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New global high-resolution centerlines dataset of selected river systems
We present the first high resolution (1:20,000) river centerlines shapefiles from 50 large rivers across the world. Rivers were selected based on the criteria of having more than 1000 km length and which have been reported to have a significant contribution to global fishery production. Since large...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6153272/ https://www.ncbi.nlm.nih.gov/pubmed/30258958 http://dx.doi.org/10.1016/j.dib.2018.09.016 |
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author | Basher, Zeenatul Lynch, Abigail J. Taylor, William W. |
author_facet | Basher, Zeenatul Lynch, Abigail J. Taylor, William W. |
author_sort | Basher, Zeenatul |
collection | PubMed |
description | We present the first high resolution (1:20,000) river centerlines shapefiles from 50 large rivers across the world. Rivers were selected based on the criteria of having more than 1000 km length and which have been reported to have a significant contribution to global fishery production. Since large rivers often span multiple countries, the degree of changes (i.e., anthropogenic or climate derived) varies from region to region. These high-resolution layers were developed to enable researchers to delineate accurate river length, from headwaters regions to their delta and assess or visualize the ongoing changes more accurately in these river systems. Further, these polylines could be used in coordination with satellite derived environmental or landscape variables for ecological research (e.g. predicting biodiversity, estimating biomass). |
format | Online Article Text |
id | pubmed-6153272 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-61532722018-09-26 New global high-resolution centerlines dataset of selected river systems Basher, Zeenatul Lynch, Abigail J. Taylor, William W. Data Brief Earth and Planetary Science We present the first high resolution (1:20,000) river centerlines shapefiles from 50 large rivers across the world. Rivers were selected based on the criteria of having more than 1000 km length and which have been reported to have a significant contribution to global fishery production. Since large rivers often span multiple countries, the degree of changes (i.e., anthropogenic or climate derived) varies from region to region. These high-resolution layers were developed to enable researchers to delineate accurate river length, from headwaters regions to their delta and assess or visualize the ongoing changes more accurately in these river systems. Further, these polylines could be used in coordination with satellite derived environmental or landscape variables for ecological research (e.g. predicting biodiversity, estimating biomass). Elsevier 2018-09-11 /pmc/articles/PMC6153272/ /pubmed/30258958 http://dx.doi.org/10.1016/j.dib.2018.09.016 Text en © 2018 The Authors http://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 | Earth and Planetary Science Basher, Zeenatul Lynch, Abigail J. Taylor, William W. New global high-resolution centerlines dataset of selected river systems |
title | New global high-resolution centerlines dataset of selected river systems |
title_full | New global high-resolution centerlines dataset of selected river systems |
title_fullStr | New global high-resolution centerlines dataset of selected river systems |
title_full_unstemmed | New global high-resolution centerlines dataset of selected river systems |
title_short | New global high-resolution centerlines dataset of selected river systems |
title_sort | new global high-resolution centerlines dataset of selected river systems |
topic | Earth and Planetary Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6153272/ https://www.ncbi.nlm.nih.gov/pubmed/30258958 http://dx.doi.org/10.1016/j.dib.2018.09.016 |
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