植物叶片可见与近红外光谱反射率数据库的建立与主成分分析

可见与近红外波段光谱反射率数据库是颜色科学与技术和遥感目标地物分类识别领域等研究与应用的基础数据。主成分分析(PCA)在光谱数据分析、光谱重建、高光谱数据降维以及遥感图像分类等方面有广泛应用。测量并建立了云南公园常见绿化植物柳树、樟、红花檵木、蓝花楹等48种植物150条叶片从可见光到近红外波段光谱反射率数据库，波长范围400～1 000 nm、间隔4 nm。并且分别对可见与可见到近红外两种波段范围进行PCA研究。结果表明：不同植物叶片按照红、绿、黄相同色相的光谱反射率曲线基本相似；但对于同一种植物，在可见光波段400～700 nm，因为体内叶绿素、叶黄素、叶红素和花青苷含量的不同，光谱反射率曲线有较大的差异；在近红外波段700～1 000 nm，所有植物叶片光谱反射率仅仅是大小不同，而同一植物光谱反射率基本不随波长变化。PCA分析表明：在可见光和可见与近红外波段前三个主成分的累积贡献率分别达到98.62%和94.97%。数据库及其PCA分析结果将为自然物体光谱重建、多光谱成像技术和遥感目标地物分类识别等领域应用提供支撑。

Establishment of Visible and NIR Spectral Reflectance Database of Plant Leaves and Principal Component Analysis

Visible and near-infrared spectral reflectance is the basic database for research and application in color science and technology and remote sensing object classification and recognition.The principal component analysis (PCA) is widely used in spectral data analysis, spectral reconstruction, hyperspectral data dimension reduction, and remote sensing image classification. In this paper, a database of spectral reflectance from visible light to near-infrared of 150 leaves of 48 plants, including Salix, Cinnamomum camphora (L.) Presl, Dracaena marginata, and Jacaranda mimosifolia, etc. Which are common in park greenery of Yunnan, isestablished. The wavelength range from 400 to 1 000 nm with 4 nm intervals. The PCA wascarried out on the visible and from visible to near-infrared wavebands respectively.The measurement results show that the spectral reflectance of different vegetation leaves according to the same hue of red, green and yellow are the same, For the same plant,in the visible waveband, the spectral reflectances are quite different because of the different content of chlorophyll, lutein, carotene and anthocyanin in the body.The spectral reflectance of all plant leaves in the near-infrared waveband is only different in amplitude, while the spectral reflectance of the same plant does not change with wavelength.The PCA shows that the cumulative contribution rates of the first three principal components in the visible and visible near-infrared wavebands reached 98.62% and 94.97% respectively.The database and results of PCA provide support for the spectral reconstruction of natural objects, the multispectral imaging technology and the classification and recognition of the target of remote sensing images.