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Total propagated uncertainty for coastal zone mapping and imaging lidar (CZMIL)

机译:沿海地区测绘和成像激光雷达(CZMIL)的总传播不确定性

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CZMIL is an airborne multi-sensor system that exploits the data fusion paradigm to generate automated and high-resolution 3D environmental maps of coastal zones. CZMIL is used to map the near-shore environment for engineering and nautical charting applications on a recurring basis under the U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program. We have developed a mathematical framework, based on the contributing individual systematic and environmental parameters, for the estimation of Total Propagated Uncertainties (TPU) associated with CZMIL bathymetric data. We developed the TPU model based on the General Law of the Propagation of Variances. TPU is a critical metadata that characterizes the quality of a hydrographic survey. If there are issues with data integrity, TPU can be used as a diagnostic tool to provide insight and identify the particular lidar sub-system or processing module that is responsible. Moreover, because the overall ranging accuracy for any specific lidar bathymetric system is a function of water column properties, we have developed a simplified water-depth uncertainty model based on the different water types that CZMIL typically surveys. This depth uncertainty model is utilized in the TPU model. In this paper we will discuss the methodology, and list and discuss the CZMIL parameters that contribute to the uncertainty. We will also present TPU estimates for sample CZMIL datasets and compare theoretical and actual uncertainties. These actual or empirical uncertainties are estimated by comparing CZMIL positional data with ground truth.
机译:CZMIL是一种机载多传感器系统,它利用数据融合范例来生成沿海地区的自动化和高分辨率3D环境地图。根据美国陆军工程兵团(USACE)国家沿海制图计划,CZMIL经常性地对工程和航海制图应用程序的近岸环境进行制图。我们已经基于贡献的单个系统和环境参数开发了一个数学框架,用于估算与CZMIL水深数据相关的总传播不确定度(TPU)。我们根据差异传播的一般规律开发了TPU模型。 TPU是表征水文测量质量的关键元数据。如果数据完整性存在问题,则可以将TPU用作诊断工具,以提供洞察力并识别负责的特定激光雷达子系统或处理模块。此外,由于任何特定激光雷达测深系统的总体测距精度是水柱属性的函数,因此我们基于CZMIL通常调查的不同水类型开发了简化的水深不确定性模型。该深度不确定性模型在TPU模型中使用。在本文中,我们将讨论方法,并列出和讨论会导致不确定性的CZMIL参数。我们还将介绍样本CZMIL数据集的TPU估算值,并比较理论和实际不确定性。这些实际或经验上的不确定性是通过将CZMIL位置数据与实际情况进行比较来估算的。

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