By Topic

Geoscience and Remote Sensing, IEEE Transactions on

Issue 11 • Date Nov. 2006

Filter Results

Displaying Results 1 - 25 of 27
  • [Front cover]

    Page(s): c1
    Save to Project icon | Request Permissions | PDF file iconPDF (137 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Geoscience and Remote Sensing publication information

    Page(s): c2
    Save to Project icon | Request Permissions | PDF file iconPDF (39 KB)  
    Freely Available from IEEE
  • Table of contents

    Page(s): 2997 - 2998
    Save to Project icon | Request Permissions | PDF file iconPDF (50 KB)  
    Freely Available from IEEE
  • Foreword to the March 2003 EOS Aqua AMSR-E Arctic Sea Ice Field Campaign Special Issue

    Page(s): 2999 - 3001
    Save to Project icon | Request Permissions | PDF file iconPDF (128 KB)  
    Freely Available from IEEE
  • List of reviewers

    Page(s): 3002
    Save to Project icon | Request Permissions | PDF file iconPDF (11 KB)  
    Freely Available from IEEE
  • March 2003 EOS Aqua AMSR-E Arctic Sea Ice Field Campaign

    Page(s): 3003 - 3008
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (599 KB)  

    An overview of the March 2003 coordinated sea ice field campaign in the Alaskan Arctic is presented with reference to the papers in this special section. This campaign is part of the program to validate the Aqua Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) sea ice products. Standard AMSR-E sea ice products include sea ice concentration, sea ice temperature, and snow depth on sea ice. The validation program consists of three elements, namely: 1) satellite data comparisons; 2) coordinated satellite/aircraft/surface measurements; and 3) modeling and sensitivity analyses. Landsat-7 and RADARSAT observations were used in comparative studies with the retrieved AMSR-E sea ice concentrations. The aircraft sensors provided high-resolution microwave imagery of the surface, atmospheric profiles of temperature and humidity, and digital records of sea ice conditions. When combined with in situ measurements, aircraft data were used to validate the AMSR-E sea ice temperature and snow-depth products. The modeling studies helped interpret the field-data comparisons, provided insight on the limitations of the AMSR-E sea ice algorithms, and suggested potential improvements to the AMSR-E retrieval algorithms View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Snow Depth and Ice Thickness Measurements From the Beaufort and Chukchi Seas Collected During the AMSR-Ice03 Campaign

    Page(s): 3009 - 3020
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1695 KB)  

    In March 2003, a field validation campaign was conducted on the sea ice near Barrow, AK. The goal of this campaign was to produce an extensive dataset of sea ice thickness and snow properties (depth and stratigraphy) against which remote sensing products collected by aircraft and satellite could be compared. Chief among these were products from the Polarimetric Scanning Radiometer (PSR) flown aboard a NASA P-3B aircraft and the Aqua Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). The data were collected in four field areas: three on the coastal sea ice near Barrow, AK, and the fourth out on the open ice pack 175 km northeast of Barrow. The snow depth ranged from 9.4-20.8 cm in coastal areas (n=9881 for three areas) with the thinnest snow on ice that had formed late in the winter. Out in the main pack ice, the snow was 20.6 cm deep (n=1906). The ice in all four areas ranged from 138-219 cm thick (n=1952), with the lower value again where the ice had formed late in the winter. Snow layer and grain characteristics observed in 118 snow pits indicated that 44% of observed snow layers were depth hoar; 46% were wind slab. Snow and ice measurements were keyed to photomosaics produced from low-altitude vertical aerial photographs. Using these, and a distinctive three-way relationship between ice roughness, snow surface characteristics, and snow depth, strip maps of snow depth, each about 2 km wide, were produced bracketing the traverse lines. These maps contain an unprecedented level of snow depth detail against which to compare remote sensing products. The maps are used in other papers in this special issue to examine the retrieval of snow properties from the PSR and AMSR-E sensors View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Spatial Variability of Barrow-Area Shore-Fast Sea Ice and Its Relationships to Passive Microwave Emissivity

    Page(s): 3021 - 3031
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1229 KB)  

    Aircraft-acquired passive microwave data, laser radar height observations, RADARSAT synthetic aperture radar imagery, and in situ measurements obtained during the AMSR-Ice03 experiment are used to investigate relationships between microwave emission and ice characteristics over several space scales. The data fusion allows delineation of the shore-fast ice and pack ice in the Barrow area, AK, into several ice classes. Results show good agreement between observed and Polarimetric Scanning Radiometer (PSR)-derived snow depths over relatively smooth ice, with larger differences over ridged and rubbled ice. The PSR results are consistent with the effects on snow depth of the spatial distribution and nature of ice roughness, ridging, and other factors such as ice age. Apparent relationships exist between ice roughness and the degree of depolarization of emission at 10, 19, and 37 GHz. This depolarization would yield overestimates of total ice concentration using polarization-based algorithms, with indications of this seen when the NT-2 algorithm is applied to the PSR data. Other characteristics of the microwave data, such as effects of grounding of sea ice and large contrast between sea ice and adjacent land, are also apparent in the PSR data. Overall, the results further demonstrate the importance of macroscale ice roughness conditions such as ridging and rubbling on snow depth and microwave emissivity View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Sea Ice Roughness From Airborne LIDAR Profiles

    Page(s): 3032 - 3037
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (419 KB)  

    Light detection and ranging (LIDAR) data acquired during the AMSR-Ice03 Arctic flights are used to observe and characterize the spectral behavior of sea ice roughness. Height distributions and roughness spectral densities are derived from surface profiles measured over a variety of sea ice types. The spectral densities are fit to Lorentzian curves to obtain the correlation length and root-mean-square height of roughness within the sampling bandpass of the LIDAR profiler. The utilization of these spectral parameters outside of their bandpass is also discussed View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Geostatistical Characterization of Snow-Depth Structures on Sea Ice Near Point Barrow, Alaska—A Contribution to the AMSR-Ice03 Field Validation Campaign

    Page(s): 3038 - 3056
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2890 KB)  

    The objective of this paper is to characterize spatial properties of snow-depth structures and their role as indicators of sea-ice properties and sea-ice-morphogenetic processes, and to provide quantitative measures of sea-ice properties that may be utilized in analyses of passive-microwave data. Snow-depth data collected near Point Barrow, Alaska, as part of the AMSRIce03 Field Validation Campaign for Advanced Microwave Scanning Radiometer (AMSR)-E-Sea-Ice Products from NASA earth-observing-systems satellite AQUA, are analyzed and compared to P-3 polarimetric scanning radiometer (PSR) data, a proxy for AMSR-E brightness temperatures. The approach taken in the analysis is geostatistical characterization. Various functions of first and second order are calculated for the snow-depth profiles, then geostatistical classification parameters are extracted and combined into feature vectors, on which the characterization is based. The complexity of sea ice requires a generalization of the method by introduction of the hyperparameter concept. Results include a quantitative characterization of sea-ice provinces from field transects in the Beaufort Sea, Chukchi Sea, and Elson Lagoon, which represent a good subset of Arctic sea-ice types, an internal segmentation of the longer profiles, and a derivation of surface-roughness length and of sea-ice-type complexity. PSR data reflect complexity of spatial snow-depth structures as captured in multidimensional feature vectors and, less directly, snow-depth and surface-roughness length. These results indicate that passive-microwave data in general may be affected by spatial snow depth and surface roughness, with a dependence on scale and quantified by geostatistical classification View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Assessment of EOS Aqua AMSR-E Arctic Sea Ice Concentrations Using Landsat-7 and Airborne Microwave Imagery

    Page(s): 3057 - 3069
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (976 KB)  

    An assessment of Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) sea ice concentrations under winter conditions using ice concentrations derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) imagery obtained during the March 2003 Arctic sea ice validation field campaign is presented. The National Oceanic and Atmospheric Administration Environmental Technology Laboratory's Airborne Polarimetric Scanning Radiometer Measurements, which were made from the National Aeronautics and Space Administration P 3B aircraft during the campaign, were used primarily as a diagnostic tool to understand the comparative results and to suggest improvements to the AMSR-E ice concentration algorithm. Based on the AMSR-E/ETM+ comparisons, a good overall agreement with little bias (~1%) for areas of first year and young sea ice was found. Areas of new ice production result in a negative bias of about 5% in the AMSR-E ice concentration retrievals, with a root mean square error of 8%. Some areas of deep snow also resulted in an underestimate of the ice concentration (~10%). For all ice types combined and for the full range of ice concentrations, the bias ranged from 0% to 3%, and the rms errors ranged from 1% to 7%, depending on the region. The new-ice and deep-snow biases are expected to be reduced through an adjustment of the new-ice and ice-type C algorithm tie points View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Assessment of the AMSR-E Sea Ice-Concentration Product at the Ice Edge Using RADARSAT-1 and MODIS Imagery

    Page(s): 3070 - 3080
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (954 KB)  

    Imagery from the C-band synthetic aperture radar (SAR) aboard RADARSAT-1 and the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to evaluate the performance of the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) ice-concentration product near the sea ice edge in the Bering Sea for four days during March 2003, which is concurrent with the AMSRIce03 field/aircraft campaign. The AMSR-E products were observed to perform very well in identifying open-water and pack-ice areas, although the AMSR-E products occasionally underestimate ice concentration in areas with thin ice. The position of the ice edge determined from AMSR-E data using a 15% concentration threshold was found to be, on average, within one AMSR-E grid square (12.5 km) of the ice edge determined from the SAR data, with the AMSR-E edge tending to be outside the SAR-derived edge View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Microwave Signatures of Snow on Sea Ice: Observations

    Page(s): 3081 - 3090
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (698 KB)  

    Part of the Earth Observing System Aqua Advanced Microwave Scanning Radiometer (AMSR-E) Arctic sea ice validation campaign in March 2003 was dedicated to the validation of snow depth on sea ice and ice temperature products. The difficulty with validating these two variables is that neither can currently be measured other than in situ. For this reason, two aircraft flights on March 13 and 19, 2003, were dedicated to these products, and flight lines were coordinated with in situ measurements of snow and sea ice physical properties. One flight was in the vicinity of Barrow, AK, covering Elson Lagoon and the adjacent Chukchi and Beaufort Seas. The other flight was farther north in the Beaufort Sea (about 73degN, 147.5degW) and was coordinated with a Navy ice camp. The results confirm the AMSR-E snow depth algorithm and its coefficients for first-year ice when it is relatively smooth. For rough first-year ice and for multiyear ice, there is still a relationship between the spectral gradient ratio of 19 and 37 GHz, but a different set of algorithm coefficients is necessary. Comparisons using other AMSR-E channels did not provide a clear signature of sea ice characteristics and, hence, could not provide guidance for the choice of algorithm coefficients. The limited comparison of in situ snow-ice interface and surface temperatures with 6-GHz brightness temperatures, which are used for the retrieval of ice temperature, shows that the 6-GHz temperature is correlated with the snow-ice interface temperature to only a limited extent. For strong temperature gradients within the snow layer, it is clear that the 6-GHz temperature is a weighted average of the entire snow layer View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Microwave Signatures of Snow on Sea Ice: Modeling

    Page(s): 3091 - 3102
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (811 KB)  

    Accurate knowledge of snow-depth distribution over sea ice is critical for polar climate studies. Current snow-depth-over-sea-ice retrieval algorithms do not sufficiently account for variations in snow and ice physical properties that can affect the accuracy of retrievals. For this reason, airborne microwave observations were coordinated with ground-based measurements of snow depth and snow properties in the vicinity of Barrow, AK, in March 2003. In this paper, the effects of snowpack properties and ice conditions on microwave signatures are examined using detailed surface-based measurements and airborne observations in conjunction with a thermal microwave-emission model. A comparison of the Microwave Emission Model of Layered Snowpacks (MEMLS) simulations with detailed snowpack and ice data from stakes along the Elson Lagoon and the Beaufort Sea and radiometer data taken from low-level flights using a Polarimetric Scanning Radiometer (PSR-A) shows that MEMLS can be used to simulate snow on sea ice and is a useful tool for understanding the limitations of the snow-depth algorithm. Analysis of radiance data taken over the Elson Lagoon and the Beaufort Sea using MEMLS suggests that the radiometric differences between the two locations are due to the differences in sea-ice emissivity. Furthermore, measured brightness temperatures suggest that the current snow-depth retrieval algorithm is sufficient for areas of smooth first-year sea ice, whereas new algorithm coefficients are needed for rough first-year sea ice. Snowpack grain size and density remain an unresolved issue for snow-depth retrievals using passive-microwave radiances View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Impact of Surface Roughness on AMSR-E Sea Ice Products

    Page(s): 3103 - 3117
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1301 KB)  

    This paper examines the sensitivity of Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperatures (Tbs) to surface roughness by a using radiative transfer model to simulate AMSR-E Tbs as a function of incidence angle at which the surface is viewed. The simulated Tbs are then used to examine the influence that surface roughness has on two operational sea ice algorithms, namely: (1) the National Aeronautics and Space Administration Team (NT) algorithm and (2) the enhanced NT algorithm, as well as the impact of roughness on the AMSR-E snow depth algorithm. Surface snow and ice data collected during the AMSR-Ice03 field campaign held in March 2003 near Barrow, AK, were used to force the radiative transfer model, and resultant modeled Tbs are compared with airborne passive microwave observations from the Polarimetric Scanning Radiometer. Results indicate that passive microwave Tbs are very sensitive even to small variations in incidence angle, which can cause either an over- or underestimation of the true amount of sea ice in the pixel area viewed. For example, this paper showed that if the sea ice areas modeled in this paper were assumed to be completely smooth, sea ice concentrations were underestimated by nearly 14% using the NT sea ice algorithm and by 7% using the enhanced NT algorithm. A comparison of polarization ratios (PRs) at 10.7, 18.7, and 37 GHz indicates that each channel responds to different degrees of surface roughness and suggests that the PR at 10.7 GHz can be useful for identifying locations of heavily ridged or rubbled ice. Using the PR at 10.7 GHz to derive an "effective" viewing angle, which is used as a proxy for surface roughness, resulted in more accurate retrievals of sea ice concentration for both algorithms. The AMSR-E snow depth algorithm was found to be extremely sensitive to instrument calibration and sensor viewing angle, and it is concluded that more work is needed to investigate the sensitivity of the gradient ratio at 37 a- - nd 18.7 GHz to these factors to improve snow depth retrievals from spaceborne passive microwave sensors View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Aircraft Measurements of Heat Fluxes Over Wind-Driven Coastal Polynyas in the Bering Sea

    Page(s): 3118 - 3134
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1326 KB)  

    The first estimates of the average bulk heat transfer coefficient for Arctic sea ice are presented as a function of mean ice thickness. Turbulent heat flux measurements made by the NASA P-3 over the St. Lawrence Island polynya (SLIP) and Kuskokwim Bay in the Bering Sea during AMSR-Ice03 were used to estimate the values of the heat transfer coefficient CH. Estimates of ice thickness were made from the algorithm of Perovich using broadband albedos obtained from Moderate Resolution Imaging Spectroradiometer data. Plots of CH as a function of ice thickness showed a nearly linear relationship for ice thicknesses in the range of 0-14 cm in the polynyas. Previous estimates of CH for different cases over the SLIP were 1.2times10-3, but no estimates of ice thickness were available. These results will allow more accurate estimates of heat fluxes from the thin-ice areas of polynyas using satellite retrievals View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Soil Moisture Estimates From AMSR-E Brightness Temperatures by Using a Dual-Frequency Algorithm

    Page(s): 3135 - 3144
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (420 KB)  

    This paper investigates the possibility of estimating the soil moisture content (SMC) on a global scale from dual-frequency (C- and X-bands) microwave data of the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Because some anomalous behavior was occasionally found in AMSR-E C- and X-band data, a calibration check compared the AMSR-E data with measurements from the SSM/I sensor over two reference targets, namely a Russian evergreen forest and the sea surface, both of which have already been studied in the past. The algorithm for retrieving soil moisture uses both the brightness temperature at C-band in horizontal polarization and the polarization index at X-band for correcting the effects of vegetation. This algorithm is based on a simplified radiative transfer (tau-omega) model, which has been inverted by using the Nelder-Mead iterative minimization method. The algorithm was validated with microwave data collected on two sites during the Microwave Alpine Soil Moisture Experiment 2002 (MASMEx02) and the Soil Moisture Experiment 2002 (SMEX02), respectively. The first site, in Italy, was characterized by natural vegetation covers, whereas the second site, in Iowa (U.S.), was covered primarily in agricultural crops. In general, the soil moisture estimated by the algorithm from AMSR-E data and the SMC measured on the ground were in good agreement with each other in both sites, and five classes of soil moisture were easily identified View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Physically Based Estimation of Bare-Surface Soil Moisture With the Passive Radiometers

    Page(s): 3145 - 3153
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (246 KB)  

    A physically based bare-surface soil moisture inversion technique for application with passive microwave satellite measurements, including the Advanced Microwave-Scanning Radiometer-Earth Observing System, Special Sensor Microwave/Imager, Scanning Multichannel Microwave Radiometer, and Tropical Rainfall Measuring Mission Microwave Imager, was developed in this paper. The inversion technique is based on the concept of a simple parameterized surface emission model, the Qp model, which was developed using advanced integral equation model simulations of microwave emission. Through evaluation of the relationship between roughness parameters Qp at different polarizations, it was found that they could be described by a linear function. Using this relationship and the surface emissivities measured from two polarizations, the effect of the surface roughness is cancelled out. In other words, this approach consisted in adding different weights on the v and h polarization measurements so as to minimize the surface roughness effects. This method leads to a dual-polarization inversion technique for the estimation of the surface dielectric properties directly from the emissivity measurements. For validation, we compared the soil moisture estimates, derived from ground radiometer measurements at C- to Ka-band obtained from the Institute National de Recherches Agronomiques' field experimental data in 1993 and the Beltsville Agricultural Research Center's field experimental data at C- and X-band obtained in 1979-1982, with the field in situ soil moisture measurements. The accuracies [root-mean-square error (rmse)] are higher than 4% for the available experimental data at the incidence angles of 50deg and 60deg. The newly developed inversion technique should be very useful in monitoring global soil moisture properties using the currently available satellite instruments that commonly have incidence angles between 50deg and 55deg View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Forest Structure Dependency of the Relation Between L-Band \sigma ^0 and Biophysical Parameters

    Page(s): 3154 - 3165
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (911 KB)  

    Biophysical parameters and L-band polarimetry synthetic aperture radar observation data were taken for 59 test sites in Tomakomai national forest, which is located in the northern part of Japan. Correlations between the derived sigmaHH 0, sigmaHV 0, and sigmaVV 0 and the biophysical parameters are investigated and yield the following results. 1) The above-ground biomass-sigma0 curves saturate above 50 tons/ha for sigmaVV 0, 100 tons/ha for sigmaHH 0, and over 100 tons/ha for sigmaHV 0 when all forest species are included in the curves. 2) The sigmaHH 0-above-ground biomass curve for one forest species indicates a higher saturation level than that for the other forest species. Dependence on the forest species was absent for VV polarization and low for HV polarization. 3) A simple three-component scattering model indicates that volume scattering accounts for 80%-90% when the above-ground biomass exceeds 50 tons/ha. The surface-scattering components are up to ~20% for young stands, and the volume-scattering components are down to 70%. The origin of the dependency among the forest species was examined for the sigmaHH 0-above-ground biomass. It is concluded that a possible cause of the dependency is the different characteristics of the stands rather than forest species View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Spectral Normalization and Fusion of Optical Sensors for the Retrieval of BRDF and Albedo: Application to VEGETATION, MODIS, and MERIS Data Sets

    Page(s): 3166 - 3179
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (973 KB)  

    This paper aims at demonstrating the possibility of merging data from various medium-resolution spaceborne sensors to produce a consistent time series of surface bidirectional reflectance distribution function (BRDF) and albedo products. The spectral, directional, temporal, and spatial aspects of the multisensor fusion are presented. Emphasis is then given on the spectral normalization for the fusion of Medium Resolution Imaging Spectrometer Instrument (MERIS) data with Moderate Resolution Imaging Spectroradiometer (MODIS) and VEGETATION (VGT) data. Two methods are evaluated: a simple statistical method, which relies on a linear regression using all the available spectral bands, and a more innovative method called the spectral mode method, which is based on the restitution of the surface spectral signature by a combination of universal spectral functions. Analysis with Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral data and satellite products reveals that the spectral mode method is more efficient. This approach is used to merge top-of-canopy bidirectional reflectances from MERIS and VGT for the restitution of BRDF and albedo over a subset of West Africa. Compared to the products obtained with MERIS alone, the fusion with VGT demonstrates an improvement of the spatial coverage and a reduction of product uncertainty by about a third View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Deep Blue Retrievals of Asian Aerosol Properties During ACE-Asia

    Page(s): 3180 - 3195
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1579 KB)  

    During the ACE-Asia field campaign, unprecedented amounts of aerosol property data in East Asia during springtime were collected from an array of aircraft, shipboard, and surface instruments. However, most of the observations were obtained in areas downwind of the source regions. In this paper, the newly developed satellite aerosol algorithm called "Deep Blue" was employed to characterize the properties of aerosols over source regions using radiance measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Based upon the Aringngstroumlm exponent derived from the Deep Blue algorithm, it was demonstrated that this new algorithm is able to distinguish dust plumes from fine-mode pollution particles even in complex aerosol environments such as the one over Beijing. Furthermore, these results were validated by comparing them with observations from AERONET sites in China and Mongolia during spring 2001. These comparisons show that the values of satellite-retrieved aerosol optical thickness from Deep Blue are generally within 20%-30% of those measured by sunphotometers. The analyses also indicate that the roles of mineral dust and anthropogenic particles are comparable in contributing to the overall aerosol distributions during spring in northern China, while fine-mode particles are dominant over southern China. The spring season in East Asia consists of one of the most complex environments in terms of frequent cloudiness and wide ranges of aerosol loadings and types. This paper will discuss how the factors contributing to this complexity influence the resulting aerosol monthly averages from various satellite sensors and, thus, the synergy among satellite aerosol products View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Cloud Masking for Ocean Color Data Processing in the Coastal Regions

    Page(s): 3196 - 3105
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (956 KB)  

    The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) use the near-infrared (NIR) reflectance threshold at 865 nm (869 nm for MODIS) to discriminate clear sky from clouds for processing of the ocean color products. Such a simple scheme generally works well over the open oceans where Case-1 waters and maritime aerosols are usually the case. However, in coastal regions, there are often cases with significant ocean contributions at the NIR wavelengths from the turbid waters. In addition, aerosols are likely to be dominated with small particles (large Aringngstrom exponent). In these cases, the cloud-masking scheme using the NIR reflectance threshold often mistakenly identifies these scenes as clouds, leading to significant loss of coverage in coastal regions. In this paper, we propose to use the MODIS short wave infrared (SWIR) bands at either 1240 or 1640 nm for detecting clouds. Ocean is black for turbid waters at SWIR wavelengths due to much stronger water absorption. The aerosol contribution in the SWIR bands is also significantly lower for nonabsorbing and weakly absorbing aerosols with small aerosol particle size. Thus, using the SWIR reflectance threshold, the performance of the cloud-masking algorithm in the coastal region is much better than that of using the NIR band. For sensors that do not have SWIR bands (e.g., SeaWiFS), we propose to use the Rayleigh-corrected (RC) reflectance ratio value from two NIR bands in addition to the reflectance threshold at 865 nm. The clouds are spectrally flat and have lower reflectance ratio values from two NIR measurements than cases with reflectance contributions from ocean and aerosols. It was found that, corresponding to the RC reflectance threshold of 2.7% at 869 nm, the RC threshold reflectances for 1240 and 1640 nm are 2.35% and 2.15%, respectively. The cloud-masking performance with the SWIR bands in the coastal region can usually be achieved using the RC reflect- - ance ratio value (ges 1.15 as clear atmosphere) between two NIR bands in addition to the reflectance threshold at 869 nm View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Processing of FORMOSAT-2 Daily Revisit Imagery for Site Surveillance

    Page(s): 3206 - 3214
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (853 KB)  

    The successful operation of FORMOSAT-2, which was launched on May 21, 2004, proved the concept that the temporal resolution of a remote sensing system can be much improved by deploying a high spatial resolution sensor in a daily revisit orbit, and each accessible scene can be systematically observed from the same angle under similar illumination conditions. These characteristics make FORMOSAT-2 an ideal satellite for site surveillance. The unique orbit and the arrangement of the charge-coupled device lines onboard FORMOSAT-2, however, also raise new challenges in image processing. This paper describes a fast and automatic system that is able to process a large amount of FORMOSAT-2 daily revisit imagery for the purpose of site surveillance. The system is comprised of several modules, including level-2 product generation, band-to-band coregistration, a spectral preserved pan-sharpening technique, and multitemporal imagery matching. Two examples processed by the system are given to demonstrate the applicability of FORMOSAT-2 daily revisit imagery for site surveillance. The experiences of operating FORMOSAT-2 for more than one and a half years are summarized, and the advantages and disadvantages of a daily revisit orbit are discussed. Experience obtained from this paper would benefit the system design and image processing of future satellite missions with similar specifications, such as the Pleacuteiades HR scheduled to be launched in 2008 View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Special issue on the DMSP special sensor microwave imager sounder (SSMIS)

    Page(s): 3215
    Save to Project icon | Request Permissions | PDF file iconPDF (168 KB)  
    Freely Available from IEEE
  • Special issue on the pattern recognition in remote sensing

    Page(s): 3216
    Save to Project icon | Request Permissions | PDF file iconPDF (159 KB)  
    Freely Available from IEEE

Aims & Scope

 

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.

 

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Antonio J. Plaza
University of Extremadura