Abstract
Enhancing our understanding of the spectral properties of forest elements is essential for interpreting airborne and satellite-borne remote sensing data. This article presents two datasets on the spectral properties of understory elements in boreal forests collected with close-range hyperspectral measurements. We conducted two field campaigns in June and July 2023 in Finland to acquire spectral measurements at wavelengths from 350 to 2500 nm using an ASD FieldSpec 4 spectrometer for forest understory elements. We measured ferns, decaying wood, common wood sorrel and May lily in situ. In a laboratory, we measured leaves from European fly honeysuckle, alder buckthorn and common hazel. These data support the analysis of vegetation characteristics, training of classification algorithms and improvement of forest radiative transfer models, and could be used to evaluate the potential of hyperspectral data to discriminate the understory elements of boreal forest.
Original language | English |
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Article number | 111068 |
Number of pages | 8 |
Journal | Data in Brief |
Volume | 57 |
DOIs | |
Publication status | Published - Dec 2024 |
MoE publication type | A1 Journal article-refereed |
Keywords
- Alder buckthorn
- Common hazel
- Decaying wood
- European fly honeysuckle
- Ferns
- Maianthemum bifolium
- Reflectance and transmittance factors
- Wood sorrel
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Dive into the research topics of 'Hyperspectral data of understory elements in boreal forests : In situ and laboratory measurements'. Together they form a unique fingerprint.Datasets
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Leaf spectra of alder buckthorn, common hazel and European fly honeysuckle
Mercier, A. (Creator), Karlqvist, S. (Contributor), Hovi, A. (Contributor) & Rautiainen, M. (Contributor), Mendeley Data, 6 Oct 2023
DOI: 10.17632/3bkrwhk4p3.1, https://data.mendeley.com/datasets/3bkrwhk4p3
Dataset
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Reflectance spectra of boreal forest floor elements: ferns, herbaceous plants and decaying wood
Mercier, A. (Creator), Karlqvist, S. (Contributor), Hovi, A. (Contributor) & Rautiainen, M. (Contributor), Mendeley Data, 6 Oct 2023
DOI: 10.17632/dddb2prk4p.1, https://data.mendeley.com/datasets/dddb2prk4p
Dataset