Rapid mapping of small-scale river-floodplain environments using UAV SfM supports classical theory

Guy J.P. Schumann*, Joseph Muhlhausen, Konstantinos M. Andreadis

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

14 Citations (Scopus)
222 Downloads (Pure)

Abstract

Unmanned Aerial Vehicle (UAV) platforms have rapidly developed as tools for remote mapping at very high spatial resolutions. They have recently gained in popularity in many application fields owing to the versatility of platforms and sensors, ease of deployment, and a steady increase in computational power. Obtaining highly detailed topography data over very small scales is one of the more typical application domains. Here, we demonstrate this application using Structure from Motion (SfM) processing over a small river floodplain in Howard County (Maryland, USA). Evaluation of the derived bare-earth terrain model with state-of-the art LiDAR shows a trivial bias of 1.6 cm and a root mean square deviation (RMSD) of 39 cm. We then applied this terrain model to extract floodplain and river cross-section geometries of a small stream, important during high-magnitude urban flash flood events, with the aim to assess its value for floodplain inundation mapping and first order characterization of in-channel hydraulics. Initial findings agree with traditional stream and floodplain classification theory and thus show very promising results for this type of UAV usage. We expect this type of application to gain more momentum in the near future with the ever-growing importance of more detailed data in order to increase resilience to flood risk, especially in urban areas.

Original languageEnglish
Article number982
Number of pages12
JournalRemote Sensing
Volume11
Issue number8
DOIs
Publication statusPublished - 24 Apr 2019

Keywords

  • Digital elevation model
  • Floodplain
  • LiDAR
  • Stream
  • Structure from Motion
  • UAV

Fingerprint Dive into the research topics of 'Rapid mapping of small-scale river-floodplain environments using UAV SfM supports classical theory'. Together they form a unique fingerprint.

Cite this