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中药资源调查是中药资源保护和利用的首要问题,实时准确地监测药用植物种类和覆盖面积对药用植物物种多样性研究和生态环境的可持续发展具有重要意义。花期是遥感识别物种的关键时期,花期具有独特的光谱特征,相比营养生长期通过花更容易识别物种。红花作为新疆地区主要的经济和药用植物,已受到广泛关注。该文于2011年7月在新疆昌吉地区的红花栽培样地对红花冠层以及红花样地边缘的高光谱测定,得到红花冠层、采摘过后剩下的红花冠层、红花样地边缘及红花叶片光谱反应曲线。通过对其冠层光谱特征分析,发现红花冠层以及采摘过后剩下的红花冠层有特征吸收峰,且存在于770 nm附近;通过光谱分析发现红花冠层光谱与红花地边缘的光谱存在显著差异。一阶导数以及反高斯模型研究表明红花冠层能满足植被光谱基本特征的同时又与红花样地边缘植被冠层存在显著的差异。该文提出的方法旨在研究红花的高光谱特征,为监测红花的生长状态和生理参数提供前期的理论基础,为今后红花的分布面积估算及动态精细监测做铺垫。
The investigation of traditional Chinese medicine resources is the most important issue for the conservation and utilization of traditional Chinese medicine resources. It is of great significance to monitor the species and coverage of medicinal plants in real time and accurately for the study of species diversity of medicinal plants and the sustainable development of ecological environment. Flowering is the key period for remote sensing to identify species. Flowering has unique spectral features that identify species more easily than flowers during vegetative growth. As a major economic and medicinal plant in Xinjiang, safflower has received widespread attention. In this paper, in July 2011 in Changji, Xinjiang, cultivated sample plots of safflower canopy and safflower sample edge of the hyperspectral obtained by safflower canopy, after picking the saffron, safflower sample edge and Spectral response curve of safflower leaves. Through the analysis of its canopy spectral characteristics, it was found that there were characteristic absorption peaks of safflower canopy and the remaining safflower canopy after picking, and existed in the vicinity of 770 nm. The spectrum of safflower canopy and safflower was found by spectral analysis Significant differences. The first derivative and the inverse Gaussian model show that safflower can meet the basic characteristics of vegetation spectra, while there is a significant difference with the safflower edge vegetation canopy. The method proposed in this paper aims to study the hyperspectral characteristics of safflower, provide the pre-theoretical basis for monitoring the growth status and physiological parameters of safflower, and pave the way for future estimation of safflower distribution area and dynamic fine monitoring.