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Journal of Applied Remote Sensing • Open Access

Georeferencing of mobile ground-based hyperspectral digital single-lens reflex imagery
Author(s): Amr Abd-Elrahman; Naoufal Sassi; Ben Wilkinson; Bon Dewitt

Paper Abstract

The georeferencing accuracy of a ground-based mobile mapping system designated for agricultural applications is tested. The system integrates a hyperspectral sensor, digital camera, global navigation satellite system receivers, and an inertial navigation system. Acquired imagery was synchronized with GPS time using custom hardware and software solutions developed in-house. The imaging platform was mounted on a forklift and used to conduct three imaging missions along a paved road segment and agricultural beds. Sixteen ground control points were established in each site and used to calibrate the system and test the positional accuracy. The control point coordinates were determined using GNSS and total station observations independent from the imaging data. The navigation data were postprocessed to extract sensor positions and attitude along the imaging trajectories. The pushbroom hyperspectral images were georeferenced using ReSe Parge software, while the digital camera images were analyzed using Agisoft PhotoScan software. Control point coordinates extracted from the georeferenced imagery were compared to corresponding ground-surveyed coordinates. The maximum root mean square errors obtained for the hyperspectral images in all experiments were 2.4 and 3.1 cm in the easting and northing directions, respectively. These results were achieved using only two control points at both ends of the scan line to estimate the boresight offsets. The RMSE values of the orthorectified image constructed using the digital camera images and two control points at each end of the agricultural site were 1.6 and 2.6 cm in the easting and northing directions.

Paper Details

Date Published: 7 March 2016
PDF: 18 pages
J. Appl. Remote Sens. 10(1) 014002 doi: 10.1117/1.JRS.10.014002
Published in: Journal of Applied Remote Sensing Volume 10, Issue 1
Show Author Affiliations
Amr Abd-Elrahman, Univ. of Florida (United States)
Naoufal Sassi, Univ. of Florida (United States)
Ben Wilkinson, University of Florida (United States)
Bon Dewitt, Univ. of Florida (United States)

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