[2] Lin Wenpeng, Wang Changyao, Chu Deping, et al.. Extraction of fall crop types based on spectral analysis[J]. Transactions of the Chinese Society of Agricultural Engineering, 2006, 22(9): 128-132.
[3] Guo Lin, Wang Fei, Zhang Yin, et al.. Design and implementation of business management system for crop remote sensing monitoring[J]. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(3): 132-138.
[4] Hardeberg J Y, Schmitt F, Brettel H. Multispectral color image capture using a liquid crystal tunable filter[J]. Opt Eng, 2002, 41(10): 2532-2548.
[6] Zjakic I, Parac-Osterman D, Bates I. New approach to metamerism measurement on halftone color images[J]. Measurement, 2011, 44(8): 1441-1447.
[7] Steidley C, Bachnak R, Dannelly R S, et al.. A multi-spectral imaging system for geo-spatial applications[J]. J Computational Methods in Sciences and Engineering, 2005, 5(1 suppl): S93-S109.
[8] Wang H C, Tsai M T, Chiang C P. Visual perception enhancement for detection of cancerous oral tissue by multi-spectral imaging[J]. J Optics, 2013, 15(5): 055301.
[9] Chen Rongrong, Zhou Zhiguo, Cao Weixing, et al.. Spatial variability and quantitative analysis of field factors based on GIS[J]. Chinese J Applied Ecology, 2004, 15(9): 1678-1680.
[10] Ya Huiyuan, Li Weitao, Wang Weidong, et al.. Cluster analysis of some common gramineous plants based on the sequences of EF1-a[J]. J Zhengzhou University, 2012, 44(2): 108-113.
[11] Jiang Lili, Qi Qingwen, Zhang An. Grid-based precision agriculture database and its demonstrative application: taking Shuangshan Farm in Heilongjiang Province as an example[J]. J Geo-Information Science, 2011, 13(6): 804-809.
[12] Feng Jie, Li Hongning, Liu Wei, et al.. Extract spectral feature bands of pseudoperonospora cubensis′s narrow-band multispectral images using brightness[J]. Chinese J Lasers, 2011, 38(s1): s109003.
[13] Jiang Xiaoguang, Wang Changyao, Wang Cheng. Optimum band selection of hyperspectrral remote sensing data[J]. Arid Land Geography, 2000, 23(3): 214-220.
[14] Yang A, Cao T, Li R F, et al.. A hybird gene selection method for cancer classification based on clustering algorithm and Euclidean distance[J]. J Computational and Theoretical Nanoscience, 2012, 9(4): 611-615.