eCite Digital Repository

An Automated Technique for Generating Georectified Mosaics from Ultra-High Resolution Unmanned Aerial Vehicle (UAV) Imagery, Based on Structure from Motion (SfM) Point Clouds

Citation

Turner, D and Lucieer, A and Watson, C, An Automated Technique for Generating Georectified Mosaics from Ultra-High Resolution Unmanned Aerial Vehicle (UAV) Imagery, Based on Structure from Motion (SfM) Point Clouds, Remote Sensing, 4, (5) pp. 1392-1410. ISSN 2072-4292 (2012) [Refereed Article]


Preview
PDF
6Mb
  

Copyright Statement

Licensed under the Creative Commons Attribution license http://creativecommons.org/licenses/by/3.0/

DOI: doi:10.3390/rs4051392

Abstract

Unmanned Aerial Vehicles (UAVs) are an exciting new remote sensing tool capable of acquiring high resolution spatial data. Remote sensing with UAVs has the potential to provide imagery at an unprecedented spatial and temporal resolution. The small footprint of UAV imagery, however, makes it necessary to develop automated techniques to geometrically rectify and mosaic the imagery such that larger areas can be monitored. In this paper, we present a technique for geometric correction and mosaicking of UAV photography using feature matching and Structure from Motion (SfM) photogrammetric techniques. Images are processed to create three dimensional point clouds, initially in an arbitrary model space. The point clouds are transformed into a real-world coordinate system using either a direct georeferencing technique that uses estimated camera positions or via a Ground Control Point (GCP) technique that uses automatically identified GCPs within the point cloud. The point cloud is then used to generate a Digital Terrain Model (DTM) required for rectification of the images. Subsequent georeferenced images are then joined together to form a mosaic of the study area. The absolute spatial accuracy of the direct technique was found to be 65120 cm whilst the GCP technique achieves an accuracy of approximately 1015 cm.

Item Details

Item Type:Refereed Article
Research Division:Earth Sciences
Research Group:Physical Geography and Environmental Geoscience
Research Field:Physical Geography and Environmental Geoscience not elsewhere classified
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management of Antarctic and Sub-Antarctic Environments
Author:Turner, D (Mr Darren Turner)
Author:Lucieer, A (Associate Professor Arko Lucieer)
Author:Watson, C (Dr Christopher Watson)
ID Code:79083
Year Published:2012
Web of Science® Times Cited:159
Deposited By:Geography and Environmental Studies
Deposited On:2012-08-16
Last Modified:2014-10-16
Downloads:423 View Download Statistics

Repository Staff Only: item control page