Estimation accuracy of fractional vegetation cover based on normalized difference vegetation index and UAV hyperspectral images
LIU Yongmei1,2(), FAN Hongjian1, GE Xinghua1, LIU Jianhong1,2, WANG Lei1,2
1. College of Urban and Environmental Science, Northwest University, Xi’an 710127, China 2. Shaanxi Key Laboratory of Surface System and Environmental Carrying Capacity, Xi’an 710127, China
The researches on the effects of band parameters on the biophysical parameters of vegetation estimation using the normalized difference vegetation index (NDVI) have great significance for the improvement in the application accuracy of NDVI in vegetation dynamic monitoring. Based on the hyperspectral images of artificial grassland obtained from a Resonon, Inc. Pika XC2 Hyperspectral Imaging Camera loaded by an unmanned aerial vehicle (UAV), this study analyzes the effects of the positions and width of red and near-infrared bands on NDVI and assesses the sensitivity of NDVI to fractional vegetation cover and the estimation accuracy. The results are as follows. When band positions were fixed, the width expansion of red and near-infrared bands had little effects on NDVI and its sensitivity, and the accuracy of fractional vegetation cover estimated using narrowband NDVI is higher than the accuracy based on broadband NDVI. When the red and near-infrared bands moved towards long waves, the NDVI and its sensitivity were affected to different extents. With an increase in the sensitivity, the anti-disturbance performance of NDVI decreased, and the estimation accuracy of fractional vegetation cover decreased. The sensitivity coefficient of narrowband NDVI and the R2 determined by the linear fitting of the sensitivity coefficient and the fractional vegetation cover greatly fluctuated, and the estimated fractional vegetation cover at various locations was unstable. High estimation accuracy of fractional vegetation was obtained at different locations using the 10 nm NDVI, with the maximum R2 value of 0.83. The broadband NDVI calculated using four popular satellite images can be well applied in the inversion of the fractional vegetation cover in areas with high vegetation cover. However, its inversion accuracy of fractional vegetation cover still suffered some attenuation compared with narrowband NDVI (10 nm). These results will serve as scientific references and bases for accurate inversion of vegetation parameters using NDVI.
刘咏梅, 范鸿建, 盖星华, 刘建红, 王雷. 基于无人机高光谱影像的NDVI估算植被盖度精度分析[J]. 自然资源遥感, 2021, 33(3): 11-17.
LIU Yongmei, FAN Hongjian, GE Xinghua, LIU Jianhong, WANG Lei. Estimation accuracy of fractional vegetation cover based on normalized difference vegetation index and UAV hyperspectral images. Remote Sensing for Natural Resources, 2021, 33(3): 11-17.
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