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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 50, NO. 3, MARCH 2012
A Technique For Removing Second-Order Light
Effects From Hyperspectral Imaging Data
Rong-Rong Li, Robert Lucke, Daniel Korwan, and Bo-Cai Gao
Abstract—The Hyperspectral Imager for the Coastal Ocean
(HICO) instrument currently on board the International Space
Station is a new sensor designed specifically for the studies of
turbid coastal waters and large inland lakes and rivers. It covers
the wavelength range between 0.4 and 0.9 μm with a spectral
resolution of 5.7 nm and a spatial resolution of approximately
90 m. The HICO sensor is not equipped with a second-order
blocking filter in front of the focal plane array. As a result, the
second-order light from the shorter visible spectral region falls
onto the detectors covering the near-IR spectral region above
0.8 μm. In order to have accurate radiometric calibration of the
near-IR channels, the second-order light contribution needs to be
removed. The water-leaving radiances of these near-IR channels
over clear ocean waters are close to zero because of strong liquid water absorption above 0.8 μm. Through analysis of HICO
imaging data containing features of shallow underwater objects,
such as coral reefs, we have developed an empirical technique
to correct for the second-order light effects in near-IR channels.
HICO data acquired over Midway Island in the Pacific Ocean and
the Bahamas Banks in the Atlantic Ocean are used to demonstrate
the effectiveness of the new technique.
Index Terms—Hyperspectral imager, imaging spectrometer,
remote sensing, second-order light correction.
I. I NTRODUCTION
T
HE Hyperspectral Imager for the Coastal Ocean (HICO)
sensor [1] is a spaceborne imaging spectrometer designed
specifically for remote sensing of the complex coastal environment. It is a conventional hyperspectral imaging sensor, incorporating an Offner grating-type spectrometer [2] and covering
a scene in push-broom mode. The HICO sensor was built at the
Naval Research Laboratory in Washington, DC. It was launched
into space on a Japanese HII-B rocket from Tanegashima Space
Center, Japan, on September 11, 2009, and docked with the
International Space Station (ISS) on September 24, 2009. HICO
is now generating hyperspectral imaging data in the wavelength
range of 0.4–0.9 μm with a spectral resolution of 5.7 nm and
a spatial resolution of approximately 90 m. The total spectral
range covered by HICO is from 0.35 to 1.08 μm, but data
outside of the 0.4–0.9-μm range are typically not reported due
Manuscript received December 13, 2010; revised April 6, 2011; accepted
June 19, 2011. Date of publication September 15, 2011; date of current version
February 24, 2012. This work was supported in part by the U.S. Office of Naval
Research.
The authors are with the Remote Sensing Division, Naval Research Laboratory, Washington, DC 20375 USA (e-mail: rong-rong.li@nrl.navy.mil).
Digital Object Identifier 10.1109/TGRS.2011.2163161
to the low sensitivity of the sensor at extreme blue and red
wavelengths. It is expected that improved understanding of the
global coastal waters as well as certain inland lakes [3] can be
obtained through analysis of HICO data.
Within the nominal spectral range of 0.35–1.08 μm covered
by the HICO sensor, the second-order light in the wavelength
interval between 0.35 and 0.54 μm falls in the same pixels as
the first-order light in the 0.7–1.08-μm wavelength interval.
It was originally planned that a second-order blocking filter
would be placed close to the focal plane array (FPA) of HICO,
but mechanical mounting problems were encountered, and the
tight development schedule of the program did not leave time
to find a reliable solution. As a result, the near-IR channels of
the HICO sensor receive both the first-order radiances from the
near-IR spectral region and the second-order radiances from the
visible region.
In order to achieve accurate radiometric calibrations of the
HICO near-IR channels above 0.8 μm, the second-order light
effects must be removed. The real water-leaving radiances of
the near-IR channels over clear ocean waters are close to zero
because of strong liquid water absorption above 0.8 μm [4].
Based on the water absorption property and through analysis of
HICO imaging data containing features of shallow underwater
objects, such as coral reefs, we have developed an empirical
technique to correct the second-order light effects in near-IR
channels. In this paper, we describe the empirical correction
technique and present results from application of the technique
to HICO data. The same technique is, in principle, applicable
for the correction of second-order light effects from hyperspectral imaging data acquired with similar sensors without orderseparation filters.
II. BACKGROUND
Previously, through analysis of hyperspectral imaging data
collected with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) [5], [6], we have found that shallow underwater
objects are not observed in near-IR channel images. AVIRIS is
an instrument free of the second-order light effects because it
is equipped with several order-separation filters [6]. Fig. 1(a)
shows a true-color AVIRIS red–green–blue (RGB) image (red:
0.66 μm; green: 0.55 μm; blue: 0.47 μm) acquired over French
Frigate Shoals in Hawaiian waters in April of 2000. Underwater
features, such as coral reefs (spot in light green color) and shallow water (in light blue color), are clearly seen. Fig. 1(b) shows
a 1.0-μm single-channel image of the same scene. Underwater
coral reef features are no longer seen in this image because of
strong liquid water absorption in the near-IR spectral region.
U.S. Government work not protected by U.S. copyright.
LI et al.: TECHNIQUE FOR REMOVING SECOND-ORDER LIGHT EFFECTS
Fig. 1. (a) True-color AVIRIS image acquired over French Frigate Shoals in
Hawaiian waters in April of 2000 and (b) a 1.0-μm single-channel image of the
same scene. Underwater coral reef features are seen obviously in (a) but not in
(b) due to strong liquid water absorption in the near-IR spectral region.
825
0.55 μm in the visible is as large as 90%. Based on Fig. 2(b),
we expect that the underwater objects 2 m below the air–water
interface will be seen in visible channel images but not in
images of near-IR channels above 0.75 μm.
Soon after the ISS HICO data became available, we observed
shallow underwater features in images of near-IR channels
close to 0.9 μm. Based on our previous experiences with
AVIRIS data [see Fig. 1(b)], we realized that the underwater
features in these images resulted from the second-order light of
visible channels. Fig. 3 shows an example of a HICO data set
acquired over Midway Island in the Pacific Ocean on October
20, 2009. The image in Fig. 3(a) is the true-color RGB image,
and the images in Fig. 3(b)–(j) are single-band images at the
wavelengths stated in each image. In the RGB image, the area
in light blue color is the atoll. The surrounding regions in black
color are deepwater areas. Eastern Island (left) and Sand Island
(right) also appear in the lower region of the atoll. Spatial
features of shallow underwater objects are seen in the RGB
image and in the images of shorter wavelength channels, such
as those wavelengths at λ = 0.502 and 0.600 μm. Because of
strong liquid water absorption in the near-IR spectral region,
these underwater features should disappear in all the near-IR
channel images. The spatial features are not seen obviously
in the 0.857-μm channel image [see the image in Fig. 3(e)],
where only the two small islands and the outline of the atoll are
seen. However, due to the increased second-order light effects,
the underwater features reappear in the images for channels at
longer wavelengths starting from Fig. 3(f) and become stronger
as wavelength increases [see the images in Fig. 3(f)–(j)].
III. M ETHOD
Fig. 2. (a) Liquid water absorption coefficient as a function of wavelength and
(b) transmittance spectrum for light passing through a 4-m-thick liquid water
layer.
In order to illustrate the liquid water absorption properties,
we show in Fig. 2(a) the liquid water absorption coefficient
[7] in the range of 0.3–1.1 μm. It is noted that the liquid
water absorption coefficient increases by two orders of magnitude from 0.55 to 0.86 μm. Fig. 2(b) shows the calculated
transmittance spectrum for light passing through a liquid water
layer with a thickness of 4 m. The transmittance of pure water
decreases rapidly with increasing wavelength in the 0.5–1.0-μm
spectral region. For wavelengths greater than about 0.75 μm,
the transmittances are close to zero, while the transmittance at
In order to recover the true near-IR channel radiances from
HICO data, the second-order light needs to be removed completely from the total radiances received by these channels.
Through analysis of data acquired over water surfaces with
underwater features, such as coral reefs, we have developed
an effective empirical method for quantifying the second-order
light. This method uses the fact that, if second-order light were
not present, spatial features of coral reefs and other objects in
shallow-water areas should not be observed in images taken
at wavelengths near 1 μm. This is because solar radiation at
these wavelengths is totally absorbed by liquid water. The observation of spatial features of shallow-water objects in images
of channels near 1 μm is an indication of the presence of
second-order light. Based on this, we establish an equation to
calculate the intensities contributed by the second-order light
and subtract them out from the radiances of near-IR channels.
It should be pointed out that, although no spatial features are
observed over deepwater areas in near-IR channel images [see
Fig. 3(f)–(j)], the signals of these channels are also affected by
the second-order light of visible channels.
To develop the method, we extract a pair of spectra over
shallow water S(λ) and nearby deep water D(λ) from the
HICO observation of Midway Island shown in Fig. 3. The
points are chosen just inside and just outside the coral reef,
separated by, at most, a few kilometers in order to minimize
atmospheric path radiance differences between them (we will
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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 50, NO. 3, MARCH 2012
Fig. 3. Sample ISS HICO images acquired over Midway Island in the Pacific Ocean on October 20, 2009, (first and second rows from a to j) before and (third
row from k to o) after the removal of second-order light. See text for detailed descriptions. (a) RGB. (b) 0.502 μm. (c) 0.600 μm. (d) 0.703 μm. (e) 0.857 μm.
(f) 0.903 μm. (g) 0.955 μm. (h) 1.001 μm. (i) 1.035 μm. (j) 1.064 μm. (k) 0.903 μm. (l) 0.955 μm. (m) 1.001 μm. (n) 1.035 μm. (o) 1.064 μm.
return to this point in Section V). Note that the width of the
Midway scene is about 30 km. We use p(λ) to represent the
empirical correction factor for removing second-order light.
The basic equation for the derivation of p(λ) is
S(λ) − p(λ)S(λ/2) = D(λ) − p(λ)D(λ/2)
(1)
where S(λ) is the signal (in digital numbers (DNs) from the
FPA, not in radiometrically calibrated values) from the shallowwater area at λ, D(λ) is the signal from the deepwater area at λ,
S(λ/2) is the signal from the shallow-water area at half wavelength (λ/2), D(λ/2) is the signal from the deepwater area at
λ/2, and p(λ) is the empirical scaling factor for correcting the
second-order light effect, which is also the fraction of the firstorder light leaking into the near-IR detectors. In principle, (1)
applies to wavelengths longer than about 0.75 μm. However, the
characteristics of the HICO grating are such that second-order
light is nearly zero at wavelengths near 0.8 μm, and indeed, no
second-order artifacts appear in Fig. 3(e). In practice, then, (1)
is applied to wavelengths longer than about 0.85 μm.
Both the shallow-water signal S(λ) and deepwater signal
D(λ) are directly obtained from the original HICO data in DNs.
S(λ/2) and D(λ/2) are the corresponding quantities at the
half wavelength (λ/2), and their values are obtained through
linear interpolation of the original HICO spectral data. The term
p(λ) S(λ/2) on the left side of (1) is the second-order signal at
the near-IR wavelength λ contributed by the signal at λ/2 for
the shallow-water spectrum. Similarly, the term p(λ) D(λ/2)
on the right side of (1) is the second-order signal for the
deepwater spectrum. After the corrections of the second-order
effects, the near-IR channel signal over the shallow-water and
deepwater areas should be equal. Solving for p(λ), (1) can be
rewritten as
p(λ) = [S(λ) − D(λ)] / [S(λ/2) − D(λ/2)] .
(2)
An empirical scaling factor p(λ) can be calculated from hyperspectral imaging data according to (2).
In order to generate p(λ) for the second-order light corrections to all HICO data, we selected a number of pairs of
shallow-water and nearby deepwater spectra. We calculated
an empirical curve for each pair of spectra using (2). Each
spectrum used in the calculations was obtained from a spatial
averaging of spectra over 3-by-3 to 10-by-10 homogeneous
water pixels with a standard deviation less than 3%. Fig. 4
shows examples of correction curves obtained from several
pairs of water areas. They are approximately linear functions of wavelength, particularly for wavelengths greater than
0.9 μm. The black diamonds are the averaged values from
all the selected data points. A linear fit (the black line) to
the averaged values gives a correlation coefficient of 0.97.
LI et al.: TECHNIQUE FOR REMOVING SECOND-ORDER LIGHT EFFECTS
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Fig. 4. Empirical scaling factors as a function of wavelength for second-order
light corrections over different locations. The black line shows the averaged
values of all the locations.
Approximately 1% to 3% of the first-order light in the visible is
leaked into the near-IR detectors.
IV. S AMPLE DATA S ETS AND R ESULTS
After generating the scale factor p(λ), we make the correction for HICO data sets on a pixel-by-pixel basis. The equation
to correct the data is
C(λ) = f (λ) − p(λ) ∗ f (λ/2)
(3)
where f (λ) is the signal at λ, p(λ) is the correcting factor,
f (λ/2) is the signal at λ/2, and p(λ) ∗ f (λ/2) is the secondorder contribution. C(λ) is the signal after the second-order
correction.
We have applied (3) to HICO data sets, and quite reasonable
results have been obtained. The results from two HICO data
sets are presented hereinafter.
A. Midway Island
Examples of second-order corrected Midway Island images
are shown in the third row in Fig. 3. The images in Fig. 3(k)–(o)
correspond to the images in Fig. 3(f)–(j), except for the secondorder light correction. The shallow-water features seen in the
images in Fig. 3(f)–(j) have disappeared in the images in
Fig. 3(k)–(o). This demonstrates that the second-order light
effects have been removed properly. It is noted that the two
small islands, the circle around the edge of the atoll, and clouds
are still present. The circle is most likely resulted from the
scattering of solar radiation by foams from breaking waves, and
it is not due to the second-order effect of visible light.
In order to facilitate the sensitivity and error analysis on our
second-order light correction technique, we have enlarged the
image in Fig. 3(a) around the Midway Island. Fig. 5(a) shows
the resulting image. Fig. 5(b) shows examples of spectral plots
for HICO data in DNs over shallow-water and deepwater areas
before and after the second-order light removal. Two shallow-
Fig. 5. (a) Magnified HICO RGB image acquired over Midway Island in the
Pacific Ocean on October 20, 2009, and (b) examples of spectral plots for HICO
data in DNs. See text for detailed descriptions.
water spectra from area 1 and area 2, as marked in Fig. 5(a),
and two deepwater spectra from area 3 and area 4, also marked
in the image, are plotted. In the visible spectral region, the
shallow-water areas have DNs between approximately 3000
and 6000, while the deepwater areas have DNs about 2000. The
inset is a magnified spectral plot for a smaller wavelength range
between 0.8 and 1.05 μm. The dashed lines are the spectra
of the four locations before the second-order light corrections.
Both types of spectra, either shallow-waters from area 1 and
area 2 or deepwaters from area 3 and area 4, contain extra
DNs due to the second-order light from the visible spectral
region. The DNs vary from approximately 40 for deepwater
spectra (areas 3 and 4) to as high as 100 for the shallowwater spectrum (area 1) at 1 μm. The solid lines are the same
spectra but after the removal of the second-order light effects.
It is seen that, after the corrections, both the shallow-water
and deepwater spectra (solid lines) above 0.85 μm are reduced
significantly. The signals from both types of waters are reduced
to about ten DNs at 1 μm, which are approximately 70% to 90%
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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 50, NO. 3, MARCH 2012
Fig. 6. HICO images at the 1-μm channel (left) before and (right) after the
second-order light correction over Midway Islands on October 20, 2009.
over the Bahamas in the Atlantic Ocean on October 22, 2009,
using the correction factor derived from the Midway scene.
The image in Fig. 7(a) is the true-color RGB image. The left
portions of the image in blue and green colors are shallow-water
areas. The right dark portions of the image are deepwater areas.
The white spots in the images are cumulus clouds.
Spatial features in shallow-water areas are clearly seen in
the left portions of the image. A sharp boundary is observed
between the shallow-water and deepwater areas. The images
in Fig. 7(b)–(h) are single-band images with the wavelength
stated above each image. When the second-order effects are
not present, the spatial features should not appear in the images
in Fig. 7(d)–(h) because of strong liquid water absorption for
wavelengths longer than 0.8 μm [see Fig. 2(b)]. Fig. 7(d) shows
the 0.86-μm image, in which the shallow-water features are not
seen obviously, just as expected. However, the spatial features
reappear in the images in Fig. 7(e)–(h) due to the presence of
the second-order light effects. The images in Fig. 7(i)–(l) are the
same channel images as those in Fig. 7(e)–(h), except that the
second-order light effects are removed. After the correction of
the second-order light effect, the shallow-water features in the
near-IR channel images have disappeared, while the cumulus
cloud features remain in the images.
V. D ISCUSSION
Fig. 7. Sample ISS HICO images acquired over Bahamas in the Atlantic
Ocean on October 22, 2009. Image (a) is the true-color RGB image. The
left portions of the image are covered by shallow waters with reflection from
the bottom. The right portions of the image are covered by deep waters.
Images (b)–(h) are single-band images at wavelengths as shown. The spatial
features observed in images (e)–(h) are due to the presence of the secondorder light effects. Images (i)–(l) correspond to images (e)–(h), respectively,
except that the second-order light effects are removed. (a) RGB. (b) 0.502 μm.
(c) 0.600 μm. (d) 0.860 μm. (e) 0.903 μm. (f) 0.955 μm. (g) 1.001 μm.
(h) 1.035 μm. (i) 0.903 μm. (j) 0.955 μm. (k) 1.001 μm. (l) 1.035 μm.
reductions from their uncorrected signals. The estimated error
in the second-order light correction is approximately 2%.
In order to further demonstrate the effects of second-order
light correction, we show a single-channel false-color image at
1 μm in Fig. 6 before (left plot) and after (right plot) the secondorder light correction. The two images used the same color bar,
as shown in the middle plot in Fig. 6. From the left image in
Fig. 6, it is seen that the DNs are approximately in the range
between 70 and 140 in shallow-water areas and about 40–60 in
deepwater areas before the correction. After the correction, the
DNs over both the shallow waters and deep waters are reduced
as shown. By comparing the two images in Fig. 6, it is seen
quantitatively the dramatic reduction of unwanted DNs after the
removal of the second-order light effect.
B. Bahamas, Atlantic Ocean
Another example of the second-order correction is shown in
Fig. 7. The images are processed from the HICO data acquired
The HICO sensor is not the only hyperspectral sensor built
without a blocking filter to eliminate the second-order light
effects. Over the past three decades, many hyperspectral sensors were built without implementation of blocking filters.
For example, the Airborne Imaging Spectrometer (AIS) [8],
[9] covered a spectral interval of 0.9–2.4 μm and contained
no blocking filters in the optical train to prevent overlapping
spectral orders at infrared wavelengths. The radiances measured
with AIS in the early 1980s for channels above 1.5 μm were
positively identified to be contaminated by radiances from the
λ/2 wavelength interval [10]. At the time, a rigorous removal of
the unwanted spectral contamination did not seem possible, and
blocking filters were recommended for inclusion in the optical
trains of imaging spectrometers [10]. Later on, the Compact
High Resolution Imaging Spectrometer (CHRIS) [11] covering
a solar spectral range between 0.4 and 1.05 μm on board the
Project for On Board Autonomy-1 mission of the European
Space Agency did not contain a blocking filter either. CHRIS
was intended for land use, where the signal at the red end
(> 0.65 μm) of the spectrum is typically much higher than that
for a water scene. Therefore, the contamination by second-order
light from blue is less important for CHRIS than for HICO.
At present, some airborne imaging spectrometers built for the
spectral range between approximately 0.4 and 1.05 μm use
special silicon detector arrays, which have low sensitivity for
blue light in the region of the array where red light from the
grating would fall. Thus, the second-order filter is effected in
the construction of the FPA. However, this approach is not as
effective as a second-order filter that completely blocks shortwavelength light, and the empirical technique described in this
paper should be applicable for the correction of second-order
light effects of hyperspectral data measured with these sensors.
LI et al.: TECHNIQUE FOR REMOVING SECOND-ORDER LIGHT EFFECTS
Ideally, there would be no spread in the curves shown in
Fig. 4. To explain the existence of the spread, we first examine
in more detail the assumption that no light comes from below
the water surface at near-IR wavelengths. As seen in Fig. 3, the
shortest wavelength at which a perceptible second-order effect
is visible is about 0.9 μm. Inspection of Fig. 2(a) shows that
the 1/e absorption path of water at this wavelength is about
15 cm. Thus, if the water column contains a significant amount
of scattering material within a quarter meter or so of the
surface, the assumption that no light is returned from below
the surface may not be strictly valid. This contribution to the
signal in (1) would cause an error in the calculation of p(λ)
using (2).
As noted in Section III, the shallow-water and deepwater
comparison points were chosen just inside and just outside of
the coral reefs. Atmospheric path radiance normally changes
very slightly over a distance of a few kilometers, but it is
possible that the atmosphere, particularly the near-surface atmosphere, is sufficiently different between the two points that
the assumption of the constancy of atmospheric path radiance
is not strictly valid.
We attribute the spread in the curves in Fig. 4 to the
aforementioned effects, but the basic validity of the method is
demonstrated by the fact that the correction coefficient derived
from four small areas in the Midway scene works very well for
the whole scene, as shown in Section IV-A. If long-wavelength
light from the water column (or the bottom) were interfering,
then the correction would not apply to the whole scene unless
the water properties and/or bottom type were the same everywhere, which is extremely unlikely. Similar remarks apply to
the effects of atmospheric path radiance variations. The case
for the method’s validity is reinforced by the fact that the same
correction coefficient also applies equally well to a completely
different scene in the Bahamas, as shown in Section IV-B.
The second-order correction factor based on the Midway
scene has been applied to other scenes with similarly good
results.
VI. S UMMARY
Because the HICO sensor, currently on board the ISS, is
not equipped with an order-separation filter, the second-order
light from the shorter visible spectral region falls onto the
detectors covering the near-IR spectral region above 0.8 μm.
We have developed a new technique to correct for the secondorder light effects, using the fact that water-leaving radiances
of near-IR channels above 0.8 μm over shallow ocean waters
are close to zero because of strong liquid water absorption.
The technique is developed using pairs of shallow-water and
nearby deepwater spectra acquired over Midway Island in the
Pacific Ocean. Its effectiveness has been demonstrated using
the full Midway Island image and the image acquired over
the Bahamas Banks in the Atlantic Ocean. The technique has
been used operationally for radiometric calibrations of the
entire HICO data sets. The same technique should, in principle,
be applicable for the correction of second-order light effects
from hyperspectral imaging data acquired with similar sensors
without order-separation filters.
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Rong-Rong Li received the B.S. degree in physics
from Nankai University, Tianjin, China, in 1982,
and the M.S. and Ph.D. degrees in physics from the
University of Cincinnati, Cincinnati, OH, in 1989
and 1995, respectively.
She is currently with the Remote Sensing
Division, Naval Research Laboratory, Washington,
DC. Her present work includes characterization and
calibration of hyperspectral imaging sensors. Her research involved atmospheric corrections, vegetation
indices, fires and burnt scar detections, and coastal
water studies using multispectral and hyperspectral imaging data acquired from
both the aircraft and satellite platforms.
Robert Lucke received the M.S. and Ph.D. degrees in physics from the Johns Hopkins University,
Baltimore, MD, in 1971 and 1975, respectively.
Since 1982, he has been with the Naval Research
Laboratory, Washington, DC, where he has flown airborne systems for measuring IR signatures of targets
and backgrounds and developed computer models
and image processing techniques to analyze the data
that they return. He has worked extensively in optical
modeling, including the use of aberration theory and
of Fourier optics. Since 1994, he has been with the
Remote Sensing Division, Naval Research Laboratory, where he has worked in
the areas of sparse-aperture and synthetic aperture imaging, optical system design, and, recently, hyperspectral imaging from airborne, and now spaceborne,
platforms. He headed up the team that built the Hyperspectral Imager for the
Coastal Ocean, which is now returning images from the International Space
Station.
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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 50, NO. 3, MARCH 2012
Daniel Korwan received the Ph.D. degree in physics
from Virginia Polytechnic Institute and State University, Blacksburg, in 1996.
He joined the Remote Sensing Division, Naval Research Laboratory, Washington, DC, in 1996, where
his primary work has focused on the development
and deployment of space- and airborne-based visible
and infrared spectral sensors, primarily for ocean and
atmospheric research. He was part of the team that
specified and constructed the Hyperspectral Imager
for the Coastal Ocean and was the lead for the optical
alignment, optical characterization, and radiometric characterization of the
instrument.
Bo-Cai Gao received the B.S. degree in physics
from Nankai University, Tianjin, China, in 1982, and
the M.S. and Ph.D. degrees in physics from The
Ohio State University, Columbus, in 1984 and 1988,
respectively.
He is currently with the Remote Sensing
Division, Naval Research Laboratory, Washington,
DC. He has conducted research on remote sensing
of cirrus clouds, atmospheric water vapor, and
coastal water using multichannel data collected with
the National Aeronautics and Space Administration
(NASA) Terra and Aqua Moderate Resolution Imaging Spectroradiometer
instruments. He is the inventor of the normalized difference water index, which
is widely used in the vegetation research community.
Dr. Gao was a recipient of the Prize Paper Award from the IEEE Geoscience
and Remote Sensing Society in 1991 for his development of an operational
atmospheric radiative transfer code to retrieve surface reflectance spectra from
hyperspectral imaging data measured with the NASA/Jet Propulsion Laboratory Airborne Visible/Infrared Imaging Spectrometer.