Radiometric and Geometric Analysis of Hyperspectral Imagery Acquired from an Unmanned Aerial Vehicle

Ryan Hruska,Jessica Mitchell,Matthew Anderson,Nancy F Glenn

doi:10.3390/rs4092736

Abstract

In the summer of 2010, an Unmanned Aerial Vehicle (UAV) hyperspectral calibration and characterization experiment of the Resonon PIKA II imaging spectrometer was conducted at the US Department of Energy’s Idaho National Laboratory (INL) UAV Research Park. The purpose of the experiment was to validate the radiometric calibration of the spectrometer and determine the georegistration accuracy achievable from the on-board global positioning system (GPS) and inertial navigation sensors (INS) under operational conditions. In order for low-cost hyperspectral systems to compete with larger systems flown on manned aircraft, they must be able to collect data suitable for quantitative scientific analysis. The results of the in-flight calibration experiment indicate an absolute average agreement of 96.3%, 93.7% and 85.7% for calibration tarps of 56%, 24%, and 2.5% reflectivity, respectively. The achieved planimetric accuracy was 4.6 m (based on RMSE) with a flying height of 344 m above ground level (AGL).

Highlights

AIRBORNE hyperspectral imaging systems are widely used for environment research applications since the development of imaging spectrometers such as AVIRIS (Airborne Visible / Infrared ImagingSpectrometer) and HyMap (Hyperspectral Mapping) [1,2]
This paper describes the integration of a sophisticated, light weight commercial off-the-shelf imaging spectrometer with a medium-altitude, long-endurance unmanned aerial vehicle and presents results of a calibration and characterization experiment
These biases were most likely introduced while mounting the sensor payload and the Piccolo II autopilot into the Unmanned Aerial Vehicle (UAV) airframe

Summary

Introduction

Spectrometer) and HyMap (Hyperspectral Mapping) [1,2]. To date hyperspectral processing techniques for vegetation applications have primarily involved the development and use of narrowband vegetation indices, often times in conjunction with radiative transfer modeling [13,14]. Hyperspectral imaging is generally accomplished by sensors mounted on manned aircraft, and to a limited degree, spaceborne platforms. Manned flights are scheduled months to years in advance for high quality systems such as AVIRIS and HyMap, and have considerable mission costs. Weather conditions can force the cancellation of a mission, as many commercial manned-aircraft systems providers are oversubscribed and cannot accommodate remaining on-station for considerable time periods

Methods

Results

Conclusion