The reference data for accuracy assessment of the Global Forest Watch tree cover 2000 in China

Remote-sensing products have emerged as key tools in forest cover monitoring. Their quality vary spatially, local validations are recommended before using the data for inventory and management tasks. We conducted a validation based on a visual interpretation procedure using high-resolution optical i...

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Detalles Bibliográficos
Autores principales: Zhang, Di, Wang, Hao, Wang, Xu, Lü, Zhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Agricultural and Biological Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7033316/
https://www.ncbi.nlm.nih.gov/pubmed/32149165
http://dx.doi.org/10.1016/j.dib.2020.105238
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author Zhang, Di
Wang, Hao
Wang, Xu
Lü, Zhi
author_facet Zhang, Di
Wang, Hao
Wang, Xu
Lü, Zhi
author_sort Zhang, Di
collection PubMed
description Remote-sensing products have emerged as key tools in forest cover monitoring. Their quality vary spatially, local validations are recommended before using the data for inventory and management tasks. We conducted a validation based on a visual interpretation procedure using high-resolution optical imagery on Google Earth to map the uncertainties and inaccuracies of Global Forest Watch (GFW) Tree Cover 2000 in China. The article provides the reference dataset applied in Zhang et al. (2020). The reference data has a total amount of 96 364 sample pixels collected using spatially stratified random sampling method. The samples were labelled with land use classifications and can provide further usage for remote sensing products.
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spelling pubmed-70333162020-03-06 The reference data for accuracy assessment of the Global Forest Watch tree cover 2000 in China Zhang, Di Wang, Hao Wang, Xu Lü, Zhi Data Brief Agricultural and Biological Science Remote-sensing products have emerged as key tools in forest cover monitoring. Their quality vary spatially, local validations are recommended before using the data for inventory and management tasks. We conducted a validation based on a visual interpretation procedure using high-resolution optical imagery on Google Earth to map the uncertainties and inaccuracies of Global Forest Watch (GFW) Tree Cover 2000 in China. The article provides the reference dataset applied in Zhang et al. (2020). The reference data has a total amount of 96 364 sample pixels collected using spatially stratified random sampling method. The samples were labelled with land use classifications and can provide further usage for remote sensing products. Elsevier 2020-02-01 /pmc/articles/PMC7033316/ /pubmed/32149165 http://dx.doi.org/10.1016/j.dib.2020.105238 Text en © 2020 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 Agricultural and Biological Science
Zhang, Di
Wang, Hao
Wang, Xu
Lü, Zhi
The reference data for accuracy assessment of the Global Forest Watch tree cover 2000 in China
title The reference data for accuracy assessment of the Global Forest Watch tree cover 2000 in China
title_full The reference data for accuracy assessment of the Global Forest Watch tree cover 2000 in China
title_fullStr The reference data for accuracy assessment of the Global Forest Watch tree cover 2000 in China
title_full_unstemmed The reference data for accuracy assessment of the Global Forest Watch tree cover 2000 in China
title_short The reference data for accuracy assessment of the Global Forest Watch tree cover 2000 in China
title_sort reference data for accuracy assessment of the global forest watch tree cover 2000 in china
topic Agricultural and Biological Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7033316/
https://www.ncbi.nlm.nih.gov/pubmed/32149165
http://dx.doi.org/10.1016/j.dib.2020.105238
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