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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Quantifying the Accuracy of Digital Hemispherical Photography for Leaf Area Index Estimates on Broad-Leaved Tree Species
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Quantifying the Accuracy of Digital Hemispherical Photography for Leaf Area Index Estimates on Broad-Leaved Tree Species

机译：量化数字半球摄影对阔叶树种叶面积指数估计的准确性

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摘要

Digital hemispherical photography (DHP) has been widely used to estimate leaf area index (LAI) in forestry. Despite the advancement in the processing of hemispherical images with dedicated tools, several steps are still manual and thus easily affected by user’s experience and sensibility. The purpose of this study was to quantify the impact of user’s subjectivity on DHP LAI estimates for broad-leaved woody canopies using the software Can-Eye. Following the ISO 5725 protocol, we quantified the repeatability and reproducibility of the method, thus defining its precision for a wide range of broad-leaved canopies markedly differing for their structure. To get a complete evaluation of the method accuracy, we also quantified its trueness using artificial canopy images with known canopy cover. Moreover, the effect of the segmentation method was analysed. The best results for precision (restrained limits of repeatability and reproducibility) were obtained for high LAI values (>5) with limits corresponding to a variation of 22% in the estimated LAI values. Poorer results were obtained for medium and low LAI values, with a variation of the estimated LAI values that exceeded the 40%. Regardless of the LAI range explored, satisfactory results were achieved for trees in row-structured plantations (limits almost equal to the 30% of the estimated LAI). Satisfactory results were achieved for trueness, regardless of the canopy structure. The paired t-test revealed that the effect of the segmentation method on LAI estimates was significant. Despite a non-negligible user effect, the accuracy metrics for DHP are consistent with those determined for other indirect methods for LAI estimates, confirming the overall reliability of DHP in broad-leaved woody canopies.
机译：数字半球摄影（DHP）已被广泛用于估算林业的叶面积指数（LAI）。尽管使用专用工具处理半球图像有所进步，但仍然需要手动执行几个步骤，因此很容易受到用户的经验和敏感性的影响。这项研究的目的是使用Can-Eye软件来量化用户主观性对阔叶木冠层DHP LAI估计值的影响。根据ISO 5725协议，我们量化了该方法的可重复性和可重复性，从而定义了其宽阔的檐篷结构明显不同的精度。为了获得对方法准确性的完整评估，我们还使用具有已知树冠覆盖度的人工树冠图像对了其真实性进行了量化。此外，分析了分割方法的效果。对于较高的LAI值（> 5），其最佳精度（限制重复性和再现性的限制）获得了最佳结果，其限制对应于估计LAI值的22％变化。对于中等和较低的LAI值，获得的结果较差，而估计的LAI值的变化超过40％。不管探索的LAI范围如何，行结构人工林的树木均取得了令人满意的结果（极限值几乎等于估计LAI的30％）。不论顶篷结构如何，都可获得令人满意的真实性结果。配对t检验表明，分割方法对LAI估计的影响显着。尽管对用户的影响不可忽略，但DHP的准确性指标与其他用于LAI估计的间接方法所确定的准确性指标一致，从而确认了DHP在阔叶木冠层中的整体可靠性。

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