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Geoscience and Remote Sensing, IEEE Transactions on

Issue 8  Part 1 • Date Aug. 2009

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Displaying Results 1 - 25 of 32
  • [Front cover]

    Publication Year: 2009 , Page(s): C1
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  • IEEE Transactions on Geoscience and Remote Sensing publication information

    Publication Year: 2009 , Page(s): C2
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  • Table of contents

    Publication Year: 2009 , Page(s): 2405 - 2406
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  • Two-Shell Ionospheric Model for Indian Region: A Novel Approach

    Publication Year: 2009 , Page(s): 2407 - 2412
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (308 KB) |  | HTML iconHTML  

    In the U.S. Wide Area Augmentation System, European Geostationary Navigation Overlay Service, and Indian Global Positioning System Aided Geo Augmented Navigation, a near real-time grid-based single-shell model is proposed to correct the ionospheric delay at the user aircrafts. The single-shell model is based on the assumption that the whole ionosphere is compressed at a fixed altitude at 350 km. This assumption may not be appropriate for the Indian region, which falls in the Equatorial Ionospheric Anomaly belt. In this paper, a two-shell model which incorporates two different shells, at 300- and 500-km altitudes, having different weights at different time domains has been implemented. A statistical comparison between single- and two-shell models has been done for all quiet days of year 2005. Based on the results, it is observed that there is at least 60% improvement in the performance of the two-shell model in comparison to the single-shell model for the Indian region. View full abstract»

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  • Retrieval of Cloud Optical Properties From Multiple Infrared Hyperspectral Measurements: A Methodology Based on a Line-by-Line Multiple-Scattering Code

    Publication Year: 2009 , Page(s): 2413 - 2426
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1145 KB) |  | HTML iconHTML  

    A methodology to retrieve cloud optical properties using high spectral resolution (HSR) infrared (IR) measurements is presented. This new method has the ability to easily adapt to multiple instruments and viewing angles. The retrieval uses a line-by-line multiple-scattering simulation and HSR IR measurements to retrieve spectrally resolved cloud optical depths (ODs). The spectral ODs are compared to a precomputed OD database generated from an ensemble of cloud particle-size distributions and precomputed single-scattering and single-particle optical properties for a variety of ice-crystal habits. Cloud microphysics are retrieved by finding the closest fit to the database. Results are independent of first-guess optical property assumptions on size and habit. The retrieval method has been applied to aircraft, satellite, and uplooking HSR measurements with results evaluated against coincident HSR lidar and radar measurements. Analysis of retrieval errors produced by assumptions and uncertainties in the atmospheric state demonstrates different sensitivities to atmospheric parameters when uplooking or downlooking data are analyzed. For both viewing geometries, the retrieval is most sensitive to the uncertainties in the assumed cloud boundaries. It is also found that nonuniform vertical distribution of cloud OD can result in significant biases in the IR retrieved cloud ODs. View full abstract»

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  • Estimation of Three-Dimensional Atmospheric Wave Parameters From Ground-Based Spectroscopic Airglow Image Data

    Publication Year: 2009 , Page(s): 2427 - 2435
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (490 KB) |  | HTML iconHTML  

    This paper describes the methodology to estimate the intrinsic parameters of atmospheric gravity waves from multiple ground-based observations of a single mesospheric airglow emission. In this configuration, several spectroscopic imagers are placed on the ground to achieve multiple perspectives of the emission as it is perturbed by gravity waves. The classical way to analyze this data is to use a tomographic approach to estimate the wave parameters. In this paper, a strategy is developed to estimate the wave parameters directly from the data without using tomography. This approach is then demonstrated with a simulation. View full abstract»

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  • Conditioning Stochastic Rainfall Replicates on Remote Sensing Data

    Publication Year: 2009 , Page(s): 2436 - 2449
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1364 KB) |  | HTML iconHTML  

    Temporally and spatially variable rainfall replicates are frequently required in hydrologic applications of ensemble forecasting and data assimilation. Ensemble methods can be expected to work better when the rainfall replicates more closely resemble observed storms. In particular, the replicates should capture the intermittency and variability that are dominant features of rainfall events. In this paper, we present a new probabilistic procedure for generating realistic rainfall replicates that are constrained by (or conditioned on) remote sensing measurements. The procedure uses remotely sensed cloud top temperatures to identify potentially rainy regions. The cloud top temperatures are obtained from visible/infrared instruments in geostationary orbit. A multipoint geostatistical algorithm generates areas of nonzero rain (rain clusters) within each cloudy region. This algorithm relies on statistics derived from ground-based weather radar [National Operational Weather Radar (NOWRAD)] data. A truncated multiplicative cascade generates rain rates within each rain cluster. A computational experiment based on summer 2004 data from the Central U.S. indicates that the rainfall replicates simulated by the procedure are visually and statistically similar to individual NOWRAD images and to a large ensemble of NOWRAD images collected throughout the summer simulation period. View full abstract»

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  • Atmospheric Correction at AERONET Locations: A New Science and Validation Data Set

    Publication Year: 2009 , Page(s): 2450 - 2466
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1624 KB) |  | HTML iconHTML  

    This paper describes an Aerosol Robotic Network (AERONET)-based Surface Reflectance Validation Network (ASRVN) and its data set of spectral surface bidirectional reflectance and albedo based on Moderate Resolution Imaging Spectroradiometer (MODIS) TERRA and AQUA data. The ASRVN is an operational data collection and processing system. It receives 50 times 50 km2 subsets of MODIS level 1B (L1B) data from MODIS adaptive processing system and AERONET aerosol and water-vapor information. Then, it performs an atmospheric correction (AC) for about 100 AERONET sites based on accurate radiative-transfer theory with complex quality control of the input data. The ASRVN processing software consists of an L1B data gridding algorithm, a new cloud-mask (CM) algorithm based on a time-series analysis, and an AC algorithm using ancillary AERONET aerosol and water-vapor data. The AC is achieved by fitting the MODIS top-of-atmosphere measurements, accumulated for a 16-day interval, with theoretical reflectance parameterized in terms of the coefficients of the Li Sparse-Ross Thick (LSRT) model of the bidirectional reflectance factor (BRF). The ASRVN takes several steps to ensure high quality of results: 1) the filtering of opaque clouds by a CM algorithm; 2) the development of an aerosol filter to filter residual semitransparent and subpixel clouds, as well as cases with high inhomogeneity of aerosols in the processing area; 3) imposing the requirement of the consistency of the new solution with previously retrieved BRF and albedo; 4) rapid adjustment of the 16-day retrieval to the surface changes using the last day of measurements; and 5) development of a seasonal backup spectral BRF database to increase data coverage. The ASRVN provides a gapless or near-gapless coverage for the processing area. The gaps, caused by clouds, are filled most naturally with the latest solution for a given pixel. The ASRVN products include three parameters of the LSRT model (kL, kG, and kV), surface albedo, normalized BRF (computed for a standard viewing geometry, VZA = 0deg, SZA = 45deg), and instantaneous BRF (or one-angle BRF value derived from the last day of MODIS measurement for specific viewing geometry) for the MODIS 500-m bands 1-7. The results are produced daily at a resolution of 1 km in gridded format. We also provide a cloud mask, a quality flag, and a browse bitmap image. The ASRVN data set, including 6 years of MODIS TERRA and 1.5 years of MODIS AQUA data, is available now as a standard MODIS product (MODASRVN) which can be accessed through the Level 1 and Atmosphere Archive and Distribution System website ((http://ladsweb.nascom.nasa.gov/data/search.html).). It can be used for a wide range of applications including validation analysis and science research. View full abstract»

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  • Sea Surface Manifestation of Along-Tidal-Channel Underwater Ridges Imaged by SAR

    Publication Year: 2009 , Page(s): 2467 - 2477
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2021 KB) |  | HTML iconHTML  

    A group of submerged ocean bottom sand ridges in the Bohai Sea, China, are shown in RADARSAT-1 and ENVISAT synthetic aperture radar (SAR) images. The sand ridges appear as fingerlike quasi-linear features in the SAR images. Examining the detailed local bathymetry chart, we find that these features coincide with the satellite images. The heights of the sand ridges are less than 10 m, and the water depth is between 10 and 30 m. The spacing of the sand ridges is about 10 km, and the length of the sand ridges is about 20 km. The same sand ridges are also visible on a Moderate Resolution Imaging Spectroradiometer (MODIS) true-color image. The semidiurnal and diurnal tidal currents in this area are almost parallel to the major axis of these sand ridges. These observations cannot be explained using the existing 1-D SAR imaging model, which is not applicable to sand ridges parallel to the tidal current. In this paper, we consider the shallow-water current bathymetry in a 2-D space. An analytical ocean model was applied to demonstrate the temporal variations of the current divergence and convergence that are induced by the along-sand-ridge-direction current and ridge interaction. A radar simulation model is used to simulate the variation of normalized radar cross section (NRCS) induced by the ocean surface current. The simulated NRCS variation is similar to that extracted from the calibrated SAR image. Simulation results also show that the NRCS variation becomes negligible when the ocean current is set to about half of the maximum tidal current. View full abstract»

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  • Study on the Automatic Recognition of Oceanic Eddies in Satellite Images by Ellipse Center Detection—The Iberian Coast Case

    Publication Year: 2009 , Page(s): 2478 - 2491
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (996 KB) |  | HTML iconHTML  

    Ellipse detection has been presented several times in scientific literature as a potential method for finding eddies in satellite images because eddies may be roughly approximated by ellipses. In this paper, therefore, we describe a new eddy detector based on ellipse detection. The detector is capable of finding several eddies per satellite image, an ability not demonstrated for previously reported eddy detectors based on ellipse detection in the morphology of binary images. One important characteristic of this paper is the determination of the method's classification efficiency using a considerable number of eddies; such a determination has been rarely performed in the scientific literature on eddy detection. The developed detector finds ellipse centers using geometrical properties of ellipses. To the best of the author's knowledge, the proposed method has never been applied to eddy detection. The low value of the maximum temperature gradient of the eddies off the Iberian Peninsula (0.52degC/pixel) complicates the application of the detection method because it raises difficulties in outlining the eddies and induces large amounts of noise in the binary images from which the eddies are detected. The values of each parameter in the developed system were equal for the images analyzed, which suggests that the application of the proposed system to large numbers of images is simple. The author did not find any method applicable to the present case in the scientific literature whose classification efficiencies, assessed on complete images or a considerable number of eddies, were better than those reported here. View full abstract»

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  • Validation of a Quasi-Analytical Algorithm for Highly Turbid Eutrophic Water of Meiliang Bay in Taihu Lake, China

    Publication Year: 2009 , Page(s): 2492 - 2500
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (502 KB) |  | HTML iconHTML  

    In many hydrological studies and applications, it is desirable to know the absorption property of water bodies. In order to derive this inherent optical property of waters from remote sensing reflectance, a multiband quasi-analytical algorithm (QAA) was calibrated and validated for the highly turbid water of Taihu Lake in China. A data set collected on November 8, 2007, from Meiliang Bay of Lake Taihu was first used to calibrate a regional QAA algorithm for this area, and other two independent data sets, which were collected on August 22, 2006, and November 10, 2008, from the same area, were used to further validate the local algorithm. By shifting the reflectance wavelength from the red region to near infrared, the local QAA algorithm works well for this highly turbid water, the percent difference between the derived and measured absorption coefficients is less than 20% for all 13 samples in the data set of 2007, and most of them are less than 10%. The regional calibrated algorithm also has great result in deriving the absorption for the data set of 2008. However, the performance of the local algorithm also has various seasonal properties. It failed in deriving absorption for the data set of August 2006, unless the reference wavelength is shifted to even more long ones. It has been suggested in this paper that the seasonal and regional information is necessary for using the QAA algorithm in different optical property waters. View full abstract»

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  • A Spatially Adjusted Elevation Model in Dronning Maud Land, Antarctica, Based on Differential SAR Interferometry

    Publication Year: 2009 , Page(s): 2501 - 2509
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (904 KB) |  | HTML iconHTML  

    In this paper, a new digital elevation model (DEM) is derived for the ice sheet in western Dronning Maud Land, Antarctica. It is based on differential interferometric synthetic aperture radar (SAR) from the European Remote Sensing 1/2 (ERS-1/2) satellites, in combination with ICESat's Geoscience Laser Altimeter System (GLAS). A DEM mosaic is compiled out of 116 scenes from the ERS-1 ice phase in 1994 and the ERS-1/2 tandem mission between 1996 and 1997 with the GLAS data acquired in 2003 that served as ground control. Using three different SAR processors, uncertainties in phase stability and baseline model, resulting in height errors of up to 20 m, are exemplified. Atmospheric influences at the same order of magnitude are demonstrated, and corresponding scenes are excluded. For validation of the DEM mosaic, covering an area of about 130 000 km2 on a 50-m grid, independent ICESat heights (2004-2007), ground-based kinematic GPS (2005), and airborne laser scanner data (ALS, 2007) are used. Excluding small areas with low phase coherence, the DEM differs in mean and standard deviation by 0.5 + / - 10.1, 1.1 + / - 6.4, and 3.1 +/ - 4.0 m from ICESat, GPS, and ALS, respectively. The excluded data points may deviate by more than 50 m. In order to suppress the spatially variable noise below a 5-m threshold, 18% of the DEM area is selectively averaged to a final product at varying horizontal spatial resolution. Apart from mountainous areas, the new DEM outperforms other currently available DEMs and may serve as a benchmark for future elevation models such as from the TanDEM-X mission to spatially monitor ice sheet elevation. View full abstract»

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  • Detection of Ice and Mixed Ice–Water Pixels for MODIS Ocean Color Data Processing

    Publication Year: 2009 , Page(s): 2510 - 2518
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1679 KB) |  | HTML iconHTML  

    Current data processing for deriving ocean color products from the Moderate Resolution Imaging Spectroradiometer (MODIS) has no specific ice and mixed ice-water pixel detection procedure. The near-infrared (NIR) reflectance threshold at the MODIS 869-nm band, which has been used to discriminate clear sky from clouds (cloud masking) for standard ocean color data processing, can eliminate most of the ice pixels. However, there are still many cases for which the ice and mixed ice-water pixels have been misidentified as ocean waters in current ocean color data processing, leading to errors in the MODIS-derived ocean color product (e.g., chlorophyll-a concentration). This is particularly true for most of the mixed ice-water cases. For atmospheric correction using the short-wave infrared (SWIR) method, which also uses SWIR reflectance for cloud masking, the problem of ice misidentification is even worse. In this paper, we describe a method for detection of ice and mixed ice-water pixels for MODIS ocean color data processing. Using the MODIS-derived normalized water-leaving radiances at 412, 555, and 859 nm, a scheme for ice and mixed ice-water detection has been developed and tested for producing MODIS global ocean color products. In fact, the proposed algorithm is a by-product calculated from the MODIS-derived normalized water-leaving radiance spectra data. Thus, the MODIS-derived ice surface radiance data can be used to study sea ice physical and optical properties. With the new ice detection scheme, pixels with ice and/or mixed ice-water can be discriminated, flagged, or masked out. The ice detection results are compared with the MODIS ice map product produced from the MODIS land discipline team, as well as the ice product data obtained from the NOAA National Ice Center. We show improved results from the new masking algorithm for the purpose of MODIS ocean color data processing, particularly for detection of mixed ice-water pixels. View full abstract»

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  • A Time-Series Approach to Estimate Soil Moisture Using Polarimetric Radar Data

    Publication Year: 2009 , Page(s): 2519 - 2527
    Cited by:  Papers (28)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (254 KB) |  | HTML iconHTML  

    Electromagnetic scattering from a rough surface is a function of both surface roughness and dielectric constant of the scattering surface. Therefore, in order to estimate soil moisture of a bare surface accurately from radar measurements, the effects of surface roughness must be compensated for properly. Several algorithms have been developed to estimate soil moisture from a polarimetric radar image, all with limited ranges of applicability. No theoretical algorithm has been reported to retrieve volumetric soil moisture of a vegetated surface. In this paper, we examine a different approach to estimate soil moisture that exploits the fact that the backscattering cross section from a natural object changes over short timescales mainly due to variations in soil moisture. We develop a model function that expresses copolarized backscattering cross sections (sigmahh and sigmavv) in terms of volumetric soil moisture using L-band experimental data for both bare and vegetated surfaces. In order to estimate soil moisture, two unknowns in the model function must be determined. We propose a viable approach to determine these two unknowns using combined radiometer and radar data. This time-series approach also provides a framework to utilize a priori knowledge on soil moisture to improve the retrieval accuracy of volumetric soil moisture. We demonstrate that this time-series algorithm is a simple and robust way to estimate soil moisture for both bare and vegetated surfaces. View full abstract»

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  • Large-Area Soil Moisture Estimation Using Multi-Incidence-Angle RADARSAT-1 SAR Data

    Publication Year: 2009 , Page(s): 2528 - 2535
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (390 KB) |  | HTML iconHTML  

    The sensitivity of synthetic aperture radar (SAR) backscatter to soil moisture has been adequately established. However, monitoring of soil moisture over large agricultural areas is still difficult because SAR backscatter is also sensitive to other target properties like surface roughness, crop cover, and soil texture (soil type), along with its strong sensitivity to soil moisture. Hence, to develop a methodology for large-area soil moisture estimation using SAR, it is necessary to incorporate the effects of surface roughness, crop cover, and soil texture in the soil moisture retrieval model. In this paper, a methodology for soil moisture estimation over a large area is developed using a pair of low- and high-incidence-angle RADARSAT-1 SAR data over parts of Agra, Mathura, and Bharatpur districts, India, during March 1999. The methodology requires acquisition of synthetic aperture radar data at low and high incidence angles, such that the soil moisture changes are negligible between the two acquisitions. In order to demonstrate the applicability of the developed methodology, the same was validated over a different area (parts of Saharanpur and Haridwar districts, India) during March 2005. Both test sites provided the variety of agricultural heterogeneity required for development and validation of the methodology for large-area soil moisture estimation. The proposed methodology offers an approach to incorporate the effects of surface roughness, crop cover, and soil texture in the soil moisture retrieval model from the space platform, without making any assumptions on the distributions of these parameters or without knowing the actual values of these parameters on ground. View full abstract»

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  • A Temporally Integrated Inversion Method for Estimating Leaf Area Index From MODIS Data

    Publication Year: 2009 , Page(s): 2536 - 2545
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1088 KB) |  | HTML iconHTML  

    Multiple leaf area index (LAI) products have been generated from remote-sensing data. Among them, the Moderate-Resolution Imaging Spectroradiometer (MODIS) LAI product (MOD15A2) is now routinely derived from data acquired by MODIS sensors onboard Terra and Aqua satellite platforms. However, the MODIS LAI product is not spatially and temporally continuous and is inaccurate in many areas for some vegetation types. In this paper, a new algorithm is developed to estimate LAI from time-series MODIS reflectance data (MOD09A1). A radiative-transfer model is coupled with a double-logistic LAI temporal-profile model, and the shuffled complex evolution optimization method, developed at the University of Arizona, is used to estimate the parameters of the coupled model from the temporal signature in a given time window. Preliminary analysis using MODIS surface-reflectance data at flux sites was performed to validate this method. The results show that the new algorithm is able to construct a temporally continuous LAI product efficiently, and the accuracy has been significantly improved over the MODIS LAI product as compared to field-measured LAI data. View full abstract»

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  • BRDF Analysis of Savanna Vegetation and Salt-Pan Samples

    Publication Year: 2009 , Page(s): 2546 - 2556
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2694 KB) |  | HTML iconHTML  

    In this paper, laboratory-based bidirectional reflectance distribution function (BRDF) analysis of vegetation leaves, soil, and leaf-litter samples is presented. The leaf litter and soil samples, numbered 1 and 2, were obtained from a site located in the savanna biome of South Africa (Skukuza: 25.0deg S, 31.5deg E). A third soil sample, number 3, was obtained from Etosha Pan, Namibia (19.20deg S, 15.93deg E, altitude of 1100 m). In addition, BRDF of local fresh and dry leaves from tulip polar tree (Liriodendron tulipifera) and black locust tree (Robinia pseudoacacia) were studied. It is shown how the BRDF depends on the incident and scatter angles, sample size (i.e., crushed versus whole leaf), soil samples fraction size, sample status (i.e., fresh versus dry leaves), vegetation species (i.e., poplar versus locust), and the vegetation's biochemical composition. As a demonstration of the application of the results of this paper, airborne BRDF measurements acquired with NASA's Cloud Absorption Radiometer over the same general site where the soil and leaf-litter samples were obtained are compared to the laboratory results. Good agreement between laboratory and airborne-measured BRDF is reported. View full abstract»

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  • Impact of Hillslope-Scale Organization of Topography, Soil Moisture, Soil Temperature, and Vegetation on Modeling Surface Microwave Radiation Emission

    Publication Year: 2009 , Page(s): 2557 - 2571
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1472 KB) |  | HTML iconHTML  

    Microwave radiometry will emerge as an important tool for global remote sensing of near-surface soil moisture in the coming decade. In this modeling study, we find that hillslope-scale topography (tens of meters) influences microwave brightness temperatures in a way that produces bias at coarser scales (kilometers). The physics underlying soil moisture remote sensing suggests that the effects of topography on brightness temperature observations are twofold: 1) the spatial distribution of vegetation, moisture, and surface and canopy temperature depends on topography and 2) topography determines the incidence angle and polarization rotation that the observing sensor makes with the local land surface. Here, we incorporate the important correlations between factors that affect emission (e.g., moisture, temperature, and vegetation) and topographic slope and aspect. Inputs to the radiative transfer model are obtained at hillslope scales from a mass-, energy-, and carbon-balance-resolving ecohydrology model. Local incidence and polarization rotation angles are explicitly computed, with knowledge of the local terrain slope and aspect as well as the sky position of the sensor. We investigate both the spatial organization of hillslope-scale brightness temperatures and the sensitivity of spatially aggregated brightness temperatures to satellite sky position. For one computational domain considered, hillslope-scale brightness temperatures vary from approximately 121 to 317 K in the horizontal polarization and from approximately 117 to 320 K in the vertical polarization. Including hillslope-scale heterogeneity in factors effecting emission can change watershed-aggregated brightness temperature by more than 2 K, depending on topographic ruggedness. These findings have implications for soil moisture data assimilation and disaggregation of brightness temperature observations to hillslope scales. View full abstract»

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  • Monitoring Sugarcane Growth Using ENVISAT ASAR Data

    Publication Year: 2009 , Page(s): 2572 - 2580
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (426 KB) |  | HTML iconHTML  

    The objective of this paper is to investigate potential of satellite C-band synthetic aperture radar (SAR) radar in monitoring sugarcane growth in southern China. This paper proposes a method to map sugarcane growing area and retrieve sugarcane leaf area index (LAI) in different growth stages using ENVISAT Advanced SAR (ASAR) alternating polarization HH/HV data. The temporal response of ASAR alternating polarization HH/HV data to sugarcane fields and sugarcane LAI was first analyzed in the study area. The analysis shows that sugarcane fields have increasing temporal radar response trend with sugarcane growth and ratio of ASAR HV to HH data has a better correlation with the increase of sugarcane LAI. A theoretical radiative transfer model was adopted to interpret the trend. Based on the temporal variation of the radar response of sugarcane fields, a method for mapping sugarcane planting area was developed using ASAR HH and HV polarization data at two acquisition dates with a certain classification accuracy. The empirical models were also established to estimate LAI of sugarcane using the HV/HH polarization ratio. The results suggest that C-band ASAR data appear promising in the development of an operational system for monitoring sugarcane growth in southern China. View full abstract»

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  • Study of Hypersaline Deposits and Analysis of Their Signature in Airborne and Spaceborne SAR Data: Example of Death Valley, California

    Publication Year: 2009 , Page(s): 2581 - 2598
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2196 KB) |  | HTML iconHTML  

    Field measurements of dielectric properties of hypersaline deposits were realized over an arid site located in Death Valley, CA. The dielectric constant of salt and water mixtures is usually high but can show large variations, depending on the considered salt. We confirmed values observed on the field with laboratory measurements and used these results to model both the amplitude and phase behaviors of the synthetic aperture radar (SAR) signal at C- and L-bands. Our analytical simulations allow reproducing specific copolar signatures observed in both Airborne SAR (AIRSAR) and Spaceborne Imaging Radar (SIR-C) data, corresponding to the saltpan of the Cottonball Basin. More precisely, the main objective of the present paper is to understand the influence of soil salinity as a function of soil moisture on the dielectric constant of soils and then on the backscattering coefficients recorded by airborne and spaceborne SAR systems. We also propose the copolarized backscattering ratio and phase difference as indicators of moistened and salt-affected soils. More precisely, we show that these copolar indicators should allow monitoring of the seasonal variations of the dielectric properties of saline deposits at both C- and L-bands. Because of the frequency dependence of the ionic conductivity, we also show that L-band SAR systems should be efficient tools for detecting both soil moisture and salinity, while C-band SAR systems are more suitable for the monitoring of soil moisture only. Through the study of terrestrial evaporitic environments by means of spaceborne SAR systems, our results could also be of great interest for defining future planetary missions, particularly for the exploration of Mars. View full abstract»

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  • Injection Heights of Biomass Burning Debris Estimated From WSR-88D Radar Observations

    Publication Year: 2009 , Page(s): 2599 - 2605
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (892 KB) |  | HTML iconHTML  

    Understanding the vertical distribution of aerosols is critical to accurately determining their effects on air quality. Since current tools for obtaining this information have limited spatial and temporal coverage, we explore the use of Doppler radar data for obtaining the injection heights of biomass burning debris (BBD) produced from large fires in southern Georgia during Spring 2007. Due to their submicrometer sizes, the smoke aerosols are not detected by the radar. Therefore, we use BBD as a possible surrogate for aerosol height since smoke aerosols are often collocated with the debris. Using 32 h of Weather Surveillance Radar-1988 Doppler (WSR-88D) radar data from Jacksonville, FL, between May 23 and 25, 2007, the injection heights of BBD (D ~ 1mm) are calculated. Our analysis indicates that the maximum injection height is ~5 km for the strongest fire, with a mean injection height of 3 plusmn 1.0 km. Maximum injection heights are present between 1800 and 0000 UTC, during the late afternoon periods when both the intensity of the fire (based on radar information) and the convective mixing are greatest. The injection heights estimated from this approach represent the first step at providing inputs for future air-quality forecasting applications within numerical simulations, particularly ones that require diurnal information. View full abstract»

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  • Assimilation of an L-Band Microwave Soil Moisture Proxy to Compensate for Uncertainties in Precipitation Data

    Publication Year: 2009 , Page(s): 2606 - 2616
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1014 KB) |  | HTML iconHTML  

    The accuracy of hydrological model simulations is dependent on the reliability of model input data like, for example, meteorological information or land cover and soil information. Uncertainties of simulations of soil water fluxes are hereby directly related to the accuracy of available precipitation data. As precipitation is characterized by small temporal and spatial correlation lengths, the uncertainties in precipitation data increase with decreasing density of available precipitation gauges. As soil moisture directly depends on precipitation dynamics, its variation can be used as a proxy for precipitation variability. Remote sensing techniques allow for monitoring of surface soil moisture dynamics at different spatiotemporal scales. In particular, low-frequency microwave data are most sensitive to soil moisture dynamics. This paper investigates the potential of integrating L-band (1-2 GHz) microwave radiometer data into a simple model for soil wetness to compensate for uncertainties in a priori information of precipitation. The study is based on a short-term ground-based L-band radiometer data set over grassland. A high correlation between the microwave signature and surface soil moisture was found, which is consistent with previous findings. An analytical data assimilation scheme for the integration of that information into a soil wetness model, based on an antecedent precipitation index (API), was established. The results revealed that the data assimilation filter adds or removes an amount of water partially compensating for the actual precipitation error. The correlation coefficient between the filter update and the actual precipitation error was found to be 0.6 les r les 0.8, and the model simulations did show a better coincidence with in situ soil moisture records when integrating the microwave data. The results indicate high potential for use of L-band microwave data to compensate for uncertainties in precipitation data. View full abstract»

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  • Nonlinear Regression Models to Identify Functional Forms of Deforestation in East Asia

    Publication Year: 2009 , Page(s): 2617 - 2626
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1166 KB) |  | HTML iconHTML  

    Identification of the factors involved in deforestation could lead to a comprehensive understanding of deforestation on a broad scale, as well as prediction capability. In this paper, regression models with two explanatory variables-human population and relief energy, i.e., the difference between the maximum and minimum altitudes in a sampled area-were verified as to whether they could elucidate aspects of deforestation. The functional forms of the nonlinear regression models were estimated by step functions analyzed with the use of high-precision Japanese data. Candidate smooth regression models were then derived from the obtained sigmoidal shapes by the step functions. Models with spatially dependent errors were also developed. Akaike's information criterion was used to evaluate the models on four data sets for the East Asia region. From the evaluation, we selected the best three models that systematically showed the best relative appropriateness to the real data. View full abstract»

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  • Modeling the Response of Electromagnetic Induction Sensors to Inhomogeneous Magnetic Soils With Arbitrary Relief

    Publication Year: 2009 , Page(s): 2627 - 2638
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (416 KB) |  | HTML iconHTML  

    A general model to compute the response of an electromagnetic induction sensor to a magnetic soil, in both time and frequency domains, is developed. The model requires modest computational resources and can be applied to arbitrary soil inhomogeneities and relief, and to arbitrary sensor coil shapes, orientations, and positions. Central to the model is the concept of a head sensitivity map, which can be used to characterize the sensor head as a function of the shape, size, and position of the sensor coils. Two further concepts related to the head sensitivity are presented, which are the zero equisensitivity surface and the volume of influence. We demonstrate that these concepts aid the understanding of the detector behavior. The general model is based on the Born approximation, which is valid if the soil magnetic susceptibility is sufficiently small. A simpler model, which is only valid for homogeneous half-space soils but does not require the Born approximation, is also developed. The responses predicted by both models are shown to be in good agreement with each other and also with available analytic solutions. Comparing the two models also enabled an expression for the error incurred when using the Born approximation to be established. We shown that, for most soils of relevance to mine clearance, the corresponding error is negligible. View full abstract»

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  • GPR Response From Buried Pipes: Measurement on Field Site and Tomographic Reconstructions

    Publication Year: 2009 , Page(s): 2639 - 2645
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (977 KB) |  | HTML iconHTML  

    The identification of the physical nature of an object or target causing a ground-penetrating radar (GPR) anomaly, as well as the estimation of a target's dimensions and geometry, is rather challenging. To improve target identification, basic studies are still required, and they can be addressed primarily using a laboratory- or field-based physical model. The field model (test site) is usually expensive and difficult to build, but it provides data for controlled target properties and geometry from a natural environment that are essential for testing processing techniques. In this paper, we present the results from a field experiment where GPR data were collected on plastic and metallic pipes. The main objective is the comparison of the classical migration technique with a microwave tomography approach for reconstructing the geometrical target properties. The use of the microwave tomography approach will allow us to obtain more focused and stable images of the buried objects compared to the ones obtained using classical migration techniques. View full abstract»

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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.

 

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Meet Our Editors

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