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Global forest management data for 2015 at a 100 m resolution

Global forest management data for 2015 at a 100 m resolution

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f6fd5cfdd81b4030a93498cc76b5b243

Global forest management data for 2015 at a 100 m resolution

About this item

Full title

Global forest management data for 2015 at a 100 m resolution

Publisher

London: Nature Publishing Group UK

Journal title

Scientific data, 2022-05, Vol.9 (1), p.199-199, Article 199

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki (
https://www.geo-wiki.org/
). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be use...

Alternative Titles

Full title

Global forest management data for 2015 at a 100 m resolution

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_f6fd5cfdd81b4030a93498cc76b5b243

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f6fd5cfdd81b4030a93498cc76b5b243

Other Identifiers

ISSN

2052-4463

E-ISSN

2052-4463

DOI

10.1038/s41597-022-01332-3

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