A new dataset of leaf optical traits to include biophysical parameters in addition to spectral and biochemical assessment

IF 11.1 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES
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引用次数: 0

Abstract

To enable future improvement on current leaf optical property models, more data incorporating a larger range of measured properties is needed. To this end, a dataset was collected to associate spectral measurements (ultraviolet, visible, and near infrared) with biochemical and biophysical properties of leaves. The leaves represented in this dataset were selected to provide a more comprehensive representation of both tree and agricultural species as well as leaves with a wide variety of color (pigment) expression, surface characteristics, and stages in a leaf lifecycle. Extensive data were collected for each of the 290 leaf samples studied in this project including multiple spectral measurement orientations and ranges, biochemical assessment, and biophysical assessment of that has not previously been a focus in other leaf datasets. The methods and results associated with this dataset are described in this work.

Abstract Image

新的叶片光学特征数据集,除光谱和生化评估外,还包括生物物理参数
为了在未来改进当前的叶片光学特性模型,需要更多的数据,包括更大范围的测量特性。为此,我们收集了一个数据集,将光谱测量结果(紫外线、可见光和近红外)与叶片的生物化学和生物物理特性联系起来。该数据集所代表的叶片经过挑选,更全面地代表了树木和农业物种,以及具有各种颜色(色素)表现、表面特征和叶片生命周期阶段的叶片。在本项目研究的 290 个叶片样本中,每个样本都收集了大量数据,包括多个光谱测量方向和范围、生化评估以及生物物理评估,而这些在其他叶片数据集中都不是重点。本作品介绍了与该数据集相关的方法和结果。
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来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
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