First spectral reflectance dataset of a highly invasive and aggressive alien plant species, Equisetum hyemale (snakegrass), in South Africa: Towards early detection and effective eradication

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-04-28 DOI:10.1016/j.dib.2025.111582

Lesibana Sedibana , Mahlatse Kganyago , Thulisile Jaca , Kowiyou Yessoufou

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引用次数: 0

Abstract

This paper presents the first spectral reflectance dataset of snakegrass (Equisetum hyemale L.) invasive alien species recorded in South Africa. A total of 338 plant specimens were collected in Howick, KwaZulu-Natal province, and carefully stored in a cooler box for less than 24 hours of collection to retain the structural and biochemical state of the specimens and their overall characteristics. Then, spectral reflectance measurements were collected under laboratory conditions using the PSR-300 Spectral Evolution full-range spectrometer, equipped with a bifurbucated cable, a leaf clip and an artificial lighting system. Next, spectral preprocessing was performed in R statistical software to remove noisy spectra and regions and perform averaging per sample. The dataset is critical for early detection of the species and spatial distribution mapping using remotely piloted systems and earth observation satellites, providing essential information for aiding containment and eradication efforts.

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南非高度入侵和侵略性外来植物——蛇草（Equisetum hyemale）的首个光谱反射数据集：面向早期发现和有效根除

本文首次建立了南非外来入侵种蛇草（Equisetum hyemale L.）的光谱反射数据集。在夸祖鲁-纳塔尔省豪威克采集了338份植物标本，并将其小心地保存在冷却箱中，收集时间少于24小时，以保留标本的结构和生化状态及其整体特征。然后，在实验室条件下，使用PSR-300光谱进化全量程光谱仪，配备分岔电缆，叶片夹和人工照明系统，收集光谱反射率测量数据。然后，在R统计软件中进行光谱预处理，去除有噪声的光谱和区域，并对每个样本进行平均。该数据集对于利用遥控系统和地球观测卫星早期发现物种和绘制空间分布地图至关重要，为协助遏制和根除工作提供了重要信息。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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.