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NASA NTRS1993

(abstract) The SIR-C/X-SAR Mission

The Shuttle Imaging Radar-C and X-Band Synthetic Aperture Radar (SIR-C/X-SAR) is a cooperative experiment between the National Aeronautics and Space Administration (NASA), the German Space Agency (DARA), and the Italian Space Agency (ASI). The experiment is the next evolutionary step in NASA's Spaceborne Imaging Radar (SIR) program that began with the Seasat SAR in 1978, and continued with SAR -A in 1981 and SAR-B in 1984. The program will eventually lead to the Earth Observing System (EOS) SAR later in this decade. SIR-C will provide increased capability over Seasat, SIR-A, and SIR-B by acquiring polarimetric images simultaneously at two microwave frequencies: L-band (wavelength 24 cm) and C-band (wavelength 6 cm). X-SAR will operate at X-band (wavelength 3 cm) with VV polarization, resulting in a three-frequency capability. Because radar backscatter is most strongly influenced by objects comparable in size to the radar wavelength, this multifrequency capability will provide information about the Earth's surface over a wide range of scales not discernable with single-frequency experiments. The polarimetric data will yield quantitative information about the surface geometric structure, vegetation dielectric properties, and surface discontinuities. The first SIR-C/X-SAR flight is planned for early in 1994, with two subsequent flights in different seasons to enable data aquisition under different environmental conditions. SIR-C/X-SAR will collect data for a period of 6 to 9 days during each flight. The instrument will be flown in a 57(deg) inclination orbit with a nomimal orbit altitude of 215 km. This altitude will result in a slightly drifting orbit. The latest status of the SIR-C/X-SAR mission and instrument design, science activities, and expected results will be presented.

SIR-C/XSAR radar backscatter surface geometric str↗
NASA NTRS1996

A Three-component Scattering Model for Polarimetric SAR Data

Classification, decomposition and modeling of polarimetric SAR data has received a great deal of attention in the recent literature. The objective behind these efforts is to better understand the scattering mechanisms which give rise to the polarimetric signatures seen in SAR image data.

SAR data AIRSAR backscatter scattering↗
NASA NTRS2022

Optical properties of morphologically complex black carbon aerosols: Effects of coatings

Optical properties are computed for fractal-like aggregate black carbon (BC) aerosols coated with different substances. Two models are used for these aerosols: (i) the coated aggregate model (model I), where coating is added to the voids and surroundings of BC fractal-like aggregates; and (ii) the closed-cell aggregate model (model II), where coating is added concentrically to each monomer of BC fractal-like aggregates. Our results favor choosing the coated aggregate model (model I) to simulate scattering and absorption by coated BC aerosols because this model is morphologically more realistic, and because this model yields mass absorption cross section (MAC) and backscattering linear depolarization ratio (LDR) values that are consistent with field measurements. Moreover the corresponding computed degree of linear polarization (DoLP) and LDR values are very sensitive to changes in the coating volume fraction (fvol) and the coating refractive index (m). With the same absorbing BC core, the MAC value increases steadily with increasing fvol and m values. For example, using a density of 1.8 g/cm 3 and BC refractive index 1.95 + i0.79, the calculated MAC values for uncoated BC aggregates range from 6.2 to 6.8 m 2 /g at 0.55 µm. When coating material is applied to the BC aggregates, the calculated MAC values for model I particles increase to between 9.8 and 13.2 m 2 /g (depending on m) when fvol = 87.5%. The backscattering LDR values also tend to increase with the increasing m values for the shapes and sizes considered in our study. For model I particles, the backscattering LDR values span a wide range of 4.2–27.8% at a wavelength of 0.35 µm at fvol = 87.5% when m increases from 1.33 to 1.55. Our results are relevant to analyses of polarimetric and lidar observations of smoke particles, especially when these particles undergo hygroscopic growth.

Black carbon aerosols↗
NASA NTRS1998

Estimating Subcanopy Soil Moisture with RADAR

The subcanopy soil moisture of a boreal old jack pine forest is estimated using polarimetric L- and P-band AIRSAR data. Model simulations have shown that for this stand, the principal scattering mechanism responsible for radar backscatter is the double-bounce mechanism between the tree trunks and the ground.

radar soil moisture vegetation non-linear estimati↗
NASA NTRS1992

Polarimetric signatures of a coniferous forest canopy based on vector radiative transfer theory

Complete polarization signatures of a coniferous forest canopy are studied by the iterative solution of the vector radiative transfer equations up to the second order. The forest canopy constituents (leaves, branches, stems, and trunk) are embedded in a multi-layered medium over a rough interface. The branches, stems and trunk scatterers are modeled as finite randomly oriented cylinders. The leaves are modeled as randomly oriented needles. For a plane wave exciting the canopy, the average Mueller matrix is formulated in terms of the iterative solution of the radiative transfer solution and used to determine the linearly polarized backscattering coefficients, the co-polarized and cross-polarized power returns, and the phase difference statistics. Numerical results are presented to investigate the effect of transmitting and receiving antenna configurations on the polarimetric signature of a pine forest. Comparison is made with measurements.

Karam, M. A.↗
NASA NTRS1992

An examination of the assumptions in the POLCAL cross-talk removal algorithm

The POLCAL crosstalk removal algorithm is based on the statistical properties of the image background and does not need any corner reflector or active radar calibrator deployed in the scene. The advantage of being able to remove the crosstalk contamination without using external calibration targets gives rise to the consideration of algorithms based on clutter statistics in polarimetric synthetic aperture radar (SAR) images in more detail. The basic assumption of the POLCAL procedure is the decorrelation of copolarized and cross-polarized backscatter, which is valid for natural targets with azimuthal symmetry. This assumption and others regarding the properties of the imaged surface are examined. An improved version called POLCALII is presented, and its performance is compared with POLCAL.

Zink, M.↗
NASA NTRS1991

Calibration of a polarimetric imaging SAR

Calibration of polarimetric imaging Synthetic Aperture Radars (SAR's) using point calibration targets is discussed. The four-port network calibration technique is used to describe the radar error model. The polarimetric ambiguity function of the SAR is then found using a single point target, namely a trihedral corner reflector. Based on this, an estimate for the backscattering coefficient of the terrain is found by a deconvolution process. A radar image taken by the JPL Airborne SAR (AIRSAR) is used for verification of the deconvolution calibration method. The calibrated responses of point targets in the image are compared both with theory and the POLCAL technique. Also, response of a distributed target are compared using the deconvolution and POLCAL techniques.

Sarabandi, K.↗
NASA NTRS1992

Calibration of a polarimetric imaging SAR

Calibration of polarimetric imaging Synthetic Aperture Radars (SAR's) using point calibration targets is discussed. The four-port network calibration techniques is used to describe the radar error model. The polarimetric ambiguity function of the SAR is then found using a single point target, namely a trihedral corner reflector. Based on this, an estimate for the backscattering coefficient of the terrain is found by a deconvolution process. A radar image taken by the JPL Airborne SAR (AIRSAR) is used for verification of the deconvolution calibration method. The calibrated responses of point targets in the image are compared both with theory and the POLCAL technique. Also, response of a distributed target are compared using the deconvolution and POLCAL techniques.

Sarabandi, Kamal↗
NASA NTRS1993

Radiative transfer modelling of discontinuous tree canopies at microwave frequencies

Development of a first-order radiative transfer model for predicting backscatter from tree canopies has been underway at the University of Michigan Radiation Laboratory for some time. This model is known as the Michigan Microwave Canopy Scattering (MIMICS) model. This article presents the second-generation MIMICS model (MIMICS II) which accounts for canopies with discontinuous (open) crown layer geometries. MIMICS II models open crown layers by treating the location, size, and shape of the individual tree crowns as random variables. The backscattering coefficients for the canopy are then determined by introducing statistics derived from these parameters into the radiative transfer solution. Application of the radiative transfer equations to the discontinuous canopy geometry is presented. The resulting model is a robust fully polarimetric solution that is applicable over a wide variety of canopy architectures. Model simulations are compared to results generated with the continuous canopy model. The effect of the open crown geometry is found to be most significant at shallow incidence angles and at high frequencies for trees with well-developed crowns. Under these conditions, the gaps in the crown layer give rise to a notable increase in crown layer transmissivity which allows the radar to see through to the lower layers of the canopy more easily, thereby directly affecting the backscatter contribution of the trunks and ground.

Mcdonald, K. C.↗
NASA NTRS2020

Mapping tree canopy cover and canopy height with L-band SAR using LiDAR data and Random Forests

Light detection and ranging (LiDAR) data can provide direct measurements of vegetation structures but are limited by the sparse spatial coverage. Polarimetric synthetic aperture radar (SAR) can perform large-scale high-resolution mapping without weather constraints but the information about vegetation and ground subsurface are mixed in the backscatter data. In this paper, we adopted the Random Forests algorithm to train an upscaling function using tree canopy cover (TCC) and canopy height model (CHM) derived from Goddard’s LiDAR, Hyperspectral and Thermal Imager (G-LiHT) data. The regression model is then applied to the L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data acquired during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign to map the TCC and CHM over the Delta Junction area in interior Alaska.

Moghaddam, Mahta↗
NASA NTRS1992

Sea bottom topography imaging with SAR

It is well known that under favorable meteorological and hydrodynamical conditions the bottom topography of shallow seas can be mapped with airborne or spaceborne imaging radar. This phenomenon was observed for the first time in 1969 by de Loor and co-workers in Q-band Side Looking Airborne Radar (SLAR) imagery of sandwaves in the North Sea. It is now generally accepted that the imaging mechanism consists of three steps: (1) interaction between (tidal) current and bottom topography causes spatial modulations in the surface current velocity; (2) modulations in the surface current velocity give rise to variations in the spectrum of wind-generated waves, as described by the action balance equation; and (3) variations in the wave spectrum show up as intensity modulations in radar imagery. In order to predict radar backscatter modulations caused by sandwaves, an imaging model, covering the three steps, was developed by the Dutch Sea Bottom Topography Group. This model and some model results will be shown. On 16 Aug. 1989 an experiment was performed with the polarimetric P-, L-, and C-band synthetic aperture radar (SAR) of NASA/JPL. One scene was recorded in SAR mode. On 12 Jul. 1991 another three scenes were recorded, of which one was in the ATI-mode (Along-Track Interferometer). These experiments took place in the test area of the Sea Bottom Topography Group, 30 km off the Dutch coast, where the bottom topography is dominated by sand waves. In-situ data were gathered by a ship in the test area and on 'Measuring Platform Noordwijk', 20 km from the center of the test area. The radar images made during the experiment were compared with digitized maps of the bottom. Furthermore, the profiles of radar backscatter modulation were compared with the results of the model. During the workshop some preliminary results of the ATI measurements will be shown.

Vanderkooij, M. W. A.↗
NASA NTRS1997

Estimating Soil Moisture in a Boreal Old Jack Pine Forest

Polarimetric L- and P-band AIRSAR data, corresponding model simulations, and classification algorithms have shown that in a boreal old jack pine (OJP) stand, the principal scattering mechanism responsible for radar backscatter is the double-bounce mechanism between the tree trunks and the ground.

Soil↗
NASA NTRS1991

Statistical Partial Calibration Of Polarimetric SAR Imagery

Mathematical technique for partial calibration of quadpolarization synthetic-aperture-radar (SAR) image data makes possible to remove partially those contaminating cross-polarization effects (crosstalk) arising in antenna(s) and/or other transmitting and receiving channels. Quadpolarization data processed with help of technique better approximates backscattering properties of target area. If corner reflectors or other known discrete radar targets placed in target area, all of data channels calibrated both relatively to each other and absolutely.

Klein, Jeffrey D.↗
NASA NTRS1995

Estimation of Boreal Forest Biomass Using Spaceborne SAR Systems

In this paper, we report on the use of a semiempirical algorithm derived from a two layer radar backscatter model for forest canopies. The model stratifies the forest canopy into crown and stem layers, separates the structural and biometric attributes of the canopy. The structural parameters are estimated by training the model with polarimetric SAR (synthetic aperture radar) data acquired over homogeneous stands with known above ground biomass. Given the structural parameters, the semi-empirical algorithm has four remaining parameters, crown biomass, stem biomass, surface soil moisture, and surface rms height that can be estimated by at least four independent SAR measurements. The algorithm has been used to generate biomass maps over the entire images acquired by JPL AIRSAR and SIR-C SAR systems. The semi-empirical algorithms are then modified to be used by single frequency radar systems such as ERS-1, JERS-1, and Radarsat. The accuracy. of biomass estimation from single channel radars is compared with the case when the channels are used together in synergism or in a polarimetric system.

Saatchi, Sassan↗
NASA NTRS1993

Classification and soil moisture determination of agricultural fields

During the Mac-Europe campaign of 1991 several SAR (Synthetic Aperature Radar) experiments were carried out in the Flevoland test area in the Netherlands. The test site consists of a forested and an agricultural area with more than 15 different crop types. The experiments took place in June and July (mid to late growing season). The area was monitored by the spaceborne C-band VV polarized ERS-1, the Dutch airborne PHARS with similar frequency and polarization and the three-frequency PP-, L-, and C-band) polarimetric AIRSAR system of NASA/JPL. The last system passed over on June 15, 3, 12, and 28. The last two dates coincided with the overpasses of the PHARS and the ERS-1. Comparison of the results showed that backscattering coefficients from the three systems agree quite well. In this paper we present the results of a study of crop type classification (section 2) and soil moisture determination in the agricultural area (section 3). For these studies we used field averaged Stokes matrices extracted from the AIRSAR data (processor version 3.55 or 3.56).

Vandenbroek, A. C.↗
NASA NTRS1992

Quantitative analysis of surface characteristics and morphology in Death Valley, California using AIRSAR data

The Jet Propulsion Laboratory Airborne Synthetic Aperture Radar (JPL-AIRSAR) is used to collect full polarimetric measurements at P-, L-, and C-bands. These data are analyzed using the radar analysis and visualization environment (RAVEN). The AIRSAR data are calibrated using in-scene corner reflectors to allow for quantitative analysis of the radar backscatter. RAVEN is used to extract surface characteristics. Inversion models are used to calculate quantitative surface roughness values and fractal dimensions. These values are used to generate synthetic surface plots that represent the small-scale surface structure of areas in Death Valley. These procedures are applied to a playa, smooth salt-pan, and alluvial fan surfaces in Death Valley. Field measurements of surface roughness are used to verify the accuracy.

Kierein-Young, K. S.↗