Imaging chlorophyll fluorescence with an airborne narrow-band multispectral
camera for vegetation stress detection
P.J. Zarco-Tejada
a,
⁎
, J.A.J. Berni
a
, L. Suárez
a
, G. Sepulcre-Cantó
a
, F. Morales
b
, J.R. Miller
c
a
Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC), Córdoba, Spain
b
Departamento de Nutrición Vegetal, Estación Experimental de Aula Dei (EEAD), Consejo Superior de Investigaciones Científicas (CSIC), Apdo, 13034, 50080 Zaragoza, Spain
c
Dept. of Earth and Space Science and Engineering, York University, Toronto, Canada
abstractarticle info
Article history:
Received 15 May 2008
Received in revised form 12 February 2009
Accepted 14 February 2009
Keywords:
Fluorescence
Airborne
Fluormod
In-filling
Hyperspectral
Progress in assessing the feasibility for imaging fluorescence using the O
2
-A band with 1 nm full-width half-
maximum (FWHM) bands centered at 757.5 and 760.5 nm is reported in this paper. Multispectral airborne
data was acquired at 150 m above ground level in the thermal, visible and near infrared regions yielding
imagery at 15 cm spatial resolution. Simultaneous field experiments conducted in olive, peach, and orange
orchards (water stress trials), and an olive orchard (variety trial) enabled the detected variability in
fluorescence emission to be examined as function of stress status. In a parallel modelling activity the coupled
leaf–canopy reflectance–fluorescence model, FluorMOD, was used to assess fluorescence retrieval capability
by the in-filling method, as well as by fluorescence indices from the published literature. Fluorescence
retrievals using the in-filling method, the derivative index D702/D680 and reflectance indices R690/R630,
R761–R757, and R761/R757 yielded the best results in the simulation study, while demonstrating
insensitivity to leaf area index (LAI) variation. The fluorescence in-filling method, derivative index D702/
D680, and R761–R757 were the indices least affected by chlorophyll a+b (Cab) variation. On the other hand,
other published indices for fluorescence detection at leaf and canopy levels exhibited high sensitivity to
variations in Cab and LAI, and therefore were considered less suitable for in-field fluorescence detection. The
fluorescence signal extraction from airborne imagery using the in-filling method was validated through
comparisons with field-measured steady-state fluorescence (Fs) using the PAM-2100 and GFS-3000
instruments, confirming simulation predictions. The water stress experiments conducted on olive and
peach orchards demonstrated the feasibility of chlorophyll fluorescence (F) extraction at the tree level from
the airborne imagery, yielding determination coefficients r
2
=0.57 (olive), and r
2
=0.54 (peach). Consistent
results were obtained between airborne F and ground truth assimilation (A) measured in the olive variety
field experiment under no water stress levels, yielding r
2
=0.71.
© 2009 Elsevier Inc. All rights reserved.
1. Introduction
The early detection of water stress has been long identified as
critical to avoid yield losses in crops, which can be affected even by
short-term water stress deficits (Hsiao et al., 1976). Water stress is
developed in crops when the evaporative demand exceeds the supply
of water from the soil (Slatyer, 1967). A remote sensing indicator for
water stress detection was successfully demonstrated in the seventies
with near-field thermal infrared radiation (Idso et al., 1978, 1981;
Jackson et al., 1977, 1981; Jackson & Pinter, 1981) and more recently
with high-resolution airborne thermal imagers flown over orchard
crops (Sepulcre-Cantó et al., 2006, 2007). The successful detection of
water stress using the thermal region is in response to the canopy
transpiration changes, where canopy temperature increases with
reductions in evaporative cooling.
In addition to canopy temperature, other physiological and structural
indicators have been proposed for remote sensing detection of water
stress, such as wilting (Bradford & Hsiao, 1982), loss of leaf area
(Bradford & Hsiao, 1982; Wolfe et al., 1983) and chlorophyll content
(Björkman & Powles, 1984). Leaf water content is proposed as the
amount of water per unit leaf area, and remote sensing indices such as a
water band index (WBI) (Peñuelas et al., 1993, 1997), a moisture stress
index (MSI) (Rock et al.,1986) or the normalized difference water index
(NDWI) (Gao, 1996) have been shown to track water content at the
canopy level. Nevertheless, changes in leaf water content only occur at
advanced stages of dehydration in many (but not all) species, therefore
representing a parameter of limited interest for predicting crop water
status. A more valuable goal is to develop pre-visual indicators of stress,
i.e. before the onset of severe stress. Suggested pre-visual indicators of
stress are the physiological reflectance index (PRI) which is sensitive to
Remote Sensing of Environment 113 (2009) 1262–1275
⁎ Corresponding author. Instituto de Agricultura Sostenible (IAS), Consejo Superior
de Investigaciones Científicas (CSIC), Alameda del Obispo, s/n, 14004—Córdoba, Spain.
Tel.: +34 957 499 280, +34 676 954 937; fax: +34 957 499 252.
E-mail address: pzarco@ias.csic.es (P.J. Zarco-Tejada).
URL: http://www.ias.csic.es/pzarco (P.J. Zarco-Tejada).
0034-4257/$ – see front matter © 2009 Elsevier Inc. All rights reserved.
doi:10.1016/j.rse.2009.02.016
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