School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 32601, USA.
Department of Global Ecology, Carnegie Institution for Science, Stanford, California 94305, USA.
Ecol Appl. 2016 Dec;26(8):2367-2373. doi: 10.1002/eap.1436.
Remote sensing is increasingly needed to meet the critical demand for estimates of forest structure and composition at landscape to continental scales. Hyperspectral images can detect tree canopy properties, including species identity, leaf chemistry and disease. Tree growth rates are related to these measurable canopy properties but whether growth can be directly predicted from hyperspectral data remains unknown. We used a single hyperspectral image and light detection and ranging-derived elevation to predict growth rates for 20 tropical tree species planted in experimental plots. We asked whether a consistent relationship between spectral data and growth rates exists across all species and which spectral regions, associated with different canopy chemical and structural properties, are important for predicting growth rates. We found that a linear combination of narrowband indices and elevation is correlated with standardized growth rates across all 20 tree species (R = 53.70%). Although wavelengths from the entire visible-to-shortwave infrared spectrum were involved in our analysis, results point to relatively greater importance of visible and near-infrared regions for relating canopy reflectance to tree growth data. Overall, we demonstrate the potential for hyperspectral data to quantify tree demography over a much larger area than possible with field-based methods in forest inventory plots.
遥感技术在满足对景观到大陆尺度的森林结构和组成进行估计的迫切需求方面变得越来越重要。高光谱图像可以检测树冠属性，包括物种身份、叶片化学和疾病。树木生长速率与这些可测量的树冠属性有关，但从高光谱数据是否可以直接预测生长速率仍不清楚。我们使用单一的高光谱图像和光探测和测距衍生的海拔来预测种植在实验田中的 20 种热带树种的生长速率。我们询问在所有物种中是否存在光谱数据与生长速率之间的一致关系，以及与不同树冠化学和结构特性相关的哪些光谱区域对预测生长速率很重要。我们发现，窄波段指数和海拔的线性组合与所有 20 种树木的标准化生长速率相关（R = 53.70%）。尽管我们的分析涉及整个可见光到短波红外光谱的波长，但结果表明，对于将冠层反射率与树木生长数据相关联，可见光和近红外区域相对更为重要。总的来说，我们证明了高光谱数据在比森林清查样地中的基于实地的方法能够更大程度地量化树木动态方面的潜力。
