Application of hyperspectral vegetation indices to detect variations in high leaf area index temperate shrub thicket canopies
Application of hyperspectral vegetation indices to detect variations in high leaf area index temperate shrub thicket canopies
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DOI：
10.1016/j.rse.2010.09.020
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发表时间：
2011-02-15
影响因子：
13.5
通讯作者：
Young, Donald R.
中科院分区：
文献类型：
--
作者：
Brantley, Steven T.;Zinnert, Julie C.;Young, Donald R.
叶面积指数（LAI）是植物冠层的一个重要特征，与初级生产力直接相关，其准确测量对于监测生态系统碳储量和其他生态系统水平通量的变化至关重要。直接测量叶面积指数是劳动密集型的，在大尺度上是不切实际的，并且不能捕获冠层生物量的季节或年度变化。需要监测冠层相关通量景观遥感估算叶面积指数的一个有吸引力的技术。许多植被指数，如归一化植被指数，在叶面积指数大于4时趋于饱和，尽管热带和温带森林生态系统往往超过这一阈值。使用两个单种灌木丛作为模型系统，我们评估了各种算法的潜力，专门开发，以提高准确性的叶面积指数估计在冠层的叶面积指数超过饱和度的其他指数。我们还测试了潜在的指标，以检测冠层叶绿素的变化，估计叶面积指数，因为总冠层叶绿素含量和叶面积指数之间的直接关系。根据直接（凋落物）和间接测量（LAI-2000）的LAI数据评价指数。还评价了直接和间接地面取样技术结果之间的关系。对于这两个冠层，最有可能准确区分LAI值>4的指数是基于红边光谱反射率的衍生指数。在农业系统中，当LAI超过4时，旨在提高高LAI值精度的算法不敏感，并且对NDVI几乎没有改善。此外，间接地面采样技术往往用来评估潜在的植被指数也饱和时，叶面积指数超过4。高光谱植被指数与间接测量的饱和LAI值之间的比较可能高估了高LAI群落中某些植被指数的准确性和敏感性。我们建议验证间接测量的叶面积指数直接破坏性采样或凋落物收集，特别是在冠层高叶面积指数。(C)2010年爱思唯尔公司All rights reserved.
Accurate measurement of leaf area index (LAI), an important characteristic of plant canopies directly linked to primary production, is essential for monitoring changes in ecosystem C stocks and other ecosystem level fluxes. Direct measurement of LAI is labor intensive, impractical at large scales and does not capture seasonal or annual variations in canopy biomass. The need to monitor canopy related fluxes across landscapes makes remote sensing an attractive technique for estimating LAI. Many vegetation indices, such as Normalized Difference Vegetation Index (NDVI), tend to saturate at LAI levels >4 although tropical and temperate forested ecosystems often exceed that threshold. Using two monospecific shrub thickets as model systems, we evaluated the potential of a variety of algorithms specifically developed to improve accuracy of LAI estimates in canopies where LAI exceeds saturation levels for other indices. We also tested the potential of indices developed to detect variations in canopy chlorophyll to estimate LAI because of the direct relationship between total canopy chlorophyll content and LAI. Indices were evaluated based on data from direct (litterfall) and indirect measurements (LAI-2000) of LAI. Relationships between results of direct and indirect ground-sampling techniques were also evaluated. For these two canopies, the indices that showed the highest potential to accurately differentiate LAI values >4 were derivative indices based on red-edge spectral reflectance. Algorithms intended to improve accuracy at high LAI values in agricultural systems were insensitive when LAI exceeded 4 and offered little or no improvement over NDVI. Furthermore, indirect ground-sampling techniques often used to evaluate the potential of vegetation indices also saturate when LAI exceeds 4. Comparisons between hyperspectral vegetation indices and a saturated LAI value from indirect measurement may overestimate accuracy and sensitivity of some vegetation indices in high LAI communities. We recommend verification of indirect measurements of LAI with direct destructive sampling or litterfall collection, particularly in canopies with high LAI. (C) 2010 Elsevier Inc. All rights reserved.