| 光谱学与光谱分析 |
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| Study on the Nutrition of Alpine Meadow Based on Hyperspectral Data |
| 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, CUI Zhan-hong1,2,3 |
1. Province-Ministry Co-Constructing State Key Laboratory Cultivation Base of Plateau Grazing Animal Nutrition and Ecology of Qinghai Province, Xining 810086，China
2. Key Laboratory of Plateau Grazing Animal Nutrition and Feed Science of Qinghai Province, Xining 810016, China
3. Qinghai University, Academy of Animal Husbandry and Veterinary Medicine, Xining 810086, China
4. School of Environment, Tsinghua University, Beijing 100083, China
5. School of Architecture, Tsinghua University, Beijing 100083, China |
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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.
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Received: 2012-04-17
Accepted: 2012-07-10
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Corresponding Authors:
LIU Shu-jie
E-mail: mkylshi@126.com
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