An initial exploration of vicarious and in-scene calibration techniques for small unmanned aircraft systems

Baabak G. Mamaghani; Geoffrey V. Sasaki; Ryan J. Connal; Kevin Kha; Jackson S. Knappen; Ryan A. Hartzell; Evan D. Marcellus; Timothy D. Bauch; Nina G. Raqueño; Carl Salvaggio

doi:10.1117/12.2302744

21 May 2018 An initial exploration of vicarious and in-scene calibration techniques for small unmanned aircraft systems

Baabak G. Mamaghani, Geoffrey V. Sasaki, Ryan J. Connal, Kevin Kha, Jackson S. Knappen, Ryan A. Hartzell, Evan D. Marcellus, Timothy D. Bauch, Nina G. Raqueño, Carl Salvaggio

Author Affiliations +

Proceedings Volume 10664, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III; 1066406 (2018) https://doi.org/10.1117/12.2302744
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

Abstract

The use of small unmanned aircraft systems (sUAS) for applications in the field of precision agriculture has demonstrated the need to produce temporally consistent imagery to allow for quantitative comparisons. In order for these aerial images to be used to identify actual changes on the ground, conversion of raw digital count to reflectance, or to an atmospherically normalized space, needs to be carried out. This paper will describe an experiment that compares the use of reflectance calibration panels, for use with the empirical line method (ELM), against a newly proposed ratio of the target radiance and the downwelling radiance, to predict the reflectance of known targets in the scene. We propose that the use of an on-board downwelling light sensor (DLS) may provide the sUAS remote sensing practitioner with an approach that does not require the expensive and time consuming task of placing known reflectance standards in the scene. Three calibration methods were tested in this study: 2-Point ELM, 1-Point ELM, and At-altitude Radiance Ratio (AARR). Our study indicates that the traditional 2-Point ELM produces the lowest mean error in band effective reflectance factor, 0.0165. The 1-Point ELM and AARR produce mean errors of 0.0343 and 0.0287 respectively. A modeling of the proposed AARR approach indicates that the technique has the potential to perform better than the 2-Point ELM method, with a 0.0026 mean error in band effective reflectance factor, indicating that this newly proposed technique may prove to be a viable alternative with suitable on-board sensors.

Conference Presentation

Citation Download Citation

Baabak G. Mamaghani, Geoffrey V. Sasaki, Ryan J. Connal, Kevin Kha, Jackson S. Knappen, Ryan A. Hartzell, Evan D. Marcellus, Timothy D. Bauch, Nina G. Raqueño, and Carl Salvaggio "An initial exploration of vicarious and in-scene calibration techniques for small unmanned aircraft systems", Proc. SPIE 10664, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III, 1066406 (21 May 2018); https://doi.org/10.1117/12.2302744

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available