Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution

Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution based on the BIOME 6000 data set (8057 modern pollen-based site reconstructions). Predicted at 250 m using Ensemble Machine Learning and relief and climate variables representing the climate for the last 20+...

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Main Author: Hengl, Tomislav
Format: Text
Language:English
Published: Zenodo 2019
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.3526620
https://zenodo.org/record/3526620
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spelling ftdatacite:10.5281/zenodo.3526620 2023-05-15T14:15:29+02:00 Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution Hengl, Tomislav 2019 https://dx.doi.org/10.5281/zenodo.3526620 https://zenodo.org/record/3526620 en eng Zenodo https://dx.doi.org/10.5281/zenodo.3526619 Open Access Creative Commons Attribution Share Alike 4.0 International https://creativecommons.org/licenses/by-sa/4.0/legalcode cc-by-sa-4.0 info:eu-repo/semantics/openAccess CC-BY-SA potential natural vegetation biome LandGIS OpenLandMap Text Journal article article-journal ScholarlyArticle 2019 ftdatacite https://doi.org/10.5281/zenodo.3526620 https://doi.org/10.5281/zenodo.3526619 2021-11-05T12:55:41Z Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution based on the BIOME 6000 data set (8057 modern pollen-based site reconstructions). Predicted at 250 m using Ensemble Machine Learning and relief and climate variables representing the climate for the last 20+ years. Processing steps are described in detail here . Maps with "_sd_" contain estimated model errors per class. Antartica is not included. Hengl T, Walsh MG, Sanderman J, Wheeler I, Harrison SP, Prentice IC. 2018. Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potential . PeerJ 6:e5457 https://doi.org/10.7717/peerj.5457 To access and visualize maps use: OpenLandMap.org If you discover a bug, artifact or inconsistency in the LandGIS maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://github.com/envirometrix/PNVmaps/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: pnv = theme: potential natural vegetation, biome.type = variable: biome type (e.g. troppical savana), biome00k = classification model: BIOME6000, c = factor, 250m = spatial resolution / block support: 250 m, b0..0cm = vertical reference: land surface, 2000..2017 = time reference: period 2000-2017, v0.2 = version number: 0.2, Text antartic* DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic potential natural vegetation
biome
LandGIS
OpenLandMap
spellingShingle potential natural vegetation
biome
LandGIS
OpenLandMap
Hengl, Tomislav
Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution
topic_facet potential natural vegetation
biome
LandGIS
OpenLandMap
description Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution based on the BIOME 6000 data set (8057 modern pollen-based site reconstructions). Predicted at 250 m using Ensemble Machine Learning and relief and climate variables representing the climate for the last 20+ years. Processing steps are described in detail here . Maps with "_sd_" contain estimated model errors per class. Antartica is not included. Hengl T, Walsh MG, Sanderman J, Wheeler I, Harrison SP, Prentice IC. 2018. Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potential . PeerJ 6:e5457 https://doi.org/10.7717/peerj.5457 To access and visualize maps use: OpenLandMap.org If you discover a bug, artifact or inconsistency in the LandGIS maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://github.com/envirometrix/PNVmaps/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: pnv = theme: potential natural vegetation, biome.type = variable: biome type (e.g. troppical savana), biome00k = classification model: BIOME6000, c = factor, 250m = spatial resolution / block support: 250 m, b0..0cm = vertical reference: land surface, 2000..2017 = time reference: period 2000-2017, v0.2 = version number: 0.2,
format Text
author Hengl, Tomislav
author_facet Hengl, Tomislav
author_sort Hengl, Tomislav
title Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution
title_short Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution
title_full Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution
title_fullStr Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution
title_full_unstemmed Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution
title_sort potential distribution of biomes (potential natural vegetation) at 250 m spatial resolution
publisher Zenodo
publishDate 2019
url https://dx.doi.org/10.5281/zenodo.3526620
https://zenodo.org/record/3526620
genre antartic*
genre_facet antartic*
op_relation https://dx.doi.org/10.5281/zenodo.3526619
op_rights Open Access
Creative Commons Attribution Share Alike 4.0 International
https://creativecommons.org/licenses/by-sa/4.0/legalcode
cc-by-sa-4.0
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY-SA
op_doi https://doi.org/10.5281/zenodo.3526620
https://doi.org/10.5281/zenodo.3526619
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