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Remote Sens. 2012, 4(5), 1392-1410; doi:10.3390/rs4051392

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

School of Geography and Environmental Studies, University of Tasmania, Hobart, TAS 7001, Australia
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Received: 28 March 2012 / Revised: 7 May 2012 / Accepted: 7 May 2012 / Published: 14 May 2012
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) based Remote Sensing)
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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 65–120 cm whilst the GCP technique achieves an accuracy of approximately 10–15 cm. View Full-Text
Keywords: UAV; Structure from Motion (SfM); rectify; georeferencing; mosaicking; point cloud; Digital Terrain Model (DTM) UAV; Structure from Motion (SfM); rectify; georeferencing; mosaicking; point cloud; Digital Terrain Model (DTM)
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Turner, D.; Lucieer, A.; 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 Sens. 2012, 4, 1392-1410.

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