Deploying Fixed Wing Unoccupied Aerial Systems (UAS) for Coastal Morphology Assessment and Management

Published

Journal Article

© 2018 Coastal Education and Research Foundation, Inc. Accurate measurement of the morphology and distribution of coastal habitats is critical for understanding the function of coastal environments, assessing the resilience of coastal communities, and managing the coastal zone effectively. Unoccupied aerial systems (UASs, also known as unmanned aerial vehicles) and structure from motion (SfM) photogrammetry may be optimal for coastal surveys around small-or medium-sized municipalities, but guidance is needed to identify appropriate equipment configurations. Digital surface models (DSMs) from UAS equipped with mapping and survey-grade GPS units were processed with and without ground control point (GCP) correction, and their accuracy was compared to terrestrial laser scanner (TLS) derived DSMs and global navigation satellite system (GNSS) checkpoints. Four UAS sorties were flown over an active fetch-limited barrier island in North Carolina, which was concurrently surveyed with TLS and GNSS. Average DSM vertical accuracy from real-time kinematic (RTK)-equipped UAS improved from 0.081 m error to 0.032 m error after GCP correction, and the average elevation range between surfaces improved from ∼0.17 m to ∼0.05 m. In areas with low dunes, the UAS DSM was an average of 0.042 m away from the TLS DSM and was closer to the GNSS survey checkpoints. In vegetated areas, this distance increased to 0.082 m because of TLS occlusion effects. The SfM process-generated elevation artifacts in areas of imagery with homogenous texture, such as the foreshore and sun angle, likely plays an important role when surveying sandy beach environments. The RTK-equipped UAS and UAS data processed with GCPs yield DMSs with similar accuracy to those derived from TLS but are a superior choice for municipal-scale surveys because of lower operating costs, greater areal coverage, and lower environmental impact.

Full Text

Duke Authors

Cited Authors

  • Seymour, AC; Ridge, JT; Rodriguez, AB; Newton, E; Dale, J; Johnston, DW

Published Date

  • May 1, 2018

Published In

Volume / Issue

  • 34 / 3

Start / End Page

  • 704 - 717

Electronic International Standard Serial Number (EISSN)

  • 1551-5036

International Standard Serial Number (ISSN)

  • 0749-0208

Digital Object Identifier (DOI)

  • 10.2112/JCOASTRES-D-17-00088.1

Citation Source

  • Scopus