• Journal of Atmospheric and Environmental Optics
  • Vol. 15, Issue 2, 117 (2020)
Yuhong MIAO1、2、*, Min YANG3, and Guojun WU1、2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • show less
    DOI: 10.3969/j.issn.1673-6141.2020.02.005 Cite this Article
    MIAO Yuhong, YANG Min, WU Guojun. Sophisticated Vegetation Classification Based on Multi-Dimensional Features of Hyperspectral Image[J]. Journal of Atmospheric and Environmental Optics, 2020, 15(2): 117 Copy Citation Text show less
    References

    [1] Chen Dan. Vegetation Classification Based on the HIS Hyperspectral Data of HJ-IA Satellite [D]. Nanjing: Master Thesis of Nanjing Agricultural University of China, 2012 (in Chinese).

    [2] Pu Ruiliang, Gong Peng. Hyperspectral Remote Sensing and Its Application [M]. Beijing: Higher Education Press, 2000 (in Chinese).

    [3] Liang Zhilin, Zhang Liyan, Zeng Xianling, et al. Hyperspectral remote sensing for urban vegetation identification [J]. Geospatial Information, 2017, 15(2): 72-75 (in Chinese).

    [4] Ming Qunjie. Identification and Extraction of Typical Vegetation on Qinghai-Tibetan Plateau [D]. Beijing: Master Thesis of China University of Geosciences of China, 2017 (in Chinese).

    [5] Sylvain J, Mireille G. A novel maximum likelihood based method for mapping depth and water quality from hyperspectral remote-sensing data [J]. Remote Sensing of Environment, 2014, 147(18): 121-132.

    [6] ChengBoyan, Liu Qiang, Li Xiaowen, et al. Building simplification using backpropagation neural networks: a combination of cartographers’ expertise and raster-based local perception [J]. Mapping Sciences and Remote Sensing, 2013, 50(5): 527-542.

    [7] Zhou Y M, Zhang R Q, Ma H Y,et al. Retrieving of salt lake mineral ions salinity from hyper-spectral data based on BP neural network [J]. Remote Sensing for Land and Resources, 2016, 28(2): 34-40 (in Chinese).

    [8] Maulik U, Chakraborty D. Learning with transductive SVM for semisupervised pixel classification of remote sensing imagery [J]. Isprs Journal of Photogrammetry & Remote Sensing, 2013, 77: 66-78.

    [9] Liu Yanling. Physicochemical Parametric Inversion and Refined Classification of Vegetation based on Hyperspectral Remote Sensing Image [D]. Harbin: Master Thesis of Harbin Institute of Technology of China, 2018 (in Chinese).

    [10] LuoGuangchun, Chen Guangyi, Tian Ling, et al. Minimum noise fraction versus principal component analysis as a preprocessing step for hyperspectral imagery denoising [J]. Canadian Journal of Remote Sensing, 2016, 42(2): 106-116.

    [11] Wang C W, Wang H W, Hu B, et al. A new spectral-spatial algorithm method for hyperspectral image target detection [J]. Spectroscopy and Spectral Analysis, 2016, 36(4): 1163-1169 (in Chinese).

    [12] Qiao Yu. Study on Spectral Reflectance Characteristics of Representative Vegetation and Its Application in The Middle Section of The Qilian Mountains [D]. Lanzhou: Master Thesis of Lanzhou University of China, 2017 (in Chinese).

    [13] Rouse J W, Haas R H, Schell J A,et al. Monitoring Vegetation Systems in the Great Plains with ERTS[C]// Proceedings of Third Earth Resources Technology Satellite-1 Symposium. Greenbelt, 1974 (351): 310-317.

    [14] Villamuelas M, Fernandez N, Albanell E, et al. The enhanced vegetation index (EVI) as a proxy for diet quality and composition in a mountain ungulate [J]. Ecological Indicators, 2016, 61: 658-666.

    [15] Rondeaux G, Steven M, Baret F. Optimization of soil-adjusted vegetation indices [J]. Remote Sensing of Environment, 1996, 55(2): 95-107.

    [16] Elvidge C D, Chen Z K. Comparison of broad-band and narrow-band red and near-infrared vegetation indices [J]. Remote Sensing of Environment, 1995, 54(1): 38-48.

    CLP Journals

    [1] JING Min, CHEN Manlong, DING Min, ZHANG Qi, YANG Fan, MA Zhenyuan. Oil recognition based on fluorescence-lifetime decay curve combined with support vector machine[J]. Journal of Atmospheric and Environmental Optics, 2022, 17(2): 258

    MIAO Yuhong, YANG Min, WU Guojun. Sophisticated Vegetation Classification Based on Multi-Dimensional Features of Hyperspectral Image[J]. Journal of Atmospheric and Environmental Optics, 2020, 15(2): 117
    Download Citation