainland France |
title_full_unstemmed | A 5 m dataset of digital terrain model derivatives across mainland France |
title_short | A 5 m dataset of digital terrain model derivatives across mainland France |
title_sort | 5 m dataset of digital terrain model derivatives across mainland france |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10339187/ https://www.ncbi.nlm.nih.gov/pubmed/37456122 http://dx.doi.org/10.1016/j.dib.2023.109369 |
work_keys_str_mv | AT panhelleuxlea a5mdatasetofdigitalterrainmodelderivativesacrossmainlandfrance AT rapinelsebastien a5mdatasetofdigitalterrainmodelderivativesacrossmainlandfrance AT lemercierblandine a5mdatasetofdigitalterrainmodelderivativesacrossmainlandfrance AT gayetguillaume a5mdatasetofdigitalterrainmodelderivativesacrossmainlandfrance AT hubertmoylaurence a5mdatasetofdigitalterrainmodelderivativesacrossmainlandfrance AT panhelleuxlea 5mdatasetofdigitalterrainmodelderivativesacrossmainlandfrance AT rapinelsebastien 5mdatasetofdigitalterrainmodelderivativesacrossmainlandfrance AT lemercierblandine 5mdatasetofdigitalterrainmodelderivativesacrossmainlandfrance AT gayetguillaume 5mdatasetofdigitalterrainmodelderivativesacrossmainlandfrance AT hubertmoylaurence 5mdatasetofdigitalterrainmodelderivativesacrossmainlandfrance |