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张爱武,张泰配,康孝岩,郭超凡.高光谱成像分析植物叶片滞尘前后光谱特征变化[J].农业工程学报,2018,34(19):170-176.DOI:10.11975/j.issn.1002-6819.2018.19.022
高光谱成像分析植物叶片滞尘前后光谱特征变化
投稿时间:2018-05-10  修订日期:2018-09-03
中文关键词:  灰尘  光谱分析  植物  滞尘  高光谱图像  叶片光谱
基金项目:国家自然科学基金(41571369);国家重点研发计划项目(2016YFB0502500);北京市自然科学基金(4162034);青海省科技计划项目(2016-NK-138)
作者单位
张爱武 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 1000482. 首都师范大学 空间信息技术教育部工程研究中心北京 100048 
张泰配 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 1000482. 首都师范大学 空间信息技术教育部工程研究中心北京 100048 
康孝岩 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 1000482. 首都师范大学 空间信息技术教育部工程研究中心北京 100048 
郭超凡 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 1000482. 首都师范大学 空间信息技术教育部工程研究中心北京 100048 
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中文摘要:灰霾的监测与治理是迫切需要解决的问题,分析植被叶片滞尘前后的光谱变化特征是灰霾监测的一种有效方式。植物叶片具有吸附空气颗粒物的能力。该文通过获取10种常见树木叶片10月和11月连续26 d的高光谱图像,对比分析每种叶片滞尘前后的光谱特征变化情况,得出滞尘前后叶片光谱变化的基本趋势:1)10种叶片变化趋势基本一致,10种叶片滞尘前后光谱变化明显的区间均表现在500~550 nm、550~700 nm、730~760 nm波段内;2)滞尘前后的叶片红边位置并没有发生改变,滞尘没有对叶片内部生理结构构成影响;3)金露梅和二球悬铃木在765 nm波段处的光谱响应与其它树种存在很大差异;白杜、金银忍冬、紫薇和玉兰在550~570 nm波段区间对于滞尘的敏感度较弱。研究为大气降尘的监测以及灰霾的治理提供应用参考。为进一步通过高光谱探测灰霾典型成分提供理论支撑。
Zhang Aiwu,Zhang Taipei,Kang Xiaoyan,Guo Chaofan.Changes of spectral characteristics of plant leaves before and after dust-retention under hyperspectral imaging[J].Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE),2018,34(19):170-176.DOI:10.11975/j.issn.1002-6819.2018.19.022
Changes of spectral characteristics of plant leaves before and after dust-retention under hyperspectral imaging
Author NameAffiliation
Zhang Aiwu 1. Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China
2. Engineering Research Center of Spatial Information Technology, Ministry of Education, Capital Normal University, Beijing 100048, China 
Zhang Taipei 1. Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China
2. Engineering Research Center of Spatial Information Technology, Ministry of Education, Capital Normal University, Beijing 100048, China 
Kang Xiaoyan 1. Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China
2. Engineering Research Center of Spatial Information Technology, Ministry of Education, Capital Normal University, Beijing 100048, China 
Guo Chaofan 1. Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China
2. Engineering Research Center of Spatial Information Technology, Ministry of Education, Capital Normal University, Beijing 100048, China 
Key words:dust  spectrum analysis  plants  dust retention  hyperspectral imaging  leaf spectrum
Abstract: In recent years, due to the influence of natural and human factors, air pollution has become one of the serious problems in the world, which affects people’s life, physical and mental health and daily production. So this paper tried to address this problem by the monitoring and governance of haze. Analyzing the spectral characteristics of vegetation leaves before and after dust retention is an effective way to monitor haze. Plant leaves have the ability to adsorb airborne particles. By comparing the spectral curves of plant leaves before and after dust detention, it provides a scientific basis for the control of haze. In this study, the leaves of 10 common trees were collected for 26 consecutive days in October and November. Ten common tree species included Holly, Chinese rose, Platanus acerifolia, Ginkgo, Potentilla fruticosa, Lilac, Euonymus maackii, Lonicera maackii, Lagerstroemia indica and Magnolia. The hyperspectral image of leaf before and after dust retention was obtained by the hyperspectral imaging device developed by our research group. The hyperspectral image is segmented by thresholding method, and the average spectral curve of the whole leaf is extracted. The comparison of 10 kinds of leaves before and after dust retention was performed, excluding the influence of water, internal structure, and so on, and controlling dust to be the single variable. The changes of spectral characteristics of a single leaf, a variety of spectral characteristics of leaves, and the spectral differences before and after dust retention were analyzed. The basic trends of spectral changes of leaves before and after dust retention were obtained: 1) The variation trend of 10 kinds of leaves was basically the same, and the obvious spectrum changes of them before and after the dust retention were in the 500-550, 550-700 and 730-760 nm bands. 2) There was no change in the position of the red edge of the leaves before and after the dust retention, and the dust retention did not affect the internal physiological structure of the leaves. 3) The spectral response at the 765 nm band of Potentilla fruticosa and Platanus acerifolia differed greatly from other tree species; Euonymus maackii, Lonicera maackii, Lagerstroemia indica, and Magnolia had less sensitivity to dust retention in the 550-570 nm band. The spectral curves of 10 species of leaves were compared and analyzed from 3 aspects: Single leaf spectral characteristics, multiple leaf spectral characteristics, and spectral difference before and after dust retention. The spectral curves of 10 species of leaves were consistent with typical vegetation spectral curves; the spectral reflectance curves of 10 species changed obviously before and after dust retention, and the variation ranges were different, which indicated that different species had different sensitivity to dust retention. The study provides reference for monitoring atmospheric dustfall and controlling haze, and also provides theoretical support for further hyperspectral detection of typical components of haze.
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