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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1
Solar-Induced Chlorophyll Fluorescence Measured
From an Unmanned Aircraft System: Sensor
Etaloning and Platform Motion Correction
Juliane Bendig , Zbynˇ ek Malenovský , Deepak Gautam, and Arko Lucieer
Abstract— A dual-field-of-view spectroradiometer system has
been developed for measuring solar-induced chlorophyll fluo-
rescence (SIF), from an unmanned aircraft system (UAS). This
“AirSIF” system measures spectral reflectance in the visible and
near-infrared wavelengths as well as SIF in far-red O2-A and
red O2-B absorption features at high spatial resolution. It has
the potential to support the interpretation and validation of
canopy-emitted SIF observed by airborne, and future spaceborne
sensors at coarser spatial resolutions, as well as simulated by
radiative transfer models. In this contribution, we describe the
AirSIF data collection and processing workflows and present a
SIF map product of spatially explicit and geometrically correct
spectroradiometer footprints. We analyze two possible sources of
error in SIF retrieval procedure: a sensor-specific spectral artifact
called etaloning and the uncertainty of incoming irradiance
during UAS flight due to airframe motion (pitching and rolling).
Finally, we present results from two SIF acquisition approaches:
a continuous mapping flight and a stop&go flight targeting
predefined areas of interest. The results are analyzed for a case
study of Alfalfa and grass canopies and validated against ground
measurements using the same system.
Index Terms— Airborne spectroscopy, solar-induced chloro-
phyll fluorescence (SIF), unmanned aerial vehicle (UAV).
I. I NTRODUCTION
S
OLAR-INDUCED chlorophyll fluorescence (SIF) has
become a recent focus point of optical remote-sensing
research. The quantitative mapping of SIF satellite data
acquired with GOME-2 [1], GOSAT [2], OCO-2 [3] ,
and more recently the TROPOspheric Monitoring Instrument
(TROPOMI) [4] revealed the potential to enhance our under-
standing of terrestrial vegetation gross primary production and
Manuscript received May 17, 2019; revised August 11, 2019 and Octo-
ber 21, 2019; accepted November 22, 2019. This work was supported by
the Australian Research Council within the Discovery Grant under Grant
DP140101488: Air LIFT (support for Arko Lucieer, Deepak Gautam and
infrastructure). The work of J. Bendig was supported by the German Research
Foundation (DFG) Scholarship under Project 289370018. The work of
Z. Malenovský was supported by the Australian Research Council Future
Fellowship “Bridging Scales in Remote Sensing of Vegetation Stress” under
Grant FT160100477. (Corresponding author: Juliane Bendig.)
J. Bendig, Z. Malenovský, and A. Lucieer are with the College of
Sciences Engineering and Technology, School of Technology, Environ-
ments and Design, University of Tasmania, Hobart, TAS 7005, Aus-
tralia (e-mail: juliane.bendig@utas.edu.au; zbynek.malenovsky@utas.edu.au;
arko.lucieer@utas.edu.au).
D. Gautam is with the School of Agriculture, Food and Wine,
University of Adelaide, Adelaide, SA 5064, Australia (e-mail:
deeepak.gautam@adelaide.edu.au).
Color versions of one or more of the figures in this article are available
online at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TGRS.2019.2956194
consequently the global carbon cycle [5]. Early studies on
SIF retrieval triggered the development of novel SIF detecting
airborne platforms [6], [7] and new satellite missions like
the European Space Agency’s Earth Explorer FLEX [8].
These new initiatives have raised questions regarding the
interpretation and validation of a fluorescence signal collected
by the satellite. One of the main challenges is the scaling
of fluorescence measurements from the leaf to the canopy
level. Although the leaf level is relatively well-understood
[9], the interpretation of canopy SIF observations is more
complicated due to the canopy architecture. Multiple scattering
by vegetation structures (e.g., leaves and stems) is increasing
the reabsorption of the red SIF signal [10]. Additionally, sun-lit
leaves produce higher SIF intensity due to experiencing higher
levels of radiance than the shaded leaves under weaker, diffuse
illumination [11]. Recent modeling work has demonstrated
that leaf-to-canopy SIF scaling can be studied and resolved
using radiative transfer models [12]–[15], however, in situ
data are required to calibrate and validate both models and
satellite data. Ground- and tower-based systems can provide
spatially detailed, site-specific SIF data [16], [17], but they
only measure a limited area within their footprint.
SIF observations from unmanned aircraft systems (UASs)
may provide high-resolution and spatially explicit data from
relatively short observational distances (e.g., 10–30 m) [18]
and thus complement the high altitude chlorophyll fluores-
cence remote sensing. Although Burkart et al. [19] developed
a UAS-based SIF system already in 2014, UAS that can deliver
both accurate spectral data as well as accurate spatial charac-
terization of the spectroradiometer’s footprint location, shape,
and size is lacking. Burkart et al. [19], Garzonio et al. [20],
Zarco-Tejada et al. [21] used instruments, which were spec-
trally less stable (uncooled sensor chip) and with coarser spec-
tral resolution (full width at half maximum (FWHM) of 1.5,
1.5, and 6 nm), both key factors for reliable SIF retrieval [22].
Other studies used spectrally optimal spectroradiometers, but
the UAS solution was lacking the positioning and orientation
of sensors and associated geometric processing workflow for
an accurate ground projection of the spectroradiometer’s field
of view (FOV) [23]. Here, we present a system that enables
both: SIF retrieval from a spectroradiometer with a suitable
spectral resolution (FWHM of 0.8 nm) and accurate geoloca-
tion of the SIF measurements enabling further spatial analysis.
Retrieval of a weak SIF signal is challenging, especially
with regard to radiometric stability of the measurements.
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