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毕业论文网 > 任务书 > 机械机电类 > 机械设计制造及其自动化 > 正文

林木航拍光谱采集与分析任务书

 2022-01-05 21:23:43  

全文总字数:2957字

1. 毕业设计(论文)的内容、要求、设计方案、规划等

(1)前言:植物光谱,指的是植物在光线照射下,其由于叶片吸收和反射而形成的一系列具有特定波长和反射强度的光线谱。

植物光谱用于植物病害检测已有30余年历史,是目前国际主流的植物病害在线和离线检测手段。

航拍光谱是在植物光谱的技术基础上,结合无人机等航拍设备,利用成像技术,对地面区域进行航拍,并对航拍光谱图像进行光谱分析的技术手段,是目前比较先进的对大面积作物进行光谱分析的装备技术。

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2. 参考文献(不低于12篇)

1. Qin J, Burks T F, Ritenour M A, et al. Detection of citrus canker using hyperspectral reflectance imaging with spectral information divergence[J]. Journal of food engineering, 2009, 93(2): 183-191.2. Li X, Lee W S, Li M, et al. Spectral difference analysis and airborne imaging classification for citrus greening infected trees[J]. Computers and Electronics in Agriculture, 2012, 83: 32-46.3. Qin J, Burks T F, Zhao X, et al. Development of a two-band spectral imaging system for real-time citrus canker detection[J]. Journal of Food Engineering, 2012, 108(1): 87-93.4. Dzikiti S, Verreynne J S, Stuckens J, et al. Determining the water status of Satsuma mandarin trees [Citrus Unshiu Marcovitch] using spectral indices and by combining hyperspectral and physiological data[J]. Agricultural and Forest Meteorology, 2010, 150(3): 369-379.5. Lee W S. Spectral sensing of different citrus varieties for precision agriculture[J]. American Society of Agricultural and Biological Engineers, 2006 (061065).6. Sankaran S, Ehsani R. Visible-near infrared spectroscopy based citrus greening detection: Evaluation of spectral feature extraction techniques[J]. Crop Protection, 2011, 30(11): 1508-1513.7. Li H, Lee W S, Wang K, et al. Extended spectral angle mapping (ESAM)for citrus greening disease detection using airborne hyperspectral imaging[J]. Precision Agriculture, 2014, 15(2): 162-183.8. Somers B, Asner G P, Tits L, et al. Endmember variability in spectral mixture analysis: A review[J]. Remote Sensing of Environment, 2011, 115(7): 1603-1616.9. Steuer B, Schulz H, Lger E. Classification and analysis of citrus oils by NIR spectroscopy[J]. Food Chemistry, 2001, 72(1): 113-117.10. Min M, Lee W S. Determination of significant wavelengths and prediction of nitrogen content for citrus[J]. Transactions of the ASAE, 2005, 48(2): 455-461.11. Menesatti P, Antonucci F, Pallottino F, et al. Estimation of plant nutritional status by VisNIR spectrophotometric analysis on orange leaves [Citrus sinensis (L) Osbeck cv Tarocco][J]. Biosystems engineering, 2010, 105(4): 448-454.12. Ye X, Sakai K, Okamoto H, et al. A ground-based hyperspectral imaging system for characterizing vegetation spectral features[J]. Computers and electronics in Agriculture, 2008, 63(1): 13-21.

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