The CHEM spectrometer on the CCE spacecraft is designed to measure the mass and charge-state compositions as well as the energy spectra and pitch-angle distributions of all major ions from H through Fe with energies from 0.3 to 300 keV/charge and a time resolution of less than 1 min in the Earth's magnetosphere and magnetosheath. It has the sensitivity and resolution to detect artificially injected Li ions. Complementing the hot-plasma composition experiment and the medium-energy particle analyzer, this experiment will provide essential information on outstanding problems related to dynamical processes of space plasmas and of suprathermal ions. The instrument uses a combination of electrostatic deflection, post acceleration, and time of flight versus energy measurements to determine the ionization state Q, mass M, and energy E of the ambient-ion population. Pitch angle and anisotropy measurements are made utilizing the spinning motion of the CCE spacecraft. Isotopes of hydrogen and helium are resolved as are individual elements up to neon and dominant elements up to iron. Because of the intrinsically low instrument background achieved by using fast coincidence techniques combined with electrostatic deflection, the instrument has a large dynamic range and can identify rare elements and ions even in the presence of high-intensity radiation background. To increase significantly the information returned from the experiment within the allocated telemetry, an intelligent on-board data system which is part of the CHEM instrument performs fast M versus M/Q classifications.
In 1985, the authors reported the development of a semiempirical
dielectric model for soils, covering the frequency range between 1.4 and
18 GHz. The model provides expressions for the real and imaginary parts
of the relative dielectric constant of a soil medium in terms of the
soil's textural composition (sand, silt, and clay fractions), the bulk
density and volumetric moisture content of the soil, and the dielectric
constant of water at the specified microwave frequency and physical
temperature. This communication provides similar expressions for the
0.3-1.3-GHz range. Upon comparing experimental results measured in this
study with predictions based on the semiempirical model, it was found
that the model underpredicts the real part of the dielectric constant
for high-moisture cases and underestimates the imaginary part for all
soils and moisture conditions. A small linear adjustment has been
introduced to correct the expression for the real part and a new
equation was generated for the effective conductivity to correct the
expression for the imaginary part. In addition, dielectric measurements
were made to evaluate the dependence of the dielectric constant on clay
type. The results show significant variations for the real part and
large variations for the imaginary part among soils with the same clay
fractions but with clays of different specific surface areas
Advanced Land Imager (ALI), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and Hyperion imaging spectrometer data covering an area in the Central Andes between Volcan Socompa and Salar de Llullaillaco were used to map hydrothermally altered rocks associated with several young volcanic systems. Six ALI channels in the visible and near-infrared wavelength range (0.4-1.0 μm) were useful for discriminating between ferric-iron alteration minerals based on the spectral shapes of electronic absorption features seen in continuum-removed spectra. Six ASTER channels in the short wavelength infrared (1.0-2.5 μm) enabled distinctions between clay and sulfate mineral types based on the positions of band minima related to Al-OH vibrational absorption features. Hyperion imagery embedded in the broader image coverage of ALI and ASTER provided essential leverage for calibrating and improving the mapping accuracy of the multispectral data. This capability is especially valuable in remote areas of the earth where available geologic and other ground truth information is limited.
Over the past two decades, a key indicator of climate change has
been the long time series of global maps of the normalized difference
vegetation index (NDVI), derived from remotely sensed data acquired with
a series of NOAA advanced very high resolution radiometer (AVHRR)
instruments from space. These NDVI values are calculated from relatively
broad AVHRR channels in the red and near-infrared regions. Continuation
of this long term data set is extremely valuable for climate-related
research, However, sometime in the coming decade, the AVHRR time series
measurements will no longer be continued. Instead, the measurements will
be made using newer generation satellite instruments having narrower
channels and improved spatial resolution. For example, the moderate
resolution imaging spectroradiometer (MODIS) onboard the Terra
spacecraft has several narrow channels in the 0.4-1.0 spectral range.
The NDVI values derived from the MODIS red channel and near-IR channel
will be biased compared to those derived from the broader AVHRR channels
because of differences in channel positions and widths for the two
instruments. The narrow MODIS near-IR channel is only slightly affected
by atmospheric water vapor absorption, while the broad AVHRR near-IR
channel is strongly affected by water vapor absorption. As a result, the
largest bias comes from the near-IR channels on the two instruments. To
a lesser extent, the bias also comes from the differences between the
red channel positions and the widths of MODIS and AVHRR instruments. In
this paper, the authors describe a practical method for simulating AVHRR
NDVI values using several narrower MODIS channels in the 0.4-1.0 μm
spectral range, including the MODIS green channel and the water vapor
In this paper, we introduce a method to retrieve the optical thickness of tropical cirrus clouds using the isolated visible cirrus reflectance (without atmospheric and surface effects). The isolated cirrus reflectance is inferred from level 1b calibrated 0.66- and 1.375-μm Moderate Resolution Imaging Spectroradiometer (MODIS) data. We created an optical properties database and optical thickness lookup library using previously calculated single-scattering data in conjunction with the discrete ordinates radiative transfer (DISORT) code. An algorithm was constructed based on this lookup library to infer the optical thickness of tropical cirrus clouds for each pixel in a MODIS image. We demonstrate the applicability of this algorithm using several independent MODIS images from the Terra satellite. The present method is complimentary to the MODIS operational cloud retrieval algorithm for the case of cirrus clouds.
To assess the utility of laser altimetry for studies in dynamical
oceanography, the authors present a comparison of the Shuttle Laser
Altimeter (SLA)-01 and the TOPEX/POSEIDON (T/P) radar altimeter on
global and regional scales. They compare all ~1.1 million SLA-01 range
measurements over the oceans to the CSRMSS95 gridded mean sea surface
model and find the overall root mean square (RMS) difference to be 2.33
m. The misfit was improved significantly by removing the mean and trend
from individual SLA-01 profiles, often resulting in RMS differences less
than 1 m. They also show that in regions where sea surface height varies
dramatically over relatively short horizontal scales such as across
major subduction zones, SLA-01 as capable of resolving rapid changes in
sea surface height. Finally, they examine a number of coastal zones and
illustrate SLA-01's ability to track continuously across the land-sea
interface, even in regions of dramatic coastal topography. The dominant
sources of radial error in the SLA-01 data are time-interval unit (TIU)
error (±0.75 m) and radial orbit error (1 m RMS). Therefore,
limitations of the SLA-01 data set are caused primarily by system
constraints as opposed to instrumentation error. Their results indicate
that future laser altimeters will provide valuable information regarding
ocean topography. In particular, laser altimetry data can be used to
supplement orbiting microwave ranging systems in coastal areas where
such sensors are incapable of maintaining lock across the
Lyzenga's paper ("Unconstrained inversion of waveheight spectra from SAR images" IEEE Trans. Geosci. Remote Sens., vol. 40, no. 2, pp. 261-270, Feb. 2002) after being corrected (ibid., vol. 40, no. 3, p. 729, Mar. 2002) has still a few remaining errors. This paper presents the additional corrections.
The IEEE Geoscience and Remote Sensing Society's Awards were presented at the IGARSS'03 banquet on Thursday, July 24 in the Hotel Dieu in Toulouse France. The GRS-S President Charles Luther, assisted by the Awards Committee Chairman Werner Wiesbeck, presented the awards. To promote excellence in research and service, each year the Geoscience and Remote Sensing Society of IEEE recognizes individuals among its members by bestowing IEEE certificates and awards.
The Advanced Synthetic Aperture Radar (ASAR) Global Monitoring (GM) mode offers an opportunity for global soil moisture (SM) monitoring at much finer spatial resolution than that provided by the currently operational Advanced Microwave Scanning Radiometer for the Earth Observing System and future planned missions such as Soil Moisture and Ocean Salinity and Soil Moisture Active Passive. Considering the difficulties in modeling the complex soil-vegetation scattering mechanisms and the great need of ancillary data for microwave backscatter SM inversion, algorithms based on temporal change are currently the best method to examine SM variability. This paper evaluates the spatial sensitivity of the ASAR GM surface SM product derived using the temporal change detection methodology developed by the Vienna University of Technology. This evaluation is made for an area in southeastern Australia using data from the National Airborne Field Experiment 2005. The spatial evaluation is made using three different types of SM data (station, field, and airborne) across several different scales (1-25 km). Results confirmed the expected better agreement when using point ( R <sub>station</sub> = 0.75) data as compared to spatial ( R <sub>PLMR, 1 km</sub> = 0.4) data. While the aircraft-ASAR GM correlation values at 1-km resolution were low, they significantly improved when averaged to 5 km ( R <sub>PLMR, 5 km</sub> = 0.67) or coarser. Consequently, this assessment shows the ASAR GM potential for monitoring SM when averaged to a spatial resolution of at least 5 km.
The 38 papers in this special issue were originally presented at the 9th Specialist Meeting on Microwave Radiometry and Remote Sensing Applications (MicroRad '06). These papers are organized into topical areas and applications, which are in the general order of the MicroRad technical sessions: Radiometer Calibration and RFI Mitigation (4); Synthetic Aperture Radiometry (3); Land and Vegetation (6); Ocean Salinity (5); Ocean Wind (4); Atmosphere (3); Temperature and Humidity Sounding (8); and Precipitation (5).
The 14 papers in this special issue are organized into topical areas and applications, which are in the general order of the MicroRad technical sessions: Radiometer Techniques (4), Vegetation (2), Ocean (2), Atmosphere and Precipitation (4), and Snow and Sea Ice (2).
The nine papers in this special issue were originally presented at the 2009 International Geoscience and Remote Sensing Symposium (IGARSS '09), held at the University of Cape Town, Rondebosch, South Africa, from July 12 to 17.
The methodology used to store a number of the Moderate Resolution
Imaging Spectroradiometer (MODIS) land products is described. The
approach has several scientific and data processing advantages over
conventional approaches used to store remotely sensed data sets and may
be applied to any remote-sensing data set in which the observations are
geolocated to subpixel accuracy. The methodology will enable new
algorithms to be more accurately developed because important information
about the intersection between the sensor observations and the output
grid cells are preserved. The methodology will satisfy the very
different needs of the MODIS land product generation algorithms, allow
sophisticated users to develop their own application-specific MODIS land
data sets, and enable efficient processing and reprocessing of MODIS
land products. A generic MODIS land gridding and compositing algorithm
that takes advantage of the data storage structure and enables the
exploitation of multiple observations of the surface more fully than
conventional approaches is described. The algorithms are illustrated
with simulated MODIS data, and the practical considerations of increased
data storage are discussed
Identification of clouds over Earth's polar regions is difficult from satellite radiometric measurements in the visible and infrared (IR) atmospheric window regions because of the high albedos of snow- and ice-covered surfaces in the visible and the low-temperature contrast between the surface and the troposphere in the IR. The Moderate Resolution Imaging SpectroRadiometer (MODIS) on the Terra Spacecraft has a near-IR channel located within the strong water vapor absorption regions close to 1.38 μm. This channel was originally designed for remote sensing of high-altitude clouds in the tropical and mid-latitude regions. In this paper, we report that this channel is also quite useful for detecting high clouds in polar regions during the daytime. Comparisons with IR emission techniques for polar cloud detections are also presented.
The Moderate Resolution Imaging Spectro-Radiometer (MODIS) on the Terra spacecraft has a channel near 1.38 μm for remote sensing of high clouds from space. The implementation of this channel on MODIS was primarily based on previous analysis of hyperspectral imaging data collected with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). We describe an algorithm to retrieve cirrus bidirectional reflectance using channels near 0.66 and 1.38 μm. It is shown that the apparent reflectance of the 1.38-μm channel is essentially the bidirectional reflectance of cirrus clouds attenuated by the absorption of water vapor above cirrus clouds. A practical algorithm based on the scatterplot of 1.38-μm channel apparent reflectance versus 0.66-μm channel apparent reflectance has been developed to scale the effect of water vapor absorption so that the true cirrus reflectance in the visible spectral region can be obtained. To illustrate the applicability of the present algorithm, results for cirrus reflectance retrievals from AVIRIS and MODIS data are shown. The derived cirrus reflectance in the spectral region of 0.4-1 μm can be used to remove cirrus contamination in a satellite image obtained at a visible channel. An example of such an application is shown. The spatially averaged cirrus reflectances derived from MODIS data can be used to establish global cirrus climatology, as is demonstrated by a sample global cirrus reflectance image.
Techniques for retrieving cloud optical properties, i.e., the optical depths and particle size distributions, using atmospheric "window" channels in the visible and near-infrared spectral regions are well established. For partially transparent thin cirrus clouds, these "window" channels receive solar radiances scattered by the surface and lower level water clouds. Accurate retrieval of optical properties of thin cirrus clouds requires proper modeling of the effects from the surface and the lower level water clouds. In this paper, we describe a new concept using two strong water vapor absorption channels near 1.38 and 1.88 μm, together with one window channel, for remote sensing of cirrus optical properties. Both the 1.38- and 1.88-μm channels are highly sensitive in detecting the upper level cirrus clouds. Both channels receive little scattered solar radiances from the surface and lower level water clouds because of the strong water vapor absorption below cirrus. The 1.88-μm channel is quite sensitive to changes in ice particle size distributions, while the 1.38-μm channel is less sensitive. These properties allow for simultaneous retrievals of optical depths and particle size distributions of cirrus clouds with minimal contaminations from the surface and lower level water clouds. Preliminary tests of this new concept are made using hyperspectral imaging data collected with the Airborne Visible Infrared Imaging Spectrometer. The addition of a channel near 1.88 μm to future multichannel meteorological satellite sensors would improve our ability in global remote sensing of cirrus optical properties.
This paper presents a novel direct RF sampling receiver
architecture that will greatly facilitate the implementation of higher
spatial resolution satellite radiometers for improved near-term climate
forecasting. Direct-sampling is especially suitable for integration onto
the distributed, multiple element platform used in L-band synthetic
thinned array radiometry (STAR). To evaluate the direct-sampling
concept, the authors have developed a statistical model that predicts
the worst case radiometric sensitivity for a 1.4 GHz digital receiver.
Theoretical results show that only 2-3 bits of converter resolution are
needed to approach the performance of an ideal analog radiometer and
that sampling jitter will not significantly degrade the performance of
A measurement procedure has been developed and tested to determine
horizontal and vertical polarization radiative transfer properties,
i,e., single scattering albedo (ω) and optical depth (τ), of
vegetation under field conditions. The procedure was applied to a wheat
crop for a series of biomass densities. The measurements were done using
two different radiometers (1.4 and 5 GHz) and for different view angles.
The measurements and calculations indicated that the ratios of
horizontal and vertical polarization radiative transfer properties
β=ωh/ω<sub>ν</sub>) are slightly dependent on view
angle. However, no significant dependence on biomass density could be