• Spectroscopy and Spectral Analysis
  • Vol. 32, Issue 10, 2780 (2012)
WANG Xun1、2、3、*, LIU Shu-jie1、2、3, JIA Hai-feng4, CHAI Sha-tuo1、2、3, DANG An-rong5, LIU Xue-hua4, HAO Li-zhuang1、2、3, and CUI Zhan-hong1、2、3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
  • 5[in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2012)10-2780-05 Cite this Article
    WANG Xun, LIU Shu-jie, JIA Hai-feng, CHAI Sha-tuo, DANG An-rong, LIU Xue-hua, HAO Li-zhuang, CUI Zhan-hong. Study on the Nutrition of Alpine Meadow Based on Hyperspectral Data[J]. Spectroscopy and Spectral Analysis, 2012, 32(10): 2780 Copy Citation Text show less

    Abstract

    Remote sensing monitoring of alpine grassland nutritional status is a key factor of grassland reasonable utilization, also a difficulty for dynamic vegetation monitoring. The present paper studies the correlations between vegetation nutrition and hyperspectral data. The results showed that two band ratio models have a significant correlation with biomass, air-DM, P, CF, and CP. MAXR models have a significant correlation with most of nutrition index when selected wavebands equaled five. On the whole, the MAXR model precedes two band ratio models. Using MAXR models to estimate air-DM, P and CF can obtain higher accuracy.
    WANG Xun, LIU Shu-jie, JIA Hai-feng, CHAI Sha-tuo, DANG An-rong, LIU Xue-hua, HAO Li-zhuang, CUI Zhan-hong. Study on the Nutrition of Alpine Meadow Based on Hyperspectral Data[J]. Spectroscopy and Spectral Analysis, 2012, 32(10): 2780
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