Retrieving the Diurnal FPAR of a Maize Canopy from the Jointing Stage to the Tasseling Stage with Vegetation Indices under Different Water Stresses and Light Conditions.
Retrieving the Diurnal FPAR of a Maize Canopy from the Jointing Stage to the Tasseling Stage with Vegetation Indices under Different Water Stresses and Light Conditions.
复制标题
用植被指数反演不同水分胁迫和光照条件下玉米冠层从拔节期到抽雄期的日FPAR
DOI：
10.3390/s18113965
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发表时间：
2018-11-15
期刊：
影响因子：
--
通讯作者：
Ren S
中科院分区：
文献类型：
--
作者：
Zhao L;Liu Z;Xu S;He X;Ni Z;Zhao H;Ren S
在植被生产力模型中，吸收的光合有效辐射（FPAR）是一个关键变量。植被指数（维斯），来自瞬时遥感数据已成功地用于估计一天或更长时间的FPAR。然而，它还没有被验证是否可以使用连续的维斯，以准确地估计植被冠层FPAR的昼夜动态，这可能会在一天内波动剧烈。在这项研究中，我们测量了高时间分辨率光谱数据（480至850 nm）和FPAR数据的玉米冠层从拔节期到抽雄期在不同的灌溉和光照条件下，使用两个自动观测系统。为了估计FPAR，我们使用13种维斯开发了基于二次函数的回归模型。结果表明：（1）在非干旱条件下，光照条件（晴天或阴天）虽然影响冠层日FPAR的变化趋势，但对FPAR-VI模型精度的影响很小。晴天非干旱数据、多云非干旱数据和所有非干旱数据的FPAR-VIs模型的最大决定系数（R2）分别为0.895、0.88和0.828。与冠层结构相关的植被指数（包括归一化差值植被指数（NDVI）、绿色植被指数（GNDVI）、红边简单比（SR 705）、修正简单比2（mSR 2）、红边归一化差值植被指数（NDVI 705）和增强植被指数（EVI））的估算精度较高（R2 > 0.8），与土壤调节、叶绿素和生理相关的其他维斯指数差异不显著。GNDVI和部分红边维斯指数（包括NDVI 705、SR 705和mSR 2）的估算精度高于NDVI。(2)在干旱胁迫下，中午前后叶片萎蔫，有效叶面积指数下降，使FPAR显著下降。当我们在模型中包含干旱数据时，准确性大大降低，最佳模型的R2值仅为0.59。当仅基于干旱数据建立回归模型时，能弱化土壤影响的EVI模型的估计精度最高（R2 = 0.68）。
The fraction of absorbed photosynthetically active radiation (FPAR) is a key variable in the model of vegetation productivity. Vegetation indices (VIs) that were derived from instantaneous remote-sensing data have been successfully used to estimate the FPAR of a day or a longer period. However, it has not yet been verified whether continuous VIs can be used to accurately estimate the diurnal dynamics of a vegetation canopy FPAR, which may fluctuate dramatically within a day. In this study, we measured the high temporal resolution spectral data (480 to 850 nm) and FPAR data of a maize canopy from the jointing stage to the tasseling stage under different irrigation and illumination conditions using two automatic observation systems. To estimate the FPAR, we developed regression models based on a quadratic function using 13 kinds of VIs. The results show the following: (1) Under nondrought conditions, although the illumination condition (sunny or cloudy) influenced the trend of the canopy diurnal FPAR, it had only a slight effect on the model accuracies of the FPAR-VIs. The maximum coefficients of determination (R2) of the FPAR-VIs models generated for the sunny nondrought data, the cloudy nondrought data, and all of the nondrought data were 0.895, 0.88, and 0.828, respectively. The VIs—including normalized difference vegetation index (NDVI), green NDVI (GNDVI), red-edge simple ratio (SR705), modified simple ratio 2 (mSR2), red-edge normalized difference vegetation index (NDVI705), and enhanced vegetation index (EVI)—that were related to the canopy structure had higher estimation accuracies (R2 > 0.8) than the other VIs that were related to the soil adjustment, chlorophyll, and physiology. The estimation accuracies of the GNDVI and some red-edge VIs (including NDVI705, SR705, and mSR2) were higher than the estimation accuracy of the NDVI. (2) Under drought stress, the FPAR decreased significantly because of leaf wilting and the effective leaf area index decrease around noon. When we included drought data in the model, accuracies were reduced dramatically and the R2 value of the best model was only 0.59. When we built the regression models based only on drought data, the EVI, which can weaken the influence of soil, had the best estimate accuracy (R2 = 0.68).
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影响因子：
6.2
作者：
Garriques, S.;Shabanov, N. V.;Myneni, R. B.
通讯作者：
Myneni, R. B.
DOI：
10.1098/rstb.1977.0140
发表时间：
1977-01-01
影响因子：
6.3
作者：
MONTEITH, JL
通讯作者：
MONTEITH, JL
影响因子：
11.6
作者：
Hanan, NP;Burba, G;Walter-Shea, EA
通讯作者：
Walter-Shea, EA
DOI：
10.1109/tgrs.2007.904836
发表时间：
2008-02-01
影响因子：
8.2
作者：
Haboudane, Driss;Tremblay, Nicolas;Vigneault, Philippe
通讯作者：
Vigneault, Philippe
影响因子：
8.2
作者：
LIU, HQ;HUETE, A
通讯作者：
HUETE, A