光谱学与光谱分析, 2013, 33 (10): 2715, 网络出版: 2013-10-23  

在滞尘影响下的植被叶片光谱变化特征研究

Impact of Dust-Fall on Spectral Features of Plant Leaves
罗娜娜 1,2,*赵文吉 1,2晏星 3
作者单位
1 首都师范大学三维信息获取与应用教育部重点实验室, 北京100048
2 首都师范大学资源环境与地理信息系统北京市重点实验室, 北京100048
3 香港理工大学土地测量及地理资讯学系, 中国 香港
摘要
为建立以高光谱数据为基础的叶片滞尘质量反演模型, 沿北京市区采集了30个大叶黄杨叶片样本。 利用电子分析天平和光谱仪(analytical spectral devices ASD FieldSpec Pro)测定“除尘前”与“除尘后”叶片质量及光谱反射率曲线, 以获取叶片尘埃量、 光谱信息等数据。 随后以传统意义和偏最小二乘(PLS)回归模型为基础, 以探究空气尘埃量与光谱曲线之间可能存在的关系, 阐述了叶片尺度上尘埃量对植物光谱特征的影响。 结果为: 除尘前后叶片光谱曲线在350~700, 780~1 300, 1 900~2 500 nm波段区间内有较大差异, 同时尘埃量与叶片单波段光谱反射率比值呈负相关, 相关度最大值点为737波段, 属于近红外波段, 相关系数可达-0.8左右。 在尘埃量与叶片光谱多波段组合关系研究中得到, 948和945波段构成的NDVI指数与尘埃量的相关度最大, 相关系数可达0.76。 在叶片滞尘量反演研究中, 对比传统意义滞尘量回归模型, 引进的偏最小二乘算法(PLS)可使叶片滞尘量反演精度略有提高, 最后由回归模型精度评定可得偏最小二乘法反演效果较传统回归好。
Abstract
In order to build inversion model of dust-fall weight by hyperspectral data, 30 samples were collected in Beijing. Through electronic balance and Analytical Spectral Devices FieldSpec Pro (ASD) analysis, the “dust leaves” and the “clean leaves” weight and spectral reflectance were determined respectively, which also obtained information of dust weight and spectral features. Then, based on tradition and partial least squares (PLS) model’s analysis, the relationship between dust weight and spectral reflectance was explored. The results showed that 350~700, 780~1 300 and 1 900~2 500 nm bands had apparently variations when they response to the different dust weights. In general, there was a negative relationship between dust weight and spectral reflectance, the maximum negative value -0.8 occurred at 737 band which belonged to near-infrared bands. In the analysis of dust weight with multi-band, it was indicated that NDVI index which was formed by 948 and 945 bands had a significant correlation (r=0.76) to dust. Finally, through accuracy assessment of regression model, the PLS could obtain a more accurate result than the traditional model.

罗娜娜, 赵文吉, 晏星. 在滞尘影响下的植被叶片光谱变化特征研究[J]. 光谱学与光谱分析, 2013, 33(10): 2715. LUO Na-na, ZHAO Wen-ji, YAN Xing. Impact of Dust-Fall on Spectral Features of Plant Leaves[J]. Spectroscopy and Spectral Analysis, 2013, 33(10): 2715.

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