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

Vinod Ramnath; Peter Friess; Hieu Duong; Viktor Feygels; Yuri Kopilevich

doi:10.1117/12.2303893

10 May 2018 Total propagated uncertainty for coastal zone mapping and imaging lidar (CZMIL)

Vinod Ramnath, Peter Friess, Hieu Duong, Viktor Feygels, Yuri Kopilevich

Proceedings Volume 10636, Laser Radar Technology and Applications XXIII; 106360N (2018) https://doi.org/10.1117/12.2303893
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

Abstract

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.

Citation Download Citation

Vinod Ramnath, Peter Friess, Hieu Duong, Viktor Feygels, and Yuri Kopilevich "Total propagated uncertainty for coastal zone mapping and imaging lidar (CZMIL)", Proc. SPIE 10636, Laser Radar Technology and Applications XXIII, 106360N (10 May 2018); https://doi.org/10.1117/12.2303893

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KEYWORDS

CZMIL

Error analysis

LIDAR

Sensors

Ranging

Statistical analysis

Estimation theory

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