A FEEDBACK BASED MODIFICATION OF THE NDVI TO MINIMIZE CANOPY BACKGROUND AND ATMOSPHERIC NOISE
A FEEDBACK BASED MODIFICATION OF THE NDVI TO MINIMIZE CANOPY BACKGROUND AND ATMOSPHERIC NOISE
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DOI：
10.1109/36.377946
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发表时间：
1995-03-01
影响因子：
8.2
通讯作者：
HUETE, A
中科院分区：
文献类型：
--
作者：
LIU, HQ;HUETE, A
归一化植被指数方程具有简单的开环结构（无反馈），这使得它容易受到大气和冠层背景条件变化的巨大误差和不确定性的影响。在这项研究中，一个系统的分析方法是用来检查现有的植被指数（VI）的噪声源，并制定一个稳定的，修改后的归一化植被指数（MNDVI）方程。MNDVI是NDVI的闭环版本，通过添加1）土壤和大气噪声反馈回路和2）大气噪声补偿前向回路来构建。为MNDVI开发的系数是基于物理的，并与大气和背景“边界"条件的预期范围相关。MNDVI可用于未经大气校正的数据，以及经瑞利校正和大气校正的数据。在现场观测和模拟数据集测试，发现MNDVI大大减少任何复杂的土壤和大气情况下的噪音。由此产生的不确定性，表示为植被等效噪声，为+/-0.11叶面积指数（LAI）单位，比归一化植被指数（+/-0.8叶面积指数）小7倍。这些结果表明，MNDVI可能是令人满意的，在满足地球观测系统（EOS）计划的准确，长期的植被测量的需要。
The Normalized Difference Vegetation Index (NDVI) equation has a simple, open loop structure (no feedback), which renders it susceptible to large sources of error and uncertainty over variable atmospheric and canopy background conditions. In this study, a systems analysis approach is used to examine noise sources in existing vegetation indices (VI's) and to develop a stable, modified NDVI (MNDVI) equation. The MNDVI, a closed-loop version of the NDVI, was constructed by adding 1) a soil and atmospheric noise feedback loop, and 2) an atmospheric noise compensation forward loop. The coefficients developed for the MNDVI are physically-based and are empirically related to the expected range of atmospheric and background ''boundary'' conditions. The MNDVI can be used with data uncorrected for atmosphere, as well as with Rayleigh corrected and atmospherically corrected data. In the field observational and simulated data sets tested here, the MNDVI was found to considerably reduce noise for any complex soil and atmospheric situation. The resulting uncertainty, expressed as vegetation equivalent noise, was +/-0.11 leaf area index (LAI) units, which was 7 times less than encountered with the NDVI (+/-0.8 LAI). These results indicate that the MNDVI may be satisfactory in meeting the need for accurate, long term vegetation measurements for the Earth Observing System (EOS) program.