Estimation of chlorophyll content in mountain steppe using in situ hyperspectral measurements
文献类型： 外文期刊
作者： Zheng, Fengling 1 ; Xu, Bin 2 ; Xiao, Pengfeng 4 ; Zhang, Xueliang 4 ; Manlike, Asiya 2 ; Jin, Yun-Xiang 3 ; Li, Chao; 1 ;
作者机构： 1.Xinjiang Agr Univ, Coll Grassland & Environm Sci, 311 Nongda East Rd, Urumqi 830052, Xinjiang, Peoples R China
2.Xinjiang Acad Anim Sci, Inst Grassland, Urumqi, Xinjiang, Peoples R China
3.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Beijing, Peoples R China
4.Nanjing Univ, Sch Geog & Ocean Sci, Nanjing, Jiangsu, Peoples R China
关键词： Canopy spectral reflectance; chlorophyll content; hyperspectral vegetation indices; mountain steppe; red edge
期刊名称：SPECTROSCOPY LETTERS （ 影响因子：1.179； 五年影响因子：1.176 ）
ISSN： 0038-7010
年卷期：
页码：
收录情况： SCI
摘要： Mountain steppe has important production value and ecological function. The chlorophyll content is a critical biochemical parameter of steppe. This study aims at exploring effective spectral parameters for estimating the chlorophyll content in mountain steppe using in situ hyperspectral measurements. The study area is located on the northern slope of Tianshan Mountains with complex terrain and sparse vegetation. The canopy hyperspectral data and leaf chlorophyll content and canopy chlorophyll content data were measured from 101 samples. The empirical models were constructed based on nine vegetation indices and three red-edge parameters. The results showed that the red-edge magnitude, red-edge area, Second Modified Chlorophyll Absorption Ratio Index, Second Modified Chlorophyll Absorption Ratio Index/Second Optimized Soil-Adjusted Vegetation Index, Second Transformed Chlorophyll Absorption Ratio Index and Triangle Vegetation Index estimated canopy chlorophyll content satisfactorily. Leaf chlorophyll content of mountain steppe is not well estimated using canopy spectral parameters. The results revealed the specific vegetation indices and red-edge parameters for estimating vegetation biochemical parameters at canopy scale in mountain steppe using in situ hyperspectral measurements.
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