13 May 2014 Deriving vegetation fraction information for the alpine grassland on the Tibetan plateau using in situ spectral data
Bo Liu, Weishou Shen, Naifeng Lin, Ru Li, Yuemin Yue
Author Affiliations +
Abstract
Vegetation fraction (VF) is the indispensable factor involved in the assessment of land degradation in the inclement climate condition and harsh natural environment. Based on the analysis of an in situ spectral dataset of alpine grasslands on the Tibetan plateau, we assessed the performance of 28 widely used vegetation indices (VIs) and a spectral mixture analysis (SMA) model applied on the analytical spectral device and simulated enhanced thematic mapper (ETM)+ and Huan Jing (HJ)-1 data to select a method for retrieving VF there. The results show that simple VIs are competent for extracting VF information, and VIs with an extra blue band involved will produce a better performance. However, involvement of too many more bands does not yield much higher accuracy, indicated by the fact that hyperspectral VIs are not superior to multispectral ones in our case. The SMA model provides an acceptable accuracy as well but lower than that of VI regression. In addition, the normalized difference vegetation index (NDVI) values of vegetation and soil, generally, as the key parameter in the widely used NDVI-SMA model is obtained, and this would benefit the application of this model to derive VF of alpine grasslands on the Tibetan plateau with minimal or no need for field work support.
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2014/$25.00 © 2014 SPIE
Bo Liu, Weishou Shen, Naifeng Lin, Ru Li, and Yuemin Yue "Deriving vegetation fraction information for the alpine grassland on the Tibetan plateau using in situ spectral data," Journal of Applied Remote Sensing 8(1), 083630 (13 May 2014). https://doi.org/10.1117/1.JRS.8.083630
Published: 13 May 2014
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Cited by 12 scholarly publications.
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KEYWORDS
Vegetation

Data modeling

Reflectivity

Shape memory alloys

Calibration

Near infrared

Soil science

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