Error characterization of the at-altitude radiance ratio method for reflectance conversion of remote sensing data

Luke J. R. DeCoffe; David N. Conran; Ryan J. Connal; Timothy D. Bauch; Nina G. Raqueño; Carl Salvaggio

doi:10.1117/12.2622560

3 June 2022 Error characterization of the at-altitude radiance ratio method for reflectance conversion of remote sensing data

Luke J. R. DeCoffe, David N. Conran, Ryan J. Connal, Timothy D. Bauch, Nina G. Raqueño, Carl Salvaggio

Author Affiliations +

Proceedings Volume 12114, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VII; 121140D (2022) https://doi.org/10.1117/12.2622560
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

In remote sensing, the conversion of sensor recorded radiance for each pixel in a scene to surface reflectance is a first step in many diagnostic analysis tasks. This process, known as reflectance conversion, is vital in the production of accurate information for a variety of applications, one of which is precision agriculture. Several calibration methods have been explored in previous research and are widely used today, with two of these being the empirical line method (ELM) and the at-altitude radiance ratio (AARR). The AARR approach is attractive to remote sensing practitioners as it allows reflectance conversion to be carried out in real-time throughout data collection, accounting for changes in illumination conditions, which can substantially reduce collection setup and subsequent data analysis time/effort. Illumination changes during a collection greatly influence the recorded scene radiance, which can confuse subsequent analysis results. While ELM has been demonstrated to report lower error when compared to AARR, the error introduced is often times acceptable depending on the application requirements and natural variation in the reflectance of the targets of interest. An onboard, downwelling irradiance spectrometer integrated onto a small unmanned aircraft system as part of this research is utilized to characterize the expected error in generated reflectance at varying aircraft altitudes and is cross compared to the ELM approach. Although the error introduced by AARR is larger when compared to ELM, this study allows the reader to determine if the ease of collection afforded by this real-time reflectance conversion methodology produces sufficiently accurate data for their particular remote sensing application.

Conference Presentation

Citation Download Citation

Luke J. R. DeCoffe, David N. Conran, Ryan J. Connal, Timothy D. Bauch, Nina G. Raqueño, and Carl Salvaggio "Error characterization of the at-altitude radiance ratio method for reflectance conversion of remote sensing data", Proc. SPIE 12114, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VII, 121140D (3 June 2022); https://doi.org/10.1117/12.2622560

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