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Modeling Sensitivity of Topographic Change with sUAS Imagery
Geomorphology ( IF 3.9 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.geomorph.2020.107563
Michael E. Hodgson , Grayson R. Morgan

Abstract Mapping the topographic surface and monitoring the change in such topographic surfaces has largely been a remote sensing-based solution for the last eighty years. The last few years has seen the dramatic rise in the use of small unmanned aerial systems (sUAS) for mapping both the topographic surface (in largely un-vegetated areas) and particularly, the overlying surface layer. How accurate are the sUAS derived elevation surfaces? How accurate are the change surfaces from a comparison of multi-date surfaces? How confident can the user be in the changes detected? Probing the expected accuracy for a topographic surface derived from low altitude sUAS imagery is a tad more problematic than many other types remotely sensed imaging sensors. The precision and spatial resolution of the sUAS imagery, and subsequent digital elevation models (DEMs) is similar to the precision and spatial resolution of the very reference data sources used for accessing accuracy. In this research an approach was used to evaluate the performance of sUAS for creating digital elevation models on coastal sand dunes that did not change during ten repeat aerial collections at 40 m above ground level. A simple error budget model was used to empirically derive the intrinsic accuracy of the sUAS-derived topographic surface. The overall accuracy of the ten DEMs derived from independent aerial missions was 0.033 m root mean squared error (RMSE). The results indicate a confidence threshold of ~0.030 m can be typically used to separate 95% of the ‘false’ topographic changes mapped from two digital elevation models in this collection/processing context. By modeling and removing the reference data error (i.e. survey grade global navigation satellite systems (GNSS)-derived validation points) the average accuracy of the ten DEMs was 0.022 m (RMSE).

中文翻译:

使用 sUAS 图像模拟地形变化的敏感性

摘要 在过去的八十年中,绘制地形表面并监测此类地形表面的变化在很大程度上是一种基于遥感的解决方案。过去几年,小型无人机系统 (sUAS) 用于绘制地形表面(在大部分没有植被的区域),尤其是上覆地表层的情况急剧增加。sUAS 派生的高程表面有多准确?多日期表面比较的变化表面有多准确?用户对检测到的更改的信心如何?探测源自低空 sUAS 图像的地形表面的预期精度比许多其他类型的遥感成像传感器要困难一些。sUAS 图像的精度和空间分辨率,随后的数字高程模型 (DEM) 类似于用于访问准确性的非常参考数据源的精度和空间分辨率。在这项研究中,使用一种方法来评估 sUAS 在沿海沙丘上创建数字高程模型的性能,这些模型在距离地面 40 m 的十次重复空中收集期间没有变化。一个简单的误差预算模型用于凭经验推导出 sUAS 衍生的地形表面的内在精度。来自独立空中任务的十个 DEM 的整体精度为 0.033 m 均方根误差 (RMSE)。结果表明,~0.030 m 的置信阈值通常可用于分离从该采集/处理环境中的两个数字高程模型映射的 95% 的“虚假”地形变化。
更新日期:2021-02-01
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