Hyperspectral data of understory elements in boreal forests: In situ and laboratory measurements

IF 1 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2024-10-24 DOI:10.1016/j.dib.2024.111068
Audrey Mercier, Susanna Karlqvist, Aarne Hovi, Miina Rautiainen
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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.
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北方森林林下要素的高光谱数据:现场和实验室测量
加强对森林要素光谱特性的了解对于解释机载和卫星遥感数据至关重要。本文介绍了通过近距离高光谱测量收集到的两组有关北方森林林下成分光谱特性的数据集。我们于 2023 年 6 月和 7 月在芬兰进行了两次野外活动,使用 ASD FieldSpec 4 光谱仪采集波长为 350 到 2500 nm 的光谱,用于测量林下要素。我们在现场测量了蕨类植物、腐朽木材、普通木荷和五月百合。在实验室中,我们测量了欧洲飞燕草、赤杨和普通榛树的叶子。这些数据有助于分析植被特征、训练分类算法和改进森林辐射传递模型,并可用于评估高光谱数据在区分北方森林林下要素方面的潜力。
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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