Monitoring Tobacco Canopy Growth Status Based on Hyperspectral Fractal Analysis
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摘要: 植被高光谱反射曲线包含着植被生长状况的众多信息。本文通过使用野外光谱仪进行野外测量，得到烟草冠层不同生育期以及不同健康状况的反射光谱曲线。并在分析光谱特征参数如红边位置、红边面积、绿峰反射高度的基础上，利用分形理论对反射光谱曲线进行分形测量并用分形维数定量反映其健康状况。结果表明：（1）分形维数随着烟草的生长发育呈现先升高后降低的趋势，这与3个光谱参数的变化基本吻合；（2）分形维数与红边位置、红边面积、绿峰反射高度均成正相关关系，其相关系数分别为0.77、0.91和0.88；（3）病害烟草冠层光谱曲线的分形维数明显小于健康烟草冠层。因此，分形维数能够作为一个新的综合参数来客观反映烟草冠层所处的健康状况，为烟草生长状况监测提供科学依据。
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关键词:
- 健康状况
Abstract: Vegetation growth information is mostly represented by hyperspectral reflective curves. In this paper, lots of canopy spectral curves were generated using AvaSpec-4 optical spectrum instrument in order to describe the different growth stage and health status of tobacco. On the basis of analyzing the spectral characteristic parameters such as the red edge position, the area of the red edge, and the height of the green peak, the fractal theory were used to measure the fractal dimensions of the reflective spectral curves in order to analyze the health status of tobacco. The results show that (1) the fractal dimension presents a trend of decrease after the first increase along with the growing of tobacco, and it is in accordance with the change of the three spectral characteristic parameters, (2) fractal dimension has a positive correlation with the three characteristic parameters, and the correlation coefficient is 0.77, 0.91, 0.88 respectively, (3) the fractal dimension of the unhealthy tobacco is lower than the normal obviously. So, the fractal dimension of hyperspectral curve can serve as a new comprehensive parameter to analyze quantitatively the health status of tobacco and provide a scientific basis for growing situation monitoring of tobacco.-
Keywords:
- Healthy status
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[11]鲁植雄，姜春霞等. 土壤表面分形维数计算方法的对比与分析[J]. 中国科技论文在线精品论文，2013，6(19):1840-1848.
[12]Zallen R. The physics of amorphous solids [M]. New York：John Wiley & Sons，1983.[1]王梅. 病害烟草的高光谱特征及其病害程度诊断模型研究[D]. 泰安:山东农业大学硕士学位论文, 2013.
[2]Yang, H.，Zhang, J.，Van Der Meer, F. Spectral characteristics of wheat associated with hydrocarbon micro-seepages [J]. Remote Sensing, 1999, 20(4): 807-813.
[3]李向阳. 烟草高光谱特性与农艺生理品质指标的关系和估测模型研究[D]. 郑州: 河南农业大学硕士学位论文, 2007.
[4]Gilabert, M. A.，Gandia, S.，Melia, J. Analysis of spectral-biophysical Relationships for a Corn Canopy[J]. Remote Sensing of Environment, 1996,55(1):11-20.
[5]乔红波,蒋金炜等. 烟蚜为害特征的高光谱比较[J]. 昆虫知识, 2007, 44(1): 59-60.
[6]刘国顺,李向阳等. 利用冠层光谱估测烟草叶面积指数和地上生物量[J]. 生态学报, 2007, 27(5):1765-1766.
[7]李佛琳. 基于光谱的烟草生长于品质监测研究[D]. 南京:南京农业大学博士学位论文，2006.
[8]杜华强,金伟等. 用高光谱曲线分形维数分析植被健康状况[J]. 光谱学与光谱分析，2009，29(8): 2136-2140.
[9]吴继友,杨旭东,张福军,等. 山东招远金矿区赤松针叶反射光谱红边的季节特征[J]. 遥感学报,1997, 5(2):124-128.
[10]张小全. 广东南雄烟区主要气候因素与烤烟品质特点分析[J]. 西北农业学报, 2011，20(3):75-80.
[11]鲁植雄，姜春霞等. 土壤表面分形维数计算方法的对比与分析[J]. 中国科技论文在线精品论文，2013，6(19):1840-1848.
[12]Zallen R. The physics of amorphous solids [M]. New York：John Wiley & Sons，1983.
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