Variability and bias in active and passive ground-based measurements of effective plant, wood and leaf area index
Variability and bias in active and passive ground-based measurements of effective plant, wood and leaf area index
复制标题
DOI：
10.1016/j.agrformet.2018.01.029
复制
发表时间：
2018-04-15
影响因子：
6.2
通讯作者：
Lewis, Philip
中科院分区：
文献类型：
--
作者：
Calders, Kim;Origo, Niall;Lewis, Philip
就地叶面积指数（LAI）测量对于验证从卫星观测间接获得的广泛使用的大面积或全球LAI产品至关重要。在这里，我们比较了三种常见的和新兴的地面传感器，用于快速表征大面积的LAI，即数字半球面摄影（DHP），两种版本的广泛使用的商用LAI传感器（LiCOR LAI-2000和2200），以及地面激光扫描（TLS）。在空前的样本量下，在落叶林地冠层的叶片上和叶片下进行了比较。这三种地面仪器的估算值之间的偏差大于世界气象组织设定的5%的阈值目标。当汇总到地块尺度（1公顷）或场地尺度（6公顷）时，样本水平上的方差会减少。TLS在开叶和脱叶条件下的相对标准偏差均最低，分别为11.78%和13.02%。在有叶条件下，DHP得到的有效植物面积指数（ePAI）的相对标准偏差与我们密切相关，而在无叶条件下，根据所使用的阈值技术的不同，有效木材面积指数（eWAI）的相对标准偏差高达28.14-29.74%。TLS与LAI-2x00在叶片上的ePAI值一致性最好，一致性相关系数（CCC）为0.796。在落叶条件下，采用Ridler和Calvard阈值的DHP得到的eWAI值与TLS最吻合。使用蒙特卡罗自举的样本大小分析表明，TLS需要最少的样本来实现优于5%的平均值+/-标准差的精度。因此，我们支持早期的研究，表明TLS测量优先于依赖于特定照明条件的仪器测量。对LAI的间接估计进行验证的一个关键问题是真实值是未知的。由于我们无法知道LAI的真实值，因此我们无法量化测量的准确性。我们的辐射传输模拟表明，ePAI估计值平均比eLAI估计值高27%。线性回归表明eLAI与ePAI-eWAI呈线性关系（R-2 = 0.87），截距为0.552，提示在使用LAI估计值时需要谨慎。
In situ leaf area index (LAI) measurements are essential to validate widely-used large-area or global LAI products derived, indirectly, from satellite observations. Here, we compare three common and emerging ground-based sensors for rapid LAI characterisation of large areas, namely digital hemispherical photography (DHP), two versions of a widely-used commercial LAI sensor (LiCOR LAI-2000 and 2200), and terrestrial laser scanning (TLS). The comparison is conducted during leaf-on and leaf-off conditions at an unprecedented sample size in a deciduous woodland canopy. The deviation between estimates of these three ground-based instruments yields differences greater than the 5% threshold goal set by the World Meteorological Organization. The variance at sample level is reduced when aggregated to plot scale (1 ha) or site scale (6 ha). TLS shows the lowest relative standard deviation in both leaf-on (11.78%) and leaf-off (13.02%) conditions. Whereas the relative standard deviation of effective plant area index (ePAI) derived from DHP relates closely to us in leaf-on conditions, it is as large as 28.14-29.74% for effective wood area index (eWAI) values in leaf-off conditions depending on the thresholding technique that was used. ePAI values of TLS and LAI-2x00 agree best in leaf-on conditions with a concordance correlation coefficient (CCC) of 0.796. In leaf-off conditions, eWAI values derived from DHP with Ridler and Calvard thresholding agrees best with TLS. Sample size analysis using Monte Carlo bootstrapping shows that TLS requires the fewest samples to achieve a precision better than 5% for the mean +/- standard deviation. We therefore support earlier studies that suggest that TLS measurements are preferential to measurements from instruments that are dependent on specific illumination conditions. A key issue with validation of indirect estimates of LAI is that the true values are not known. Since we cannot know the true values of LAI, we cannot quantify the accuracy of the measurements. Our radiative transfer simulations show that ePAI estimates are, on average, 27% higher than eLAI estimates. Linear regression indicated a linear relationship between eLAI and ePAI-eWAI (R-2 = 0.87), with an intercept of 0.552 and suggests that caution is required when using LAI estimates.