Overseas Travel Report
1998 IEEE International Geoscience & Remote Sensing Symposium
(IGARSS'98)
Seattle, USA - 6 - 10 July 1998
Ian Grant
CSIRO Atmospheric Research
I attended the 1998 IEEE International Geoscience and Remote Sensing
Symposium (IGARSS'98) in Seattle, USA, 6--10 July 1998. David
Jupp from the CSIRO Earth Observation Centre (EOC) also attended.
Well over half of the presentations were devoted to radar, but
it is still a major international meeting in the optical remote
sensing of the earth's surface and, to a lesser extent, atmosphere.
Over the next three years IGARSS will be held in Hamburg, Hawaii
and Sydney (2001). I have a hardcopy program and the proceedings
on CD-ROM for this meeting, and also CD proceedings for the 1994,
1996, and 1997 meetings. The rest of this report summarizes the
papers I saw and discussions I had that I think are of most interest
to the EOC and particularly CAR.
AVHRR albedo and BRDF
My main priority was to learn what was being done in the areas
of retrieval of surface albedo and BRDF (Bidirectional reflectance
distribution factor - a quantitative description of the anisotropy
of the surface reflectance) from satellite observations, particularly
AVHRR, since getting results in those areas for continental Australia
will be the focus of my work with the EOC over the next couple
of years. Two presentations were devoted precisely to the generation
of global albedo maps from AVHRR.
Nic Strugnell of Alan Strahler's group at Boston University described
a scheme to generate albedo maps from AVHRR until high quality
BRDFs are available from MODIS. He recognised that for BRDF work
a new landcover classification based on vegetation structure is
necessary, and so he established a seasonally-dependent mapping
from an existing landcover classification into a BRDF classification.
David Jupp (and previously Dean Graetz) have commented that vegetation
structure is already well mapped for Australia but not for North
America or other continents - so we have an advantage here. To
each landcover class Strugnell will assign a BRDF shape from a
single field measurement, then for each month scale the BRDF to
fit a single AVHRR observation selected by a strict compositing
and cloud-detection scheme. He thus assumes that as the state
of a patch of vegetation changes the scale of the BRDF, and hence
the albedo, may change but not the shape of the BRDF. He justified
this by noting that darker surfaces generally have "flatter''
BRDFs - shallower bowl shape and less difference between forward
scatter and backscatter -but I think the assumption needs validation
and others I spoke to agreed.
I discussed with Garik Gutman and Ivan Csizar of NOAA/NESDIS their
scheme to derive global albedo maps from AVHRR data (GAC composited
or PATMOS). They use an empirical narrowband to broadband correction
and the ERBE angular models to derive the albedo at the top of
the atmosphere (TOA), and then use Li and Garand's parameterization
(dependent only on solar zenith angle and atmospheric water vapour
column amount) to convert to a surface albedo. They estimate the
total relative error to be 15% and freely concede that many of
the steps could be improved. They considered the alternative path
of atmospherically correcting the radiances first, then doing
the spectral and angular corrections at the surface but dismissed
it because the spectral and angular reflectance properties of
the surface are not sufficiently well characterised at present.
I came away from the meeting believing that the approach of fitting
the BRDF to timeseries of non-composited AVHRR observations, commenced
by Denis O'Brien and Ross Mitchell and to be continued by me,
is potentially a significant improvement over the two approaches
just described and very worthy of pursuit. The key is that the
new approach will use what information is contained in the AVHRR
observations regarding the BRDF of the surface at the location
and time in question, rather than relying on a single field-measured
BRDF shape, or on the fixed ERBE angular models (there are only
two for clear land: one for desert, one for vegetated surfaces).
While the final MODIS BRDF/albedo algorithm (known as Ambrals)
picks the best fitting of five sets of kernels, the at-launch
processing will use only the RossThick-LiSparse kernel combination.
Wolfgang Lucht told me that while the MODIS BRDF product was originally
going to omit Australia due to processing limitations, there is
a good chance now it will be included. He also showed me some
recent work on simulations of expected errors in retrievals from
sparse sampling, including the extrapolation of albedo to solar
zenith angles away from those of the measurements. I showed him
my recent work on the variation with solar zenith angle of the
albedo of the Hay site.
Crystal Schaff of Boston University applied the Ambrals algorithm
to combined AVHRR and GOES-8 data for New England and found that
the retrieved albedo maps showed the spatial structure and ranking
of brightness, and even BRDF shape, expected from a map of landcover
class but was unable to make a more quantitative check. The prediction
of the GOES radiance from the AVHRR observations alone was close
but had noticeable deviations. When I asked Wolfgang Lucht how
well the Ambrals BRDF fit was constrained by AVHRR observations
alone he confirmed that they had no way of telling other than
by looking at the reasonableness of results of trials. Alan Strahler
presented work by Feng Gao of the Chinese Academy of Sciences
on a new criterion for fitting BRDF models to angularly sparse
data sets, based on Tarantola's inversion theory - it apparently
works on as few as three view directions.
Andrew Hyman of Boston University presented field measurements
to determine how well a single albedometer on a tower characterized
a validation site in the face of spatial variability. Broadband
albedo measurements and hemispherical photographs were acquired
from a height of 4m at several points along transects through
grassland with shrubs, and compared with albedos retrieved from
AVHRR and POLDER. Hyman concluded that:
Other BRDF, POLDER
Stefan Sandmeier of GSFC presented
high-spectral resolution BRDFs of grass and emphasised the variation
with wavelength of the shape of the BRDF. The anisotropy of the
BRDF was greatest at the wavelengths at which the reflectance
was lowest (blue and red), as opposed to less anisotropy and higher
reflectance in the green and near-infrared, which Stefan ascribed
to the lesser occurrence of multiple scattering to smooth out
the field of exiting radiance. In fact even though the reflectance
went up and down across the spectrum there was a one-to-one correspondence
between reflectance and BRDF anisotropy for the cases he showed.
However, he said such a simple relation did not always hold, a
fact he put down to wavelength-dependent transmission of the vegetation
components.
I had a long discussion with Jean-Louis Roujean. A 10-day global
albedo product from the 8~months of POLDER data is now available.
Jean-Louis has commenced discussions with David Jupp regarding
bringing the airborne POLDER to Australia. Thus he was interested
in Australian sites uniform on a scale of about 10km or more;
I told him of the Amburla, Hay and Tinga Tingana sites.
Jean-Louis suggested to me that since the ratio of direct to diffuse
irradiance for clear sky changes with solar zenith angle, albedo
measurements over a clear day may be separated into direct and
diffuse albedos. This set me thinking about the cloudy-sky albedo
at the CIGSN sites, to which I hadn't previously paid attention.
It would be worthwhile looking for a stable albedo on uniformly
overcast days and looking for a significant difference from the
clear-sky albedo for the same surface. This would provide a test
of the calculation of cloudy-sky albedo (roughly diffuse albedo)
from clear-sky satellite observations as is done by, for instance,
the MODIS algorithms.
Calibration on deserts
Yves Govaerts of EUMETSAT described his calibration of the Meteosat
visible-band imager on African desert sites. He takes a fixed
BRDF shape from a model for desert and the spectrum from airborne
measurements. He claims a final accuracy of 5-10%. This is in
preparation for the operational vicarious calibration of SEVIRI
on MSG, the next generation of Europe's geostationary imager.
I was surprised that SEVIRI will not have on-board calibration.
I told Yves of recent Australian work on intercalibrating the
GMS imager against AVHRR; he was concerned that the spectral mismatch
of the two sensors would make intercalibration on bright desert
doubtful, but was more confident about the use of (more spectrally
flat) thick cloud as a target.
Francois Cabot of CNES, France, has used POLDER to characterized
the BRDF of 20 uniform desert sites in North Africa and hence
intercalibrate the VEGETATION, SeaWiFS and AVHRR sensors. The
degradation of VEGETATION he finds is consistent with that from
its on-board calibration. He plans to extend this work to SPOT-HRV,
ATSR-2 and GOME.
EOS
A morning of talks was devoted to the EOS AM-1 platform, which
won't be launched until at least a few months into 1999 because
spacecraft control software is not ready.
The calibration of CERES on TRMM has been checked by comparing
the ERBE-like processing of CERES with ERBE using the TOA longwave
radiation budget over the tropical ocean as a reference. There
is a systematic difference of 2% in the longwave calibration of
which about half is expected to be due to El~Nino and most of
the remainder to the inferior ERBE calibration. It was stated
that the calibration of the shortwave part of the CERES TOTAL
channel differs from ERBE by 1%.
Michael King described the MODIS algorithms to retrieve cloud
and aerosol properties and atmospheric water vapour. The cloud
mask is derived from 17 of the 36 bands and is threshold based
so as to be fast enough to apply on a per-pixel basis. The land
aerosol algorithms concentrated on bright desert and on dark dense
vegetation identified in the 2mm and 3mm channels, in which the aerosol is most transparent.
MODIS will provide CO2 slicing at the finest spatial
resolution yet.
The MISR aerosol retrieval aims at fairly coarse characterisation
of aerosols: particle size classed as small, medium or large;
refractive indices as dirty or clean - these two parameters constitute
the "underwear'' model shape - spherical or not; optical
depth to an accuracy of 0.05 or 20%, whichever is bigger.
Aerosol
Brent Holben showed climatologies of aerosol measurements from
several AERONET sunphotometer sites. The sites showed a marked
variety in the distribution of points on scatterplots of aerosol
optical depth versus angstrom exponent, which could be ascribed
to the different dominant aerosol types. He showed seasonal variations
in aerosol parameters.
Retrieval of aerosols over ocean from one week of data from the
GOME spectrometer on ERS-2 are encouraging, but aerosol retrievals
over land have been difficult and are unsatisfactory so far.
I was surprised when a talk from John Reagan's group described
extensions to the Forgan plot method for analysing sunphotometer
data. I had to go to Seattle to learn of Bruce's improvement on
the Langley plot! By relaxing the assumption of constant aerosol
amount and type throughout the morning or afternoon of observations
to constancy in the microphysical properties only, all spectral
channels can be calibrated with respect to an (already calibrated)
reference channel.
Hyperspectral thermal
A session on hyperspectral thermal imaging focussed mainly
on results from SEBASS, an airborne instrument constructed to
explore the utility of hyperspectral thermal data. SEBASS covers
3-5.5mm and
7.8-13.5mm
with a resolution of l /d
l @ 20, has a ground resolution
of 0.5-3m, and has flown 12 campaigns since 1995. The spectral
resolution will resolve the bands of surface materials and atmospheric
gases other than CO2. Chris Borel of Los Alamos National
Laboratory noted that there is hope that surface and atmospheric
effects can be distinguished because in general surface emissivity
spectra are much smoother than atmospheric absorption spectra.
J. Norman of the University of Wisconsin described simulations
to retrieve the boundary layer temperature rather than the land
surface temperature. V. Realmuto of JPL extracted from TIMS data
over a Hawaiian volcanic plume images of the SO2 column
abundance and LST which agreed with simultaneous data from the
Airborne Emission Spectrometer (AES).
SST
W. McKeown of the Naval Research Laboratory described a differential
absorption technique for profiling the skin sea surface temperature,
using wavelengths of 2mm and over, and covering depths to about 0.4mm.
He described a system of eight buoys for monitoring radiometric
SST with self-calibrating sensors atop 20-m masts. C. Donlon of
the Southhampton Oceanography Centre (SOC) described the SoSSTR
(Ship of Opportunity SST Radiometer) which is based on TASCO radiometers
and calibration targets on a rotating arm, and is designed to
be rugged for unattended operation. He then described the Infrared
Scanning Autonomous Radiometer (ISAR) which will build on the
experience of SOC and of the Rutherford-Appleton Laboratory's
SiSTER radiometer. It will use Heimann KT15 radiometers because
the TASCOs' calibration is demanding and they are susceptible
to thermal shock. ISARs are expected to be deployed on buoys from
(northern) spring 1999.
Lidar
K. Fischer of ERIM International described the "M10 Elastic Backscatter Lidar'', designed specifically to be a cheap, compact and robust atmospheric lidar which can run unattended in the field. It is housed in a waterproof rugged packing case of ~1m3 volume. It currently uses green light but an eye-safe version is being considered. In tests in 1997 it returned an aerosol profile every 15 minutes for most of 5 weeks.