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

Abstract

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, conjugate points can be detected for the overlapping area. The first image was georeferenced manually by six-parameter affine transformation using 2013 National Agriculture Imagery Program images as ground truths. Then, conjugate points were detected in the first and second images using Speeded Up Robust Features and Random Sample Consensus. The ground space coordinates of conjugate points were estimated using the first image’s six parameters. Then the second image’s six parameters were calculated using conjugate points’ ground space coordinates and pixel coordinates in the second image. This procedure was 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 images were 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.