|Ndzeidze, Steven - Oregon State University|
|Johnson, Kipp - Oregon State University|
|Johnson, Michael - University Of California|
|Louhaichi, Mounir - International Center For Agricultural Research In The Dry Areas (ICARDA)|
|Johnson, Douglas - Oregon State University|
Submitted to: Society for Range Management Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 10/5/2010
Publication Date: 2/9/2011
Citation: Ndzeidze, S.K., Johnson, K.E., Johnson, M.D., Clark, P., Louhaichi, M., Johnson, D.E. 2011. An algorithm for approximate rectification of digital aerial images. Society for Range Management Meeting Abstracts.
Technical Abstract: High-resolution aerial photography is one of the most valuable tools available for managing extensive landscapes. With recent advances in digital camera technology, computer hardware, and software, aerial photography is easier to collect, store, and transfer than ever before. Images can be automatically taken from aircraft at high frequency with cameras pointed vertically downward and stored on a laptop computer. The challenge in using this technology is the considerable time spent determining photo locations and subsequent geo-referencing so images can be used for spatial analysis. We coupled low-cost GPS loggers to track aircraft/camera position, altitude, and bearing with high spatial/temporal accuracy, and computer software to automatically provide rough geo-positioning of collected images. A Canon XSi digital camera, synchronized to Universal Time by photographing the US Naval Observatory’s Master Clock webpage is mounted pointed vertically downward in the belly of an aircraft. Our program takes the time when the image was taken, finds the position and elevation of the aircraft, rotates the image to account for aircraft direction, and rough positions the images automatically based on lens characteristics and height above the ground. The process creates a world file which provides coordinate and scale information and a projection file that specifies the geographic projection and datum used. Our algorithm can be used to batch process files leading to extremely fast coarse geo-referencing of aerial photos which were generally accurate to 100 meters when tested at 5 locations in Oregon. This is close enough to make further correction, if needed, quick and easy.