Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Development of a Simplified Radiometric Calibration Framework for Water-Based and Rapid Deployment Unmanned Aerial System (UAS) Operations

Version 1 : Received: 30 March 2020 / Approved: 31 March 2020 / Online: 31 March 2020 (23:13:23 CEST)

A peer-reviewed article of this Preprint also exists.

Zarzar, C.M.; Dash, P.; Dyer, J.L.; Moorhead, R.; Hathcock, L. Development of a Simplified Radiometric Calibration Framework for Water-Based and Rapid Deployment Unmanned Aerial System (UAS) Operations. Drones 2020, 4, 17. Zarzar, C.M.; Dash, P.; Dyer, J.L.; Moorhead, R.; Hathcock, L. Development of a Simplified Radiometric Calibration Framework for Water-Based and Rapid Deployment Unmanned Aerial System (UAS) Operations. Drones 2020, 4, 17.

Journal reference: Drones 2020, 4, 17
DOI: 10.3390/drones4020017

Abstract

The current study sets out to develop an empirical line method (ELM) radiometric calibration framework for reducing atmospheric contributions in UAS imagery and for producing scaled remote sensing reflectance imagery. Using a MicaSense RedEdge camera flown on a custom-built octocopter, the research reported herein finds that atmospheric contributions have an important impact on UAS imagery. Data collected over the Lower Pearl River Estuary in Mississippi during five week-long missions covering a wide range of environmental conditions was used to develop and test a simplified ELM radiometric calibration framework designed specifically for the reduction of atmospheric contributions to UAS imagery in studies with limited site accessibility or data acquisition time constraints. The framework was effective in reducing atmospheric and other external contributions to UAS imagery. Unique to the proposed radiometric calibration framework is the radiance to reflectance conversion conducted externally from the calibration equations which allows for the normalization of illumination independent from the time of UAS image acquisition and from the time of calibration equations development. This paper presents the simplified ELM radiometric calibration framework that can be used as a time-effective calibration technique to reduce errors in the UAS imagery.

Subject Areas

radiometric calibration; remote sensing; atmospheric effects; UAS; empirical line method

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