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  5. More than one quarter of Africa's tree cover found outside areas previously classified as forest

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Preprint
English
2022

More than one quarter of Africa's tree cover found outside areas previously classified as forest

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English
2022
Research Square (Research Square)
DOI: 10.21203/rs.3.rs-1816495/v2

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Compton Tucker
Compton Tucker

NASA Goddard Space Flight Center

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Florian Reiner
Martin Brandt
Xiaoye Tong
+21 more

Abstract

The consistent monitoring of trees both inside and outside of forests is key to mitigating climate change. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we make use of the PlanetScope nanosatellite constellation, which delivers global very high-resolution daily imagery, to map both forest and non-forest tree cover for continental Africa using images from a single year. Our prototype map of 2019 demonstrates that a precise assessment of all tree-based systems is possible at continental scale, and reveals that 29% of tree cover is found outside areas previously classified as tree cover, such as in croplands and grassland. Such accurate mapping of tree cover at metric resolution down to the level of individual trees and consistent among countries has the potential to redefine land use impacts, move beyond the need for forest definitions, build the basis for natural climate solutions, and provide a new scientific basis for tree related studies.

How to cite this publication

Florian Reiner, Martin Brandt, Xiaoye Tong, David L. Skole, Ankit Kariryaa, Philippe Ciais, Andrew B. Davies, Pierre Hiernaux, Jérôme Chave, Maurice Mugabowindekwe, Christian Igel, Stefan Oehmcke, Fabian Gieseke, Sizhuo Li, Siyu Liu, Sassan Saatchi, Peter Boucher, Jenia Singh, Simon Taugourdeau, Morgane Dendoncker, Xiao‐Peng Song, Ole Mertz, Compton Tucker, Rasmus Fensholt (2022). More than one quarter of Africa's tree cover found outside areas previously classified as forest. Research Square (Research Square), DOI: 10.21203/rs.3.rs-1816495/v2.

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Publication Details

Type

Preprint

Year

2022

Authors

24

Datasets

0

Total Files

0

Language

English

Journal

Research Square (Research Square)

DOI

10.21203/rs.3.rs-1816495/v2

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