Abstract Forest inventories in uncertain future economic and environmental conditions require the development of cost-effective measurement techniques to provide robust and accurate information on forests across regional and global scales. Digital terrestrial photogrammetry (DTP) can be used to detect and measure trees on sample plots. In this study, a method was developed which used spherical images taken strategically within plots, and under varying acquisition conditions, to derive forest inventory attributes. Using a set of 102 photos on 400 m2 circular plots achieved a mean detection rate of 72.3% and estimated diameter to an RMSE of 19.0%. This study also explored the sensitivity of detection and estimation accuracy to different field and acquisition conditions. Detection of individual trees was significantly influenced by the tree size and species (p < 0.05 in a regression analysis), while plot-level detection was influenced by size and stem density. Tree size and the distance to the camera significantly influenced the accuracy of estimated attributes. These results are comparable to those of other DTP and terrestrial laser scanning studies in similar forest types while using fewer photos and less time, demonstrating the value of cost-effective methods for DTP estimation of forest attributes.

中文翻译：

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数字地面摄影测量可增强跨林分条件的实地森林清单

摘要 在不确定的未来经济和环境条件下的森林清单需要开发具有成本效益的测量技术，以提供有关区域和全球范围内森林的可靠和准确的信息。数字地面摄影测量 (DTP) 可用于检测和测量样地上的树木。在这项研究中，开发了一种方法，该方法使用在地块内和在不同采集条件下战略性拍摄的球面图像来推导森林清单属性。在 400 平方米圆形地块上使用一组 102 张照片实现了 72.3% 的平均检测率和 19.0% 的估计直径，RMSE。本研究还探讨了检测和估计精度对不同领域和采集条件的敏感性。单个树木的检测受树木大小和物种的显着影响（回归分析中 p < 0.05），而地块级别的检测受大小和茎密度的影响。树的大小和到相机的距离显着影响估计属性的准确性。这些结果与类似森林类型的其他 DTP 和地面激光扫描研究的结果相当，同时使用的照片和时间更少，证明了 DTP 估计森林属性的成本效益方法的价值。