The application of near-automated georeferencing technique to a strip of historic aerial photographs in GIS

Published date19 March 2018
Date19 March 2018
AuthorJae Sung Kim
Subject MatterLibrary & information science,Librarianship/library management,Library technology,Information behaviour & retrieval,Information user studies,Metadata,Information & knowledge management,Information & communications technology,Internet
The application of near-automated
georeferencing technique to
a strip of historic aerial
photographs in GIS
Jae Sung Kim
Department of Civil and Environmental Engineering, Colorado State University,
Fort Collins, Colorado, USA
Purpose The purpose of this paper is to describe the procedure for near-automation of the most commonly
used manual georeferencing technique in a desktop GIS environment for historic aerial photographs strip in
library archives.
Design/methodology/approach Most of the archived historic aerial photography consists of series of
aerial photographs that overlap to some extent, as the optimal overlap ratio is known as 60 percent by
photogrammetric standard.Therefore, conjugatepoints can be detectedfor the overlappingarea. The firstimage
was georeferenced manually by six-parameter affinetransformation using 2013 National AgricultureImagery
Program imagesas ground truths. Then, conjugate points were detected in the first andsecond images using
SpeededUp Robust Features andRandom Sample Consensus.The ground space coordinatesof conjugate points
were estimatedusing the first images sixparameters. Then the secondimages six parameters werecalculated
using conjugate pointsground spacecoordinates and pixelcoordinates in the secondimage. This procedurewas
repeated until the last image was georeferenced. However, error accumulated as the number of photographs
increased.Therefore, another six-parameter affine transformation was implemented using control points in the
first, middle,and last images. Finally, the imageswere warped using open source GIS tools.
Findings The result shows that historic aerial strip collections can be georeferenced with far less time and
labor using the technique proposed compared with the traditional manual georeferencing technique in a
desktop GIS environment.
Research limitations/implications The suggested approach will promote the usage of historic aerial
photographs for various scientific purposes including land use and land cover change detection, soil erosion
pattern recognition, agricultural practices change analysis, environmental improvement assessment, and
natural habitat change detection.
Practical implications Most commonly used georeferencing procedures for historic aerial photographs
in academic libraries require significant time and effort for manual measurement of conjugate points in the
object images and the ground truth images. By maximizing the automation of georeferencing procedures, the
suggested approach will save significant time and effort of library workforce.
Social implications With the suggested approach, large numbers of historic aerial photographs can be
rapidly georeferenced. This will allow libraries to provide more geospatial data to scientific communities.
Originality/value This is a unique approach to rapid georeferencing of historic aerial photograph strips.
Keywords Matching, GIS, SURF, GDAL, Historic aerial photographs, Near-automated georeferencing
Paper type Technical paper
1. Introduction
Georeferencing is the first step to using aerial photographs in a desktop GIS environment.
This typically requiresa user to measure thecoordinates of controlpoints in both unreferenced
and previously referenced images. Control points are locations to be identified accurately both
on the raster data set and in real-world coordinates (Environmental Systems Research Institute,
2016).Since most historicaerial photographycollections consistof strips of aerialphotographs,
manual georeferencing of multiple aerial photographs costs significant time and labor.
Therefore, researchers are currently seeking a methodology to automate georeferencing
procedures as much as possible. Georeferencing has been automated using various approaches
with different transformation models, degree of automation, and accuracy requirements.
Library Hi Tech
Vol. 36 No. 1, 2018
pp. 43-56
© Emerald PublishingLimited
DOI 10.1108/LHT-10-2016-0115
Received 30 October 2016
Revised 23 April 2017
Accepted 5 July 2017
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