By Topic

Geoscience and Remote Sensing, IEEE Transactions on

Issue 4  Part 2 • Date July 2000

Filter Results

Displaying Results 1 - 25 of 28
  • List of reviewers

    Page(s): 1765 - 1766
    Save to Project icon | Request Permissions | PDF file iconPDF (7 KB)  
    Freely Available from IEEE
  • On the assimilation of Ku-band scatterometer winds for weather analysis and forecasting

    Page(s): 1893 - 1902
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (292 KB)  

    Following the successful assimilation of European remote sensing satellite (ERS) scatterometer winds for weather analysis and forecasting, the authors further develop this methodology for the assimilation of the NASA scatterometer (NSCAT) and QuikSCAT Ku-band scatterometer data. Besides retrieval problems in cases of a confused sea state, the quality control (QC) developed identifies cases with rain on a wind vector cell (WVC) by WVC basis. The elimination of such geophysical conditions is a prerequisite to arrive at a successful assimilation of Ku-band scatterometer data. Moreover, the authors propose to assimilate ambiguous winds rather than radar backscatter measurements, as is being done at most meteorological centers assimilating ERS scatterometer data. After their quality assessment, NSCAT winds still have more difficult ambiguity removal properties than ERS winds. A further testing of the data assimilation method proposed is being carried out at the European Center for Medium-range Weather Forecasts in NSCAT impact experiments. A normalized wind inversion residual is used for QC. In order to determine a threshold for the rejection of poor quality wind solutions, the inversion residual and the wind vector departure from the ECMWF model are correlated. They end up rejecting around 7.4% of wind vector solutions and 4.2% of the NSCAT WVCs. In order to perform a qualitative assessment of this rejection, comparisons to collocated SSM/I rain and ECMWF winds are used. Confused sea state and presence of rain seem to be the most likely causes for the rejection of WVCs View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A practical method for simulating AVHRR-consistent NDVI data series using narrow MODIS channels in the 0.5-1.0 μm spectral range

    Page(s): 1969 - 1975
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (164 KB)  

    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 absorption channel View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Polarimetric scatterometry: a promising technique for improving ocean surface wind measurements from space

    Page(s): 1903 - 1921
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (484 KB)  

    Spaceborne wind scatterometers provide useful measurements of ocean surface winds and are important to climatological studies and operational weather forecasting. Past and currently planned scatterometers use measurements of the copolarized backscatter cross-section at different azimuth angles to infer ocean surface wind speed and direction. Although successful, current scatterometer designs have limitations such as degraded wind performance in the near-nadir and outer regions of the measurement swath and a reliance on external wind information for vector ambiguity removal. Theoretical studies of scattering from the wind-induced ocean surface indicate that polarimetric measurements provide orthogonal and complementary directional information to aid the wind retrieval process. In this paper, potential benefits of making polarimetric backscatter measurements to improve wind retrieval performance are addressed. To investigate the performance of a polarimetric scatterometer, a modified version of the SeaWinds end-to-end simulator at the Jet Propulsion Laboratory (JPL), Pasadena, CA, is employed. To model the effect of realistic measurement errors, expressions for polarimetric measurement variance and bias are derived. It is shown that a polarimetric scatterometer can be realized with straightforward and inexpensive modifications to a current scanning pencil-beam scatterometer system such as SeaWinds. Simulation results show that such a system ran improve wind performance in the nadir region and eliminate the reliance on external wind information View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Infrared tomographic system for monitoring the two-dimensional distribution of atmospheric pollution over limited areas

    Page(s): 1922 - 1935
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (620 KB)  

    The authors analyze the feasibility and performance of a particular tomographic system for atmospheric pollution monitoring over limited areas (e.g. urban areas). Such a system exploits attenuation-based infrared measurements of the average concentration of the fundamental molecular species of pollutants along rectilinear paths. First, the paper demonstrates the feasibility of an apparatus based on semiconductor infrared laser diode transmitters and passive retroreflectors, capable of measuring the average concentration of pollutants along rectilinear paths with 2 km maximum length, by exploiting their infrared absorption properties. For each gaseous species of interest, the optimal wavelength is then singled out, with the purpose of applying the derivative method for measuring the corresponding average atmospheric concentration. The optimal wavelengths are determined based on both absorption data of atmospheric components and plausible ranges of variation of their concentration. Finally, the authors present simulations carried out to evaluate the reconstruction of spatial concentration fields of several air pollutants, obtained through a tomographic inversion algorithm exploiting simultaneous attenuation measurements made along different infrared links. Two different network topologies for such measurements are considered View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Complexity in the atmosphere

    Page(s): 2056 - 2063
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (140 KB)  

    Two complexity measures, mutual information and statistical complexity, were applied to two types of atmospheric turbulence data sets. One data set is time series measurements of ocean surface winds. The other is a time-height, Doppler lidar image of vertical winds in the atmosphere. High values of complexity are seen where they might be expected: in the time series data in wind regimes where statistical models of turbulence perform poorly and in the time-height Doppler lidar images at the top of the boundary layer, where the atmosphere is undergoing a transition from an unstable to a stable flow regime. Finite-state machines known as “epsilon machines”, were constructed to model the information flow in the data. The results are a step toward establishing new, unbiased, modeling frameworks for atmospheric turbulence that will make optimal use of the computational resources being applied to sensing, data management, and numerical modeling of the atmosphere View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multisensor image fusion using influence factor modification and the ANOVA methods

    Page(s): 1976 - 1988
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (392 KB)  

    A new scheme is proposed for fusing multisensor images in which one image is regarded as the main image and the other the complementary; based on the evaluation of certain characteristics in the images. In effect, the scheme is used to fuse an image pair in which one image is superior to the other for interpretation in terms of higher resolution, better image quality, or having more recognizable features. Feature information is based on local statistical characteristics, which are extracted using the analysis of variance (ANOVA) method, in the framework of experimental designs. In effect, feature information from one image is used to influence the corresponding pixel values of the other image. The fused image leads to a better human and/or machine interpretation of the area of interest in the images View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Decomposition of laser altimeter waveforms

    Page(s): 1989 - 1996
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (152 KB)  

    The authors develop a method to decompose a laser altimeter return waveform into a series of components assuming that the position of each component within the waveform can be used to calculate the mean elevation of a specific reflecting surface within the laser footprint. For simplicity, they assume each component is Gaussian in nature. They estimate the number of Gaussian components from the number of inflection points of a smoothed copy of the laser waveform and obtain initial estimates of the Gaussian half-widths and positions from the positions of its consecutive inflection points. Initial amplitude estimates are obtained using a nonnegative least-squares method (LSM). To reduce the likelihood of fitting the background noise within the waveform and to minimize the number of Gaussians needed in the approximation, we rank the “importance” of each Gaussian in the decomposition using its initial half-width and amplitude estimates. The initial parameter estimates of all Gaussians ranked “important” are optimized using the Levenburg-Marquardt method. If the sum of the Gaussians does not approximate the return waveform to a prescribed accuracy, then additional Gaussians can be included in the optimization procedure or initial parameters can be recalculated. The Gaussian decomposition method is demonstrated on data collected by the airborne laser vegetation imaging sensor (LVIS) in October 1997 over the Sequoia National Forest, California View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Comparison of ERS wind-scatterometer and SSM/I data for Sahelian vegetation monitoring

    Page(s): 1794 - 1803
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (200 KB)  

    ERS wind scatterometer (WSC) and SSM/I data are compared for monitoring the seasonal variation of herbaceous vegetation over a sahelian region. Temporal evolution of polarization difference brightness temperatures derived from SSM/I data and WSC backscattering coefficient acquired at 45° of incidence angle over four different sites during the period 1992-1993, exhibits a marked seasonality with opposite and symmetrical trends. Observed differences between both signals are mainly attributed to atmospheric effects affecting SSM/I data. The use of a semi-empirical model during the 1992 rainy season shows that ΔT temporal evolution is mainly due to the variation of integrated water vapor content of the atmosphere, surface, and air temperature, soil moisture content, and bare soil fraction area. In order to retrieve biomass from SSM/I data, an inversion procedure is performed and compared to previous results obtained with ERS WSC data. The absence of accurate atmospheric data over the Sahel, combined with the sensitivity of the passive model to soil moisture leads to poor results with regard to biomass retrieval from SSM/I data View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Results of combining L- and C-band passive microwave airborne data over the Sahelian area

    Page(s): 1997 - 2008
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (388 KB)  

    This study focuses on an area in the Sahelian zone, Niger, Western Africa, where the HAPEX-Sahel experiment took place in 1992. During the hydrologic atmospheric pilot experiment in the Sahel (HAPEX-Sahel), passive microwave data were acquired with airborne radiometer, the multifrequency (5 to 90 GHz) and dual polarization sensor, PORTOS, and the four-beam sensor push broom microwave radiometer (PBMR), operating at 1.4 GHz in H-polarization. The aim of this investigation is to monitor soil moisture and vegetation parameters by combining L-band C-band passive microwave airborne measurements. Through the relationships between soil moisture measurements from the 2 cm and 0.5 cm top layers, soil moisture is estimated for PORTOS data using the estimated soil moisture along the transects covered by the PBMR flights. The simplified radiative transfer model is then used to extract the optical thickness and the single scattering albedo of vegetation at C-band, and to evaluate the vegetation effect on the estimated soil moisture at L-band. An attempt to relate the estimated optical thickness from PORTOS data to the measured vegetation biophysical parameters [water content, biomass, leaf area index (LAI)] is presented View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Prediction of sea level anomalies using ocean circulation model forced by scatterometer wind and validation using TOPEX/Poseidon data

    Page(s): 1871 - 1884
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (380 KB)  

    Uncertainties in the surface wind field have long been recognized as a major limitation in the interpretation of results obtained by oceanic circulation models. It is especially true in the tropical oceans, where the response to wind forcing is very strong on short time scales. The purpose of this paper is to show that these uncertainties can be greatly reduced by using spaceborne wind sensors that provide accurate measurements on a global basis. Surface winds over the global oceans have been measured by scatterometry since the launch of the European Remote Sensing Satellite (ERS-1) in August 1991 by the European Space Agency, Noordwijk, The Netherlands, and is currently provided by ERS-2, launched in April 1995. The ground-track wind vectors are processed to compute mean weekly surface winds onto a 1° square grid at the Institut Francais de Recherche pour l'Exploitation de la Mer (IFREMER), Plouzane, France. These winds are validated by comparison with the buoy array in the tropical Pacific ocean, showing good agreement. In order to further evaluate this wind field, the three-dimensional (3D) ocean model OPA7 developed at Laboratoire d'Oceanographie Dynamique et de Climatologie, Paris, France, is forced over the tropical oceans by the ERS-derived wind stress fields and by fields from the atmospheric model Arpege/Climat. Selected ocean parameters are defined in order to validate the ocean model results with measurements of the tropical ocean and global atmosphere (TOGA) buoys in the Pacific ocean. The ability of the model to describe the short scale (a few weeks to a few years) oceanic variability is greatly enhanced when the satellite-derived surface forcing is used. Further comparison of the ocean model results with the TOPEX-Poseidon altimeter measurements is presented View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Monitoring of seasonal thawing in Siberia with ERS scatterometer data

    Page(s): 1804 - 1809
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (352 KB)  

    Information on seasonal freeze-thaw cycle of soil and vegetation is of great interest for climate modeling and understanding the fluxes of heat, moisture and gases like carbon dioxide between the land surface and the atmosphere. Radar measurements have a great potential to provide this information, because at microwave frequencies, the dielectric properties vary considerably when going from the frozen to the thawed state. A technique was developed to retrieve the date of the transition from the frozen to thawed state based on measurements of the normalized radar cross section of the Earth's surface by the ERS scatterometers. This technique was applied to the data obtained over Siberia for the years 1992 to 1999. The date of thawing varies locally by one month, which is about 30% of the duration of the overall thawing process in Siberia. Also, the extent of the thawed area varies considerably by up to 3×106 km2 from year to year for a given date. The presented results demonstrate the great potential of C-band scatterometer data for monitoring the thawing of soil and vegetation and associated processes for climatological studies View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Seasonal to interannual variability in Antarctic sea-ice surface melt

    Page(s): 1827 - 1842
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (816 KB)  

    Satellite remote sensing time-series images are used to illustrate the spatial and temporal variability in Antarctic-wide sea-ice surface melting during the austral summer. Combinations of collocated data from the Active Microwave Instrument onboard the ERS-1/2 spacecraft, RadarSat synthetic aperture radar (SAR), and special sensor microwave/imager (SSM/I) passive microwave radiometer are used in characterizing the effects of surface melting on measured values of the normalized backscatter cross-section and brightness temperature, respectively. An algorithm is developed from observed signatures to map interannual variations in the summer season melt onset and the cumulative number of melt days throughout each austral summer from 1992 to 1998. Results indicate that antarctic sea-ice surface melting is sparse and relatively short-lived, in contrast to the protracted Arctic summer melt season. Regions consistently experiencing melt periods of 15 days or longer duration are focused around the Antarctic Peninsula, primarily in the northwest Weddell and Bellingshausen Seas View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Variability in ERS scatterometer measurements over land

    Page(s): 1767 - 1776
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (268 KB)  

    Using ERS scatterometer data effectively to relate large scale surface processes to driving parameters such as vegetation type, weather, soil, etc., requires the data be referenced to a regular geographic grid. The averaging involved may conceal systematic variation in σ0 in time, space, and across incidence angle. The problems in identifying the sources of variation at a given position are discussed and the relative magnitudes of the different variability components are evaluated. Variability indices can be defined at each gridpoint, of which the most useful appears to be the coefficient of variation after model-based correction for incidence angle effects. Images of variability indicate that for about 75% of the land surface, the mean σ0 images can be considered representative. However, some cover types exhibit continual, significant variability on short timescales, particularly grasslands and sandy deserts. Other cover types display seasonal variation, which appears to be related to vegetation, snow cover, and the freeze/thaw cycle. Variability measures also provide clear indications of occasional data problems even where no data quality flags are set View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Ocean surface wind retrievals using the TRMM microwave imager

    Page(s): 2009 - 2016
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (328 KB)  

    An analysis of one year of brightness temperature data from the TRMM microwave imager (TMI) is presented with regard to the retrieval of ocean surface wind speeds using standard regression techniques with in situ meteorological buoy measurements. Comparisons to similar satellite radiometer data from the special sensor microwave/imager (SSM/I) are also presented to help quantify atmospheric contributions to the surface wind retrievals. Particular emphasis is placed upon the use of the 10.7 GHz channels aboard the TMI in overcoming the contamination in the ocean surface brightness temperature measurements caused by precipitation and water vapor in the propagation path. The resulting wind retrieval improvements permit a relaxation in the rain flag definitions used to determine precipitation interference cutoff criteria, allowing accurate wind speed retrievals over a wider range of precipitation conditions. These improvements are realized through the construction of a new D-matrix wind speed retrieval algorithm suitable for the middle and low latitude coverage provided by the TRMM orbit View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Azimuth variation in microwave scatterometer and radiometer data over Antarctica

    Page(s): 1857 - 1870
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (348 KB)  

    While designed for ocean observation, scatterometer and radiometer data have proven very useful in a variety of cryosphere studies. Over large regions of Antarctica, ice sheet and bedrock topography and the snow deposition, drift, and erosional environment combine to produce roughness on various scales. Roughness ranges from broad, basin-scale ice-sheet topography at ~100 km wavelengths to large, spatially coherent dune fields at ~10 km wavelength to erosional features on the meter scale known as sastrugi. These roughness scales influence the microwave backscattering and emission properties of the surface, combining to introduce azimuth-angle dependencies in the satellite observation data. In this paper, the authors explore the use of NASA scatterometer (NSCAT) data, European remote sensing (ERS) advanced microwave instrument (AMI) scatterometer mode data, and special sensor microwave/imager (SSM/I) data to study surface roughness effects in Antarctica. All three sensors provide strong evidence of azimuth modulation, which is correlated with the surface slope environment and results in a katabatic wind flow regime. Due to its broad azimuth coverage, NSCAT data appears to be the best suited for azimuth-angle observations. A simple empirical model for the azimuth variation in the radar backscatter is developed, and an algorithm for computing the parameters of the model from NSCAT data at a fine scale is presented. Results indicate relationships exist between the azimuthal variation of the data and the orientation of the surface slope and small-scale roughness relative to the sensor-look direction View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Novel diffraction tomographic algorithm for imaging two-dimensional targets buried under a lossy Earth

    Page(s): 2033 - 2041
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (248 KB)  

    A novel diffraction tomographic algorithm has been proposed to detect two-dimensional (2D) dielectric cylinders buried under a lossy Earth. In this algorithm, the air-Earth interface has been taken into account and the exact treatment of Sommerfeld-like integrals has been considered. Using the algorithm, all locations, shapes, and dielectric properties of buried cylinders can be accurately reconstructed under the low-contrast condition. For high-contrast targets, this algorithm can also be used to determine their locations and approximate their dielectric properties. Due to the use of fast Fourier transforms to implement the problem, this algorithm is very fast and quite tolerant to the error of measurement data. Numerical examples are given to show the validity of the algorithm View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A theoretical performance analysis and simulation of time-domain EMI sensor data for land mine detection

    Page(s): 2042 - 2055
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (356 KB)  

    The physical phenomenology of electromagnetic induction (EMI) sensors' is reviewed for application to land mine detection and remediation. The response from time-domain EMI sensors is modeled as an exponential damping as a function of time, characterized by the initial magnitude and decay rate. Currently deployed EMI sensors that are used for the land mine detection process the recorded signal in a variety of ways in order to provide an audio output for the operator to judge whether or not the signal is from a mine. Sensors may sample the decay curve, sum it, or calculate its energy. Based on exponential decay model and the assumption that the sensor response is subject to additive white Gaussian noise, the performance of these, as well as optimal, detectors are derived and compared. Theoretical performance predictions derived using simplifying assumptions are shown to agree closely with simulated performance. It will also be shown that the generalized likelihood ratio test (GLRT) is equivalent to the likelihood ratio test (LRT) for multichannel time-domain EMI sensor data under the additive white Gaussian noise assumption and specific assumptions regarding the statistics of the decay rates of targets and clutter View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Digital surface models and building extraction: a comparison of IFSAR and LIDAR data

    Page(s): 1959 - 1968
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (272 KB)  

    The task of extracting significant built structure in digital surface models (DSM) is analyzed. The original data are obtained by means of interferometric SAR or LIDAR techniques and have different resolution and noise characteristics. This work aims to make a comparison of what (and how precisely) it is possible to detect and extract starting from these models, taking into account their differences but applying to them the same planar approximation approach. To this aim, data over Los Angeles and Denver is considered and evaluated. The results show that LIDAR data provide a better shape characterization of each building, and not simply because of their higher resolution. Indeed, less accurate results obtained starting from radar data are mainly due to shadowing/layover effects, which can be only partially corrected by means of the segmentation procedures. However, better results than those already presented in the literature could be achieved by using the IFSAR data correlation map View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A model-based determination of soil moisture trends in Spain with the ERS-scatterometer

    Page(s): 1783 - 1793
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (220 KB)  

    The ERS-1 Wind Scatterometer (WSC) has a resolution cell of about 50 km but provides a high repetition rate (<4 days) and makes measurements at multiple incidence angles. In this study, a mixed target modeling approach is applied to WSC data to estimate effective surface reflectivity (related to soil moisture content) at four test locations in Spain. The model represents the footprint area as a combination of part dense, homogeneous vegetation, and part bare soil (with homogeneous roughness and dielectric properties). The method is applied to WSC data over the period 1992-95, and results are compared to measurements of total monthly precipitation. The results illustrate the applicability of WSC data for measuring soil moisture content-related parameters and offers a physically-based alternative to empirical methods for monitoring trends in surface soil moisture content View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A data fusion algorithm for mapping sea-ice concentrations from Special Sensor Microwave/Imager data

    Page(s): 1947 - 1958
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (452 KB)  

    Ice charts from the U.S. National Ice Center, Washington, DC, are compared to published algorithms for generating sea-ice concentrations from SSM/I data. The same ice charts, in a form that includes information derived only from RADARSAT, OLS, and AVHRR data, are used in an operational algorithm that effectively tunes a hybrid of the Bootstrap and NASA Team algorithms and principal components of the SSM/I data to the time and region associated with the ice chart. This “tuned” algorithm is then used to interpolate ice concentrations elsewhere in the ice chart where no cloud-free, high resolution, visible, infrared or active microwave satellite data are available. The algorithm is designed to operate in near real time to assist the ice analysts in their otherwise manually-intensive task of compiling ice charts for vessels operating in ice-infested waters View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The impact of misregistration upon composited wide field of view satellite data and implications for change detection

    Page(s): 2017 - 2032
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (440 KB)  

    Composited wide field of view satellite data are used for many applications and increasingly for studies of global change. Although several compositing schemes have been suggested, all assume perfect geometric registration, which is not operationally feasible. In this study, models of the satellite imaging, geometric registration, and compositing processes are used to investigate the impact of misregistration upon the position of high contrast edges found in composited satellite data. Simulations are performed with respect to the compositing of advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) data. Contrast edges are found to be systematically shifted in maximum and minimum value composites. The degree of shifting increases with the number of orbits that are composited, the degree of misregistration and the view zenith angle. The implications of these findings upon the utility of composited satellite data for change detection are discussed. The shifts may systematically bias estimates of location and area when composited data are used. They may also cause small and/or fragmented features, which are evident in individual orbits to disappear in composited data, precluding the ability to map such features or to detect their occurrence under a change detection scheme View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Electromagnetic inversion in monostatic ground penetrating radar: TEM horn calibration and application

    Page(s): 1936 - 1946
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (288 KB)  

    A comprehensive analysis of electromagnetic (EM) inversion applied to pavement profiling by using a monostatic ground penetrating radar (GPR) is presented. Since in GPR systems using transfers EM (TEM) horns, the antenna is positioned close to the the investigated medium and a strong EM interaction occurs. This effect is taken into account by modeling the antenna with equivalent sources placed on the aperture section and by using an accurate EM modeling within the inversion loop in order to account for the contribution of near-field effects. Experimental results on the antenna modeling procedure and on a pavement profile estimation validate the feasibility of both the calibration and the inverse problem proposed View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An iterative approach to multisensor sea ice classification

    Page(s): 1843 - 1856
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (448 KB)  

    Characterizing the variability in sea ice in the polar regions is fundamental to an understanding of global climate and the geophysical processes governing climate changes. Sea ice can be grouped into a number of general classes with different characteristics. Multisensor data from NSCAT, ERS-2, and SSM/I are reconstructed into enhanced resolution imagery for use in ice-type classification. The resulting twelve-dimensional data set is linearly transformed through principal component analysis to reduce data dimensionality and noise levels. An iterative statistical data segmentation algorithm is developed using maximum likelihood (ML) and maximum a posteriori (MAP) techniques. For a given ice type, the conditional probability distributions of observed vectors are assumed to be Gaussian. The cluster centroids, covariance matrices, and a priori distributions are estimated from the classification of a previous temporal image set. An initial classification is produced using centroid training data and a weighted nearest-neighbor classifier. Though validation is limited, the algorithm results in an ice classification that is judged to be superior to a conventional k-means approach View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Monitoring of seasonal snowmelt on Greenland with ERS scatterometer data

    Page(s): 1821 - 1826
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (244 KB)  

    In Greenland, summer melting of snow is common in large areas, and its extent and intensity are expected to respond immediately to climate change. Volume scattering is the dominating backscattering mechanism for snow with volumetric moisture of less than 3%. Free liquid water in the snow causes high dielectric loss, which increases the absorption coefficient. Therefore, the normalized radar cross section of snow decreases with increasing snow wetness when the snow starts melting. The radar cross section measurements over Greenland by the C-band scatterometers aboard the first and second European Remote Sensing Satellite (ERS-1 and ERS-2) were used to detect and monitor snow melt for the period of August 1991 to December 1999. The produced maps of snowmelt show considerable interannual variations in terms of melt extent and intensity. Although climatological trends cannot be delineated from the short time series, the presented technique is well suited for this task. In the future, this type of radar measurement will be continued by the meteorological METOP satellite series. This will offer a unique possibility for climatological studies View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

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