Estimating average tree crown size using spatial information from Ikonos and QuickBird images: Across-sensor and across-site comparisons
Estimating average tree crown size using spatial information from Ikonos and QuickBird images: Across-sensor and across-site comparisons
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DOI：
10.1016/j.rse.2009.12.022
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发表时间：
2010-05
影响因子：
13.5
通讯作者：
C. Song;M. Dickinson;L. Su;Su Zhang;Daniel Yaussey
中科院分区：
文献类型：
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作者：
C. Song;M. Dickinson;L. Su;Su Zhang;Daniel Yaussey
森林冠层是森林生态系统与大气之间能量、质量和动量交换的媒介。树冠大小是冠层结构的一个重要方面，对冠层的生物物理过程有重要影响。树冠大小还与其他冠层结构参数密切相关，如树高、胸径和生物量。但是关于树冠大小的信息很难获得，而且很少从传统的森林清查中获得。该研究的目的是验证先前开发的树冠大小估计模型可以在传感器和站点之间推广的假设。我们的研究地点包括美国俄亥俄州东南部的浣熊生态管理区和美国北卡罗来纳州皮埃蒙特的杜克森林。我们在2005年和2007年的夏天对一系列圆形地块进行了采样。我们得出了每个采样地块胸径（DBH）大于6.4cm （2.5 in）的树木的平均树冠直径（CD）。以Ikonos和QuickBird影像的影像空间信息为自变量，以俄亥俄州林分CD为因变量，建立了统计模型。该模型提供了与其他方法相当的硬木林分树冠大小的解释（R2= ~ 0.5， RMSE=0.83m）。此外，利用两种空间分辨率图像方差比估算树冠大小的模型可以跨传感器和站点应用，即Ikonos图像开发的统计模型可以直接应用于QuickBird图像估算树冠大小，俄亥俄州开发的统计模型可以直接应用于北卡罗来纳州图像估算树冠大小。上述结果表明，基于两种空间分辨率图像方差比建立的模型可以利用现有样地数据和影像对森林资源CD进行估算，提高森林资源清查和监测的效率。
The forest canopy is the medium for energy, mass, and momentum exchanges between the forest ecosystem and the atmosphere. Tree crown size is a critical aspect of canopy structure that significantly influences these biophysical processes in the canopy. Tree crown size is also strongly related to other canopy structural parameters, such as tree height, diameter at breast height and biomass. But information about tree crown sizes is difficult to obtain and rarely available from traditional forest inventory. The study objective was to test the hypothesis that a model previously developed for estimation of tree crown size can be generalized across sensors and sites. Our study sites include the Racoon Ecological Management Area in southeast Ohio, USA and the Duke Forest in North Carolina Piedmont, USA. We sampled a series of circular plots in the summers of 2005 and 2007. We derived average tree crown diameter (CD) for trees with diameter at breast height (DBH) greater than 6.4cm (2.5 in) for each sampling plot. We developed statistical models using image spatial information from Ikonos and QuickBird images as the independent variable and CD for stands in Ohio as the dependent variable. The models provide an explanation of tree crown size for the hardwood stands comparable to other approaches (R2=∼0.5 and RMSE=0.83m). Moreover, the models that estimate tree crown size using the ratio of image variances at two spatial resolutions can be applied across sensors and sites, i.e. the statistical models developed with Ikonos images can be applied directly to estimate tree crown size with QuickBird image, and the statistical models developed in Ohio can be applied directly to estimate tree crown size with images in North Carolina. These results indicate that the model developed based on image variance ratio at two spatial resolutions can be used to take advantage of existing sampling plot data and images to estimate CD with more recent images, enhancing the efficiency of forest resources inventory and monitoring.