Showing papers in "IEEE Transactions on Geoscience and Remote Sensing in 1992"

Decorrelation in interferometric radar echoes

Abstract: A radar interferometric technique for topographic mapping of surfaces, implemented utilizing a single synthetic aperture radar (SAR) system in a nearly repeating orbit, is discussed. The authors characterize the various sources contributing to the echo correlation statistics, and isolate the term which most closely describes surficial change. They then examine the application of this approach to topographic mapping of vegetated surfaces which may be expected to possess varying backscatter over time. It is found that there is decorrelation increasing with time but that digital terrain model generation remains feasible. The authors present such a map of a forested area in Oregon which also includes some nearly unvegetated lava flows. Such a technique could provide a global digital terrain map. >

An empirical model and an inversion technique for radar scattering from bare soil surfaces

Abstract: Polarimetric radar measurements were conducted for bare soil surfaces under a variety of roughness and moisture conditions at L-, C-, and X-band frequencies at incidence angles ranging from 10 degrees to 70 degrees . Using a laser profiler and dielectric probes, a complete and accurate set of ground truth data was collected for each surface condition, from which accurate measurements were made of the rms height, correlation length, and dielectric constant. Based on knowledge of the scattering behavior in limiting cases and the experimental observations, an empirical model was developed for sigma degrees /sub hh/, sigma degrees /sub vv/, and sigma degrees /sub hv/ in terms of ks (where k=2 pi / lambda is the wave number and s is the rms height) and the relative dielectric constant of the soil surface. The model, which was found to yield very good agreement with the backscattering measurements of the present study as well as with measurements reported in other investigations, was used to develop an inversion technique for predicting the rms height of the surface and its moisture content from multipolarized radar observations. >

Backscattering from a randomly rough dielectric surface

Abstract: A backscattering model for scattering from a randomly rough dielectric surface is developed. Both like- and cross-polarized scattering coefficients are obtained. The like-polarized scattering coefficients contain single scattering terms and multiple scattering terms. The single scattering terms are shown to reduce to the first-order solutions derived from the small perturbation method when the roughness parameters satisfy the slightly rough conditions. When surface roughnesses are large but the surface slope is small, only a single scattering term corresponding to the standard Kirchhoff model is significant. If the surface slope is large, the multiple scattering term will also be significant. The cross-polarized backscattering coefficients satisfy reciprocity and contain only multiple scattering terms. The difference between vertical and horizontal scattering coefficients increases with the dielectric constant and is generally smaller than that predicted by the first-order small perturbation model. Good agreements are obtained between this model and measurements from statistically known surfaces. >

Atmospherically resistant vegetation index (ARVI) for EOS-MODIS

Abstract: An atmospherically resistant vegetation index (ARVI) is proposed and developed for remote sensing of vegetation from the Earth Observing System (EOS) MODIS sensor. The same index can be used for remote sensing from Landsat TM and the EOS-HIRIS sensor. The index takes advantage of the presence of the blue channel (0.47.+or-0.01 mu m) in the MODIS sensor, in addition to the red (0.66+or-0.025 mu m) and the near-IR (0.865+or-0.02 mu m) channels that compose the present normalized difference vegetation index (NDVI). The resistance of the ARVI to atmospheric effects (in comparison to the NDVI) is accomplished by a self-correction process for the atmospheric effect on the red channel, using the difference in the radiance between the blue and the red channels to correct the radiance in the red channel. Simulations using radiative transfer computations on arithmetic and natural surface spectra, for various atmospheric conditions, show that ARVI has a similar dynamic range to the NDVI, but is, on average, four times less sensitive to atmospheric effects than the NDVI. >

Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS)

Abstract: The authors describe the status of MODIS-N and its companion instrument MODIS-T (tilt), a tiltable cross-track scanning spectrometer with 32 uniformly spaced channels between 0.410 and 0.875 mu m. They review the various methods being developed for the remote sensing of atmospheric properties using MODIS, placing primary emphasis on the principal atmospheric applications of determining the optical, microphysical, and physical properties of clouds and aerosol particles from spectral reflection and thermal emission measurements. In addition to cloud and aerosol properties, MODIS-N will be used for determining the total precipitable water vapor and atmospheric stability. The physical principles behind the determination of each of these atmospheric products are described, together with an example of their application to aircraft and/or satellite measurements. >

Relating forest biomass to SAR data

Abstract: The authors present the results of an experiment defined to demonstrate the use of radar to retrieve forest biomass. The SAR data were acquired by the NASA/JPL SAR over the Landes pine forest during the 1989 MAESTRO-1 campaign. The SAR data, after calibration, were analyzed together with ground data collected on forest stands from a young stage (eight years) to a mature stage (46 years). The dynamic range of the radar backscatter intensity from forest was found to be greatest at P-band and decreased with increasing frequencies. Cross-polarized backscatter intensity yielded the best sensitivities to variations of forest biomass. L-band data confirmed past results on good correlation with forest parameters. The most striking observation was the strong correlation of P-band backscatter intensity to forest biomass. >

Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: effect of crown shape and mutual shadowing

Abstract: In the case where a vegetation cover can be regarded as a collection of individual, discrete plant crowns, the geometric-optical effects of the shadows that the crowns cast on the background and on one another strongly condition the brightness of the vegetation cover as seen from a given viewpoint in the hemisphere. An asymmetric hotspot, in which the shape of the hotspot is related to the shape of the plant crowns in the scene, is created. At large zenith angles illumination shadows will preferentially shadow the lower portions of adjacent crowns. Further, these shadows will be preferentially obscured since adjacent crowns will also tend to obscure the lower portions of other crowns. This effect produces a 'bowl-shaped' bidirectional reflectance distribution function (BRDF) in which the scene brightness increases at the function's edges. Formulas describing the hotspot and mutual-shadowing effects are derived, and examples that show how the shape of the BRDF is dependent on the shape of the crowns, their density, their brightness relative to the background, and the thickness of the layer throughout which the crown centers are distributed are presented. >

Dependence of radar backscatter on coniferous forest biomass

Abstract: Two independent experimental efforts have examined the dependence of radar backscatter on above-ground biomass of monospecie conifer forests using polarimetric airborne SAR data at P-, L- and C-bands. Plantations of maritime pines near Landes, France, range in age from 8 to 46 years with above-ground biomass between 5 and 105 tons/ha. Loblolly pine stands established on abandoned agricultural fields near Duke, NC, range in age from 4 to 90 years and extend the range of above-ground biomass to 560 tons/ha for the older stands. These two experimental forests are largely complementary with respect to biomass. Radar backscatter is found to increase approximately linearly with increasing biomass until it saturates at a biomass level that depends on the radar frequency. The biomass saturation level is about 200 tons/ha at P-band and 100 tons/ha at L-band, and the C-band backscattering coefficient shows much less sensitivity to total above-ground biomass. >

A comparison of range-Doppler and wavenumber domain SAR focusing algorithms

Abstract: Focusing of SAR data requires a space-variant two-dimensional correlation. Different algorithms are compared with each other in terms of their focusing quality and their ability to handle the space-variance of the correlation kernel: the range-Doppler approach with and without secondary range compression, modified range-Doppler algorithms, and four versions of the wavenumber domain processor. The phase aberrations of the different algorithms are given in analytic form. Numerical examples are presented for Seasat and ERS-1. A novel systems theoretical derivation of the wavenumber domain algorithm is presented. >

The impact of misregistration on change detection

Abstract: The impact of misregistration on the detection of changes in land cover has been evaluated using spatially degraded Landsat MSS images, focusing on simulated images of the normalized difference vegetation index (NDVI) Single-date images from seven areas were misregistered against themselves, and the statistical properties of the differences were analyzed In the absence of any actual changes to the land surface, the consequences of misregistration were very marked even for subpixel misregistrations Pairs of images from different time periods were then misregistered For four densely covered areas, an error equivalent to greater than 50% of the actual differences in the NDVI, as measured by the semivariance, was induced by a misregistration of only one pixel To achieve an error of only 10%, registration accuracies of 02 pixels or less are required For three more sparsely vegetated areas with semiarid climates, a registration accuracy of between 05 and 10 pixel was sufficient to achieve an error of 10% or less The results indicate that high levels of registration are needed for reliable monitoring of global change >

Multispectral classification of Landsat-images using neural networks

Abstract: The authors report the application of three-layer back-propagation networks for classification of Landsat TM data on a pixel-by-pixel basis. The results are compared to Gaussian maximum likelihood classification. First, it is shown that the neural network is able to perform better than the maximum likelihood classifier. Secondly, in an extension of the basic network architecture it is shown that textural information can be integrated into the neural network classifier without the explicit definition of a texture measure. Finally, the use of neural networks for postclassification smoothing is examined. >

SAR calibration: an overview

Abstract: Progress in synthetic-aperture radar, (SAR) calibration is reviewed. The difficulties of calibrating both airborne and spaceborne SAR image data are addressed. The quantities measured by a SAR, i.e. radar backscatter, are defined and mathematical formulations for the three basic types of SAR image are developed. The difficulties in establishing science requirements for calibration are discussed. The measurement of SAR image quality is briefly addressed. The problem of radiometric calibration is introduced via the SAR form of the radar equation, with both internal and external calibration approaches considered. The development of algorithms for polarimetric radar calibration is reviewed and the problems involved in phase calibration of interferometric SAR are discussed. Future challenges in the field of SAR calibration are considered. >

Classification of multispectral remote sensing data using a back-propagation neural network

Abstract: The suitability of a back-propagation neural network for classification of multispectral image data is explored. A methodology is developed for selection of both training parameters and data sets for the training phase. A new technique is also developed to accelerate the learning phase. To benchmark the network, the results are compared to those obtained using three other algorithms: a statistical contextual technique, a supervised piecewise linear classifier, and an unsupervised multispectral clustering algorithm. All three techniques were applied to simulated and real satellite imagery. Results from the classification of both Monte Carlo simulation and real imagery are summarized. >

Remote sensing of water vapor in the near IR from EOS/MODIS

Abstract: The LOWTRAN-7 code was used to simulate remote sensing of water vapor over 20 different surface covers. The simulation was used to optimize the water vapor channel selection and to test the accuracy of the remote sensing method. The channel selection minimizes the uncertainty in the derived water vapor due to variations in the spectral dependence of the surface reflectance. The selection also minimizes the sensitivity of the selected channels to possible drift in the channel position. The use of additional MODIS channels reduces the errors due to the effect of haze, subpixel clouds and uncertainties in the temperature profile. Remote sensing of the variation of water vapor from day to day will be more accurate, because the surface reflectances vary slowly with time. The method was applied to Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data. >

Measurement of oceanic wind vector using satellite microwave radiometers

Abstract: The possibility of retrieving both wind speed and direction from microwave radiometer measurements of the ocean is studied using Special Sensor Microwave/Imager (SSM/I) measurements collocated with buoy reports from the National Data Buoy Center (NDBC). A physically based algorithm is used to retrieve the wind speed. The RMS difference between the SSM/I and buoy wind speed is 1.6 m/s for 3321 comparisons. It is found that the SSM/I minus buoy wind speed difference is correlated with wind direction. When this wind direction signal is removed, the RMS difference between the SSM/I and buoy winds reduces to 1.3 m/s. The wind direction signal is used to make global, low-resolution maps of the monthly mean oceanic vector. The wind direction sensing capability of a prospective two-look satellite radiometer is also processed. >

SARAS: a synthetic aperture radar (SAR) raw signal simulator

Abstract: An SAR simulator of an extended three-dimensional scene is presented. It is based on a facet model for the scene, asymptotic evaluation of SAR unit response, and a two-dimensional fast Fourier transform code for the data processing. Prescribed statistics of the model account for a realistic speckle of the image. The simulator is implemented in Synthetic Aperture Radar Advance Simulators (SARAS), whose performance is described and illustrated by a number of examples. >

A microwave scattering model for layered vegetation

Abstract: A microwave scattering model was developed for layered vegetation based on an iterative solution of the radiative transfer equation up to the second order to account for multiple scattering within the canopy and between the ground and the canopy. The model is designed to operate over a wide frequency range for both deciduous and coniferous forest and to account for the branch size distribution, leaf orientation distribution, and branch orientation distribution for each size. The canopy is modeled as a two-layered medium above a rough interface. The upper layer is the crown, containing leaves, stems, and branches. The lower layer is the trunk region, modeled as randomly positioned cylinders with a preferred orientation distribution above an irregular soil surface. Comparisons of results obtained using this model with measurements from deciduous and coniferous forests show good agreement at several frequencies for both like and cross polarizations. >

Atmospheric correction algorithm for NOAA-AVHRR products: theory and application

Abstract: Investigation of the effect of atmospheric constituents on NOAA Advanced Very High Resolution Radiometer (AVHRR) visible and near-infrared data is presented. The general remote sensing equation, including scattering, absorption, and bidirectional reflectance effects for the AVHRR solar bands, is described. The magnitude of the atmospheric effects for AVHRR solar bands with respect to their impact on the normalized difference vegetation index (NDVI) and the surface bidirection reflectance is examined. Possible approaches for acquiring atmospheric information are discussed, and examples of atmospheric correction of surface reflectance and NDVI are given. Invariant effects (ozone absorption and molecular scattering) and variant effects (water vapor absorption and aerosol scattering) are shown to dominate the atmospheric effects in the AVHRR solar bands. >

The TOPSAR interferometric radar topographic mapping instrument

Abstract: The authors have augmented the NASA DC-8 AIRSAR instrument with a pair of C-band antennas displaced across track to form an interferometer sensitive to topographic variations of the Earth's surface. During the 1991 DC-8 flight campaign, data were acquired over several sites in the US and Europe, and topographic maps were produced from several of these flight lines. Analysis of the results indicate that statistical errors are in the 2-4-m range, while systematic effects due to aircraft motion are in the 10-20-m range. The initial results from development of a second-generation processor show that aircraft motion compensation algorithms reduce the systematic variations to 2 m, while the statistical errors are reduced to 2-3 m. >

Aerosol retrieval over land from AVHRR data-application for atmospheric correction

Abstract: Correction of Advanced Very High Resolution Radiometer (AVHRR) imagery for the aerosol effect requires retrieval of the aerosol loading from the images. Two retrieval algorithms that were previously developed for Landsat are modified for the AVHRR. The methods determine the aerosol optical thickness over land surfaces from AVHRR band one data independently of ancillary information. The first method retrieves aerosols based on the atmospheric effect on the path radiance. This method requires the surface reflectance to be 0.02+or-0.01, which is found over forests in the red channel. Two techniques are used to screen an AVHRR scene for pixels that have this low reflectance. The qualifying requirements for these techniques are discussed, and the method is demonstrated to retrieve aerosol optical thicknesses to approximately +or-0.1. The second method uses the change in contrast for several scenes to determine the change in the optical thickness between the scenes. A reference scene allows absolute determination. The method has an rms error of approximately 0.1. >

Ranging performance of satellite laser altimeters

Abstract: Topographic mapping of the Earth, Moon, and planets can be accomplished with high resolution and accuracy using satellite laser altimeters. These systems employ nanosecond laser pulses and microradian beam divergences to achieve submetre vertical range resolution from orbital altitudes of several hundred kilometres. In this paper the authors develop detailed expressions for the range and pulsewidth measurement accuracies and use the results to evaluate the ranging performances of several satellite laser altimeters currently under development by NASA for launch during the next decade. The analysis includes the effects of the target surface characteristics, spacecraft pointing jitter, and waveform digitizer characteristics. The results show that ranging accuracy is critically dependent on the pointing accuracy and stability of the altimeter, especially over high-relief terrain where surface slopes are large. At typical orbital altitudes of several hundred kilometres, single-shot accuracies of a few centimetres can be achieved only when the pointing jitter is on the order of 10 mu rad or less. >

Comparison of algorithms for retrieval of snow water equivalent from Nimbus-7 SMMR data in Finland

Abstract: The correlation between the brightness temperature of snow-covered terrain (dry snow) and the snow-water equivalent in Finland was investigated using Nimbus-7 SMMR data. The satellite data set covers the winters of 1978-9 through 1981-2. The correlation analysis was performed for 17 different brightness temperature functions, each involving one or several frequencies and polarizations. The highest correlation coefficients between the satellite-derived brightness temperature functions and the manually measured snow-water equivalent values were obtained by using the brightness temperature difference between 37 GHz and either 18 GHz or 10.7 GHz, vertical polarization. >

New approaches in interferometric SAR data processing

Abstract: It is known that interferometric synthetic-aperture radar (SAR) images can be inverted to perform surface elevation mapping. Among the factors critical to the mapping accuracy are registration of the interfering SAR images and phase unwrapping. A registration algorithm is presented that determines the registration parameters through optimization. A figure of merit is proposed that evaluates the registration result during the optimization. The phase unwrapping problem is approached through a new method involving fringe line detection. The algorithms are tested with two SEASAT SAR images of terrain near Yellowstone National Park. These images were collected on SEASAT orbits 1334 and 1420, which were very close together in space, i.e. less than 100 m. >

Sensitivity to microwave measurements to vegetation biomass and soil moisture content: a case study

Abstract: A comparative evaluation of the potential of active and passive microwave sensors in estimating vegetation biomass and soil moisture content is carried out. For this purpose, experimental data collected on an agricultural area by airborne scatterometers and radiometers during the AGRISCATT and AGRIRAD 1988 campaigns have been used. The results show that both microwave backscattering and emission are sensitive to vegetation biomass over a wide frequency range. Multifrequency observations seem to offer good probabilities for separating wide leaf from small leaf herbaceous crops, and for detecting different growth stages. Low frequency data (L band) at a steep incidence angle (10 degrees ) confirm that both the backscattering coefficient and the normalized temperature are correlated and sensitive to soil moisture content. >

Branching model for vegetation

Abstract: A branching model is proposed for the remote sensing of vegetation. The frequency and angular responses of a two-scale cylinder cluster are calculated to demonstrate the significance of vegetation architecture. The results indicate that the architecture of vegetation plays an important role in determining the observed coherent effects. A two-scale branching model is implemented for soybean with its internal structure and the resulting clustering effects considered. At the scale of soybean fields, the relative location of soybean plants is described by a pair distribution function. The polarimetric backscattering coefficients are obtained in terms of the scattering properties of soybean plants and the pair distribution function. Theoretical backscattering coefficients evaluated using the hole-correction pair distribution are in good agreement with extensive data from soybean fields. The hole-correction approximation, which prevents two soybean plants from overlapping each other, is more realistic and improves the agreement between the model calculation and experimental data near normal incidence. >

Unsupervised segmentation of polarimetric SAR data using the covariance matrix

Abstract: A method for unsupervised segmentation of polarimetric synthetic aperture radar (SAR) data into classes of homogeneous microwave polarimetric backscatter characteristics is presented. Classes of polarimetric backscatter are selected on the basis of a multidimensional fuzzy clustering of the logarithm of the parameters composing the polarimetric covariance matrix. The clustering procedure uses both polarimetric amplitude and phase information, is adapted to the presence of image speckle, and does not require an arbitrary weighting of the different polarimetric channels; it also provides a partitioning of each data sample used for clustering into multiple clusters. Given the classes of polarimetric backscatter, the entire image is classified using a maximum a posteriori polarimetric classifier. Four-look polarimetric SAR complex data of lava flows and of sea ice acquired by the NASA/JPL airborne polarimetric radar (AIRSAR) are segmented using this technique. >

Polarimetric discriminators for SAR images

Abstract: A method is developed for optimizing the degree of polarization of a partially polarized wave reflected by a nonstationary scattering object. The method permits, for a scattered wave and a given target characterized by its Mueller matrix, analytic computation of the maximum and minimum values of the degree of polarization, and the corresponding transmitted polarizations. A procedure for the optimization of the scattered wave intensity is also proposed. The degree of polarization and the total scattered intensity extrema are then analyzed experimentally on JPL data. It is shown that several entities such as the received intensity extrema, the coefficient of variation, the fractional polarization and the span, which are currently used for target discrimination, can be deduced from combinations of the maximum and minimum values of the degree of polarization and the scattered wave intensity. Finally, a classification of the San Francisco image, based on these indices, is conducted for a better understanding of the specific physical meaning of each index. >

Real-time synthetic aperture radar (SAR) processing with a new subaperture approach

Abstract: A time-domain subaperture approach that is suitable for real-time synthetic aperture radar (SAR) processing and that produces high-quality, full-resolution images is presented. The real-time subaperture algorithm is based on an approximation of the phase history correction in each subaperture with a simple linear correction, which can be carried out by an up/down-conversion of the received signal followed by a moving average operation. The characteristics of the impulse response function are improved considerably by means of a frequency overlap of the subapertures and become comparable to a conventional matched filter response. Special algorithms for high-quality SAR processing, such as autofocus, Doppler centroid estimation, and range migration correction, can be efficiently implemented. High flexibility is achieved for multilook processing and no secondary range compression is needed, even for high squint angles. >

Inversion of snow parameters from passive microwave remote sensing measurements by a neural network trained with a multiple scattering model

Abstract: The inversion of snow parameters from passive microwave remote sensing measurements is performed with a neural network trained with a dense-media multiple-scattering model. The input-output pairs generated by the scattering model are used to train the neural network. Simultaneous inversion of three parameters, mean-grain size of ice particles in snow, snow density, and snow temperature from five brightness temperatures, is reported. It is shown that the neural network gives good results for simulated data. The absolute percentage errors for mean-grain size of ice particles and snow density are less than 10%, and the absolute error for snow temperature is less than 3 K. The neural network with the trained weighting coefficients of the three-parameter model is also used to invert SSMI data taken over the Antarctic region. >

Preliminary analysis of ERS-1 SAR for forest ecosystem studies

Abstract: The authors examine an image obtained by the C-band VV-polarized ERS-1 SAR with respect to potential land applications. A scene obtained near noon on Aug. 15, 1991, along the US-Canadian border near Sault Ste. Marie is calibrated relative to an array of trihedral corner reflectors and active radar calibrators distributed across the swath. Extensive contemporaneous ground observations of forest stands are used to predict sigma degrees at the time of the SAR overpass using a first-order vector radiative transfer model (MIMICS). These predictions generally agree with the calibrated ERS-1 data to within 1 dB. It is demonstrated that the dynamic range of sigma degrees is sufficient to perform limited discrimination of various forest and grassland communities even for a single-date observation. Furthermore, it is demonstrated that retrieval of near-surface soil moisture is feasible for grass-covered soils when plant biomass is less than 1 tonne/ha. >