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
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.
王 迅1,2,3，刘书杰1,2,3*，贾海峰4，柴沙驼1,2,3，党安荣5，刘雪华4，郝力壮1,2,3，崔占鸿1,2,3 . 基于高光谱数据的高寒草地营养状况的研究[J]. 光谱学与光谱分析, 2012, 32(10): 2780-2784.
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. Study on the Nutrition of Alpine Meadow Based on Hyperspectral Data . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(10): 2780-2784.
