地面和机载激光扫描与人工测量在基于茎干曲线的单棵树木生长测量中的精度比较

IF 5.7 Q1 ENVIRONMENTAL SCIENCES
Valtteri Soininen , Eric Hyyppä , Jesse Muhojoki , Ville Luoma , Harri Kaartinen , Matti Lehtomäki , Antero Kukko , Juha Hyyppä
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引用次数: 0

摘要

准确监测森林生长对于评估和控制森林碳储量非常重要,因为森林碳储量会影响大气中二氧化碳的浓度,进而影响气候变化。在以往的研究中,使用激光扫描方法监测森林生长会产生相对较高的误差。然而,很少有人分析参考测量误差对生长分辨率不确定性的影响,参考测量通常被认为是完美无瑕的。在这项研究中,我们使用机载和地面激光扫描(ALS、TLS)估算了单棵树木长达七年的生长情况,这两种方法已成为数字森林参考测量的潜在候选方法。采用间接方法得出了 2014 年至 2021 年期间胸径(DBH)和茎干体积的生长值。通过激光扫描获得的数值与人工实地测量值进行了配对,并相互进行了配对误差研究。成对比较结果表明,尽管三种测量方法在一次性测量中都产生了良好的皮尔逊相关系数(均高于 0.88),但在生长测量中的相关系数却明显较低(DBH 为 0.19-0.44,茎体积为 0.47-0.66)。人工实地测量与基于 ALS 的生长测量方法之间的相关性和均方根偏差(RMSD)最好,DBH 生长(ρ = 0.44,RMSD = 0.98 厘米)和茎干体积生长(ρ = 0.66,RMSD = 0.052 立方米)的相关性和均方根偏差(RMSD)最好,ALS 方法是从 2021 年的点云中获得树干曲线,并根据高度生长反向预测 2014 年的树干曲线。与基于 TLS 的生长测量方法相比,ALS 方法的离差值较小,因为 TLS 方法是根据 2014 年和 2021 年分别得出的茎干曲线的差值来计算生长量的。研究表明,观察茎秆曲线是一种潜在的短周期生长监测方法。利用成对比较结果,我们进一步估算了每种测量方法的测量误差平均值和标准偏差。在人工测量中,发现 DBH 生长的误差标准偏差约为 0.4 厘米,体积生长的误差标准偏差约为 0.03 立方米,是三种方法中误差最小的,但差距不大。这突出表明,随着基于激光扫描的生长估算方法的准确性不断接近人工测量的准确性,我们需要更准确的参考数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accuracy comparison of terrestrial and airborne laser scanning and manual measurements for stem curve-based growth measurements of individual trees

Monitoring forest growth accurately is important for assessing and controlling forest carbon stocks that impact, for example, the atmospheric CO2 concentration and, consequently, the climate change. In prior studies, forest growth monitoring with laser scanning methods has resulted in relatively high errors. However, the contribution of reference measurement error to uncertainty in growth resolution has rarely been analysed, and the reference measurements are usually considered mostly flawless. In this study, a seven-year-long growth of individual trees was estimated using both airborne and terrestrial laser scanning (ALS, TLS) that have emerged as potential candidates for digital forest reference measurements. The growth values were derived for diameter at breast height (DBH) and stem volume between the years 2014 and 2021 using an indirect approach. The values obtained with laser scanning were paired with manual field measurements and also with each other to study pairwise errors. The pairwise comparison showed that even though all the three measurement methods produced good Pearson correlation coefficients for one-time measurements (all above 0.88), the coefficients for growth measurements were significantly lower (0.19–0.44 for DBH and 0.47–0.66 for stem volume). The best correlation and root mean squared deviation (RMSD) for DBH growth (ρ = 0.44, RMSD = 0.98 cm) and stem volume growth (ρ = 0.66, RMSD = 0.052 m3) was observed between the manual field measurements and the ALS-based growth measurement method, in which the tree stem curve was obtained from the 2021 point cloud, and the stem curve was predicted backwards for the year 2014 according to height growth. The ALS method suffered less from outlying values than the TLS-based growth measurement method, in which the growth was computed based on the difference of stem curves derived separately for the years 2014 and 2021. The study showed that observing the stem curve is a potential method for short-period growth monitoring. Using the pairwise comparison results, we further derived estimates for the mean and standard deviation of measurement error of each individual measurement method. For the manual measurements, the standard deviation of error was found to be approximately 0.4 cm for DBH growth and 0.03 m3 for volume growth, which were the lowest of the three methods but not by a large margin. This highlights the need for more accurate reference data as the accuracy of laser scanning-based growth estimation methods continues to approach the accuracy of manual measurements.

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