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Article . 2022
License: CC BY
Data sources: Datacite
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Article . 2022
License: CC BY
Data sources: ZENODO
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ZENODO
Article . 2022
License: CC BY
Data sources: Datacite
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Detecting peatland vegetation patterns with multi-temporal field spectroscopy

descriptionPublicationkeyboard_double_arrow_right Article 23 Nov 2022Publisher:Zenodo
Authors: Pang, Yuwen;

doi: 10.5281/zenodo.7350306 , 10.5281/zenodo.7350305

Detecting peatland vegetation patterns with multi-temporal field spectroscopy

Abstract

This data support findings in paper, Detecting peatland vegetation patterns with multi-temporal field spectroscopy. The dataset includs vegetaion inventories and multi-temporal field spectrsocopy data, which collected between May and Ocotober in 2019. The data supports the finding of the paper, 'Detecting peatland vegetation patterns with multi-temporal field spectroscopy' , http://dx.doi.org/10.1080/15481603.2022.2152303eng

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Keywords

Multi-temporal spectroscopy, Peatland vegetaion, Random forest

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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.
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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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