Skip to main content
ARS Home » Plains Area » College Station, Texas » Southern Plains Agricultural Research Center » Aerial Application Technology Research » Research » Publications at this Location » Publication #343101

Research Project: Aerial Application Technology for Sustainable Crop Production

Location: Aerial Application Technology Research

Title: Automated geographic registration and radiometric correction for UAV-based mosaics

Author
item THOMASSON, JOHN - University Of Nebraska
item YEYIN, SHI - Texas A&M University
item SIM, CHAO - Texas A&M University
item Yang, Chenghai
item COPE, DALE - Texas A&M University

Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: 7/10/2017
Publication Date: 7/17/2017
Citation: Thomasson, J., Yeyin, S., Sim, C., Yang, C., Cope, D. 2017. Automated geographic registration and radiometric correction for UAV-based mosaics. Proceedings of SPIE. Vol. 10218, 102180K-1.

Interpretive Summary: To use unmanned aerial vehicles (UAV)-based images in agricultural production, many high-resolution images must be mosaicked together to create an image of an agricultural field. Two key difficulties to science-based utilization of such mosaics are geographic registration and radiometric calibration. In our current research project, we have developed a method for automated geographic registration and radiometric correction using ground targets that are installed semi-permanently at distributed locations around fields and have different reflectance values. To validate the system for radiometric calibration, a calibrated UAV-based image mosaic of a field was compared to a calibrated single image from a manned aircraft. Reflectance values in selected zones of each image were strongly linearly related. Based on these results, the proposed physical system and automated software for calibrating UAV mosaics show excellent promise.

Technical Abstract: Texas A&M University has been operating a large-scale, UAV-based, agricultural remote-sensing research project since 2015. To use UAV-based images in agricultural production, many high-resolution images must be mosaicked together to create an image of an agricultural field. Two key difficulties to science-based utilization of such mosaics are geographic registration and radiometric calibration. In our current research project, image files are taken to the computer laboratory after the flight, and semi-manual pre-processing is implemented on the raw image data, including ortho-mosaicking and radiometric calibration. Ground control points (GCPs) are critical for high-quality geographic registration of images during mosaicking. Applications requiring accurate reflectance data also require radiometric-calibration references so that reflectance values of image objects can be calculated. We have developed a method for automated geographic registration and radiometric correction with targets that are installed semi-permanently at distributed locations around fields. The targets are a combination of black (˜5% reflectance), dark gray (˜20% reflectance), and light gray (˜40% reflectance) sections that provide for a transformation of pixel-value to reflectance in the dynamic range of crop fields. The exact spectral reflectance of each target is known, having been measured with a spectrophotometer. At the time of installation, each target is measured for position with a real-time kinematic GPS receiver to give its precise latitude and longitude. Automated location of the reference targets in the images is required for precise, automated, geographic registration; and automated calculation of the digital-number to reflectance transformation is required for automated radiometric calibration. To validate the system for radiometric calibration, a calibrated UAV-based image mosaic of a field was compared to a calibrated single image from a manned aircraft. Reflectance values in selected zones of each image were strongly linearly related, and the average error of UAV-mosaic reflectances was 3.4% in the red band, 1.9% in the green band, and 1.5% in the blue band. Based on these results, the proposed physical system and automated software for calibrating UAV mosaics show excellent promise.