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HyperUAS—Imaging Spectroscopy from a Multirotor Unmanned Aircraft System
Author(s) -
Lucieer Arko,
Malenovský Zbyněk,
Veness Tony,
Wallace Luke
Publication year - 2014
Publication title -
journal of field robotics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.152
H-Index - 96
eISSN - 1556-4967
pISSN - 1556-4959
DOI - 10.1002/rob.21508
Subject(s) - remote sensing , hyperspectral imaging , multirotor , environmental science , imaging spectroscopy , image resolution , spectroradiometer , spectral resolution , computer science , geography , computer vision , engineering , optics , physics , aerospace engineering , reflectivity , spectral line , astronomy
One of the key advantages of a low‐flying unmanned aircraft system (UAS) is its ability to acquire digital images at an ultrahigh spatial resolution of a few centimeters. Remote sensing of quantitative biochemical and biophysical characteristics of small‐sized spatially fragmented vegetation canopies requires, however, not only high spatial, but also high spectral (i.e., hyperspectral) resolution. In this paper, we describe the design, development, airborne operations, calibration, processing, and interpretation of image data collected with a new hyperspectral unmanned aircraft system (HyperUAS). HyperUAS is a remotely controlled multirotor prototype carrying onboard a lightweight pushbroom spectroradiometer coupled with a dual frequency GPS and an inertial movement unit. The prototype was built to remotely acquire imaging spectroscopy data of 324 spectral bands (162 bands in a spectrally binned mode) with bandwidths between 4 and 5 nm at an ultrahigh spatial resolution of 2–5 cm. Three field airborne experiments, conducted over agricultural crops and over natural ecosystems of Antarctic mosses, proved operability of the system in standard field conditions, but also in a remote and harsh, low‐temperature environment of East Antarctica. Experimental results demonstrate that HyperUAS is capable of delivering georeferenced maps of quantitative biochemical and biophysical variables of vegetation and of actual vegetation health state at an unprecedented spatial resolution of 5 cm.