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ZENODO
Dataset . 2023
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
Data sources: ZENODO
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Africa tree cover map

Authors: Reiner, Florian; Brandt, Martin; Tong, Xiaoye; Skole, David; Kariryaa, Ankit; Ciais, Philippe; Davies, Andrew; +17 Authors

Africa tree cover map

Abstract

Data description This file is a 100 m resolution map of % tree canopy cover per pixel for Africa in 2019. Tree cover values range from 0-100 % and nodata areas are masked as -1. The map is derived from predictions of tree cover using 3 m PlanetScope imagery, which were resampled to 1 m, and then aggregated to 100 m. Predictions at 1 m resolution (or anything between 1 and 100 m) are available on request. The image data was processed from raw scenes into merged 1x1 degree mosaics. Differences in the quality of raw scenes and processed mosaics can lead to artifacts in the predicted tree cover, visible as seamlines along scene or mosaic edges. Therefore the current version of this map should not be seen as a final product representing the exact tree cover at each location, but as a proof of concept of what is possible with PlanetScope data. The main benefit of this map is the inclusion of cover from scattered single trees in sparse cover areas such as savannahs. Here it can serve as a complement to existing forest cover maps to extend the mapping to include non-forest trees. License This tree cover map is made freely available for non-commercial purposes. All usage of the data must be attributed and should be cited with the paper citation. Please see the NICFI license for full terms of usage, available at: https://assets.planet.com/docs/Planet_ParticipantLicenseAgreement_NICFI.pdf Version differences We recommend to always use the latest version. We are continuously improving the quality and consistency of the tree cover mapped, and are expecting to release regular version updates, based on an improved model and mosaics. We also plan to release different years in the future. Version 0.1: ps_africa_treecover_2019_100m_v0.1 This version was used for the analyses in the paper. It used the first version of the mosaics, which suffered from the inclusion of lower-quality scenes and missing data. Known issues - missing data coverage: incomplete mosaics and mosaics missing scenes - inconsistent predictions between mosaics: visible mosaic edges, see Zimbabwe - underprediction in very sparse cover areas - overprediction of cover in denser shrublands - overprediction (artifacts) in mountains, desert dunes, croplands and some urban areas - flowering trees in closed forests are mapped as gaps - occasional confusion between understory or shrubs and trees in wood- and shrublands Version 1.0: ps_africa_treecover_2019_100m_v1.0 This is the latest version available as of March 2023. It is based on improved mosaics and a revised model, leading to better consistency both between and within mosaics. However the current model underpredicts solid tree cover in shrublands and woodlands, leading to an overall underprediction in lower rainfall areas. Improvements over v0.1: - improved mosaic quality - reduced artifacts in croplands and urban areas (though some remain) - better consistency of forest area mapping - better detection rate of small trees in dry areas Known issues - underprediction of tree clusters in shrublands - some (few) false predictions of small trees in dry areas - occasional inconsistent predictions within mosaics: seamlines along scene edges - areas of underprediction in dense tropical forest due to lower quality scenes, see DRC - overprediction (artifacts) in mountains, and occasionally desert dunes - flowering trees in closed forests are mapped as gaps - occasional confusion between understory or shrubs and trees in wood- and shrublands - trees without leaves may not be mapped correctly

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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