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It is important to monitor forests in order to understand the impacts of global climate changes on terrestrial ecosystems. To characterize the forest changes, it is useful to parameterize a forest using several parameters.
A GPS transmitter-receiver pair form a bistatic radar for ocean remote sensing when the receiving platform carries a downlooking antenna capable of collecting the GPS signal scattered off the ocean surface.
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SAR interferometry has enabled two important science applications: surface change detection and topographic mapping.
A theoretical emission model of combined ocean surface and atmosphere is presented to predict the microwave emissivity of ocean. The modeled ocean surface is one-dimensional with a random rough profile.
We have observed the rest-frame optical and UV spectra of the luminous, high redshift IRAS source FSC10214+4724. We find the optical emission lines to be characterized by ratios similar to those found in Seyfert II galaxies.
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We presented the analysis of Windsat data for hurricanes Isabel and Fabian in 2003. The polarimetric third and fourth Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the QuikSCAT wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.
An experiment using a polarimetric scatterometer (POLSCAT) has been conducted by JPL for ocean surface wind measurement. It shows that (sigma) (subscript)0 values for HH, W, HV, and VH have the property of even symmetry with respect to the upwind direction, and correlation coefficients between co- and cross-polarizations have the odd symmetry property. In this paper, the symmetry properties will be further examined using polarimetric analysis to investigate the depolarization effect, the scattering mechanism, and the polarization orientation angle. Theoretical results based on a two scale model are used to verify the derived experiment results. The newly derived symmetry property has the potential to solve the 180(deg) ambiguity in wind direction, and to enhance the accuracy of wind vector measurements.
The synergism of active and passive microwave techniques for hurricane ocean wind remote sensing is explored. We performed the analysis of Windsat data for Atlantic hurricanes in 2003-2005. The polarimetric third Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the QuikSCAT wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.
Two simple scattering mechanisms are fitted to polarimetric synthetic aperture radar (SAR) observations of forests. The mechanisms are canopy scatter from a reciprocal medium with azimuthal symmetry and a ground scatter term that can represent double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants or Bragg scatter from a moderately rough surface, which is seen through a layer of vertically oriented scatterers. The model is shown to represent the behavior of polarimetric backscatter from a tropical forest and two temperate forest sites by applying it to data from the National Aeronautic and Space Agency/Jet Propulsion Laboratory's Airborne SAR (AIRSAR) system. Scattering contributions from the two basic scattering mechanisms are estimated for clusters of pixels in polarimetric SAR images. The solution involves the estimation of four parameters from four separate equations. This model fit approach is justified as a simplification of more complicated scattering models, which require many inputs to solve the forward scattering problem. The model is used to develop an understanding of the ground-trunk double-bounce scattering that is present in the data, which is seen to vary considerably as a function of incidence angle. Two parameters in the model fit appear to exhibit sensitivity to vegetation canopy structure, which is worth further exploration. Results from the model fit for the ground scattering term are compared with estimates from a forward model and shown to be in good agreement. The behavior of the scattering from the ground-trunk interaction is consistent with the presence of a pseudo-Brewster angle effect for the air-trunk scattering interface. If the Brewster angle is known, it is possible to directly estimate the real part of the dielectric constant of the trunks, a key variable in forward modeling of backscatter from forests. It is also shown how, with a priori knowledge of the forest height, an estimate for the attenuation coefficient of the canopy can be obtained directly from the multi-incidence-angle polarimetric observations. This attenuation coefficient is another key variable in forward models and is generally related to the canopy density.
We are developing onboard processor technology targeted at the L-band SAR instrument onboard the planned DESDynI mission to enable formation of SAR images onboard opening possibilities for near-real-time data products to augment full data streams. Several image processing and/or interpretation techniques are being explored as possible direct-broadcast products for use by agencies in need of low-latency data, responsible for disaster mitigation and assessment, resource management, agricultural development, shipping, etc. Data collected through UAVSAR (L-band) serves as surrogate to the future DESDynI instrument. We have explored surface water extent as a tool for flooding response, and disturbance images on polarimetric backscatter of repeat pass imagery potentially useful for structural collapse (earthquake), mud/land/debris-slides etc. We have also explored building vegetation and snow/ice classifiers, via support vector machines utilizing quad-pol backscatter, cross-pol phase, and a number of derivatives (radar vegetation index, dielectric estimates, etc.). We share our qualitative and quantitative results thus far.
We report here an analysis of the polarization dependence of L-band radar backscatter from the main slick of the Deepwater Horizon oil spill, with specific attention to the utility of polarimetric decomposition analysis for discrimination of oil from clean water and identification of variations in the oil characteristics. For this study we used data collected with the UAVSAR instrument from opposing look directions directly over the main oil slick. We find that both the Cloude-Pottier and Shannon entropy polarimetric decomposition methods offer promise for oil discrimination, with the Shannon entropy method yielding the same information as contained in the Cloude-Pottier entropy and averaged in tensity parameters, but with significantly less computational complexity
In this paper we show our first POLINSAR results using the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) developed by the Jet Propulsion Laboratory (JPL). UAVSAR is a L-band repeat-pass polarimetric and interferometric system designed for measuring vegetation structure and monitoring crustal deformations. In order to extract canopy height from POLINSAR data and account for temporal decorrelation, we formulate a physical model of the temporal-volumetric coherence, random motion over ground (RMOG) model. Canopy height extracted from single-baseline UAVSAR data using the RMOG model is shown to be in agreement with canopy height measured by the Land, Vegetation, and Ice Sensor (LVIS) lidar.
A semi-empirical algorithm for the retrieval of soil moisture, root mean square (RMS) height and biomass from polarimetric SAR data is explained and analyzed in this paper. The algorithm is a simplification of the distorted Born model. It takes into account the physical scattering phenomenon and has three major components: volume, double-bounce and surface. This simplified model uses the three backscattering coefficients ( sigma HH, sigma HV and sigma vv) at low-frequency (P-band). The inversion process uses the Levenberg-Marquardt non-linear least-squares method to estimate the structural parameters. The estimation process is entirely explained in this paper, from initialization of the unknowns to retrievals. A sensitivity analysis is also done where the initial values in the inversion process are varying randomly. The results show that the inversion process is not really sensitive to initial values and a major part of the retrievals has a root-mean-square error lower than 5% for soil moisture, 24 Mg/ha for biomass and 0.49 cm for roughness, considering a soil moisture of 40%, roughness equal to 3cm and biomass varying from 0 to 500 Mg/ha with a mean of 161 Mg/ha
UAVSAR has demonstrated the combined Precisions Autopilot coupled with the L-band electronically steered allow for robust repeat pass radar interferometric collections. Science results in the areas of soil moisture, volcanology, solid earth science, glaciology, and ecosystem system science have been achieved using the UAVSAR platform.
We report the results of high-accuracy controlled laboratory measurements of the Stokes reflection matrix for suspensions of submicrometer-sized latex particles in water and compare them with the results of a numerically exact computer solution of the vector radiative transfer equation (VRTE). The quantitative performance of the VRTE is monitored by increasing the volume packing density of the latex particles from 2 to 10. Our results indicate that the VRTE can be applied safely to random particulate media with packing densities up to 2. VRTE results for packing densities of the order of 5 should be taken with caution, whereas the polarized bidirectional reflectivity of suspensions with larger packing densities cannot be accurately predicted. We demonstrate that a simple modification of the phase matrix entering the VRTE based on the so-called static structure factor can be a promising remedy that deserves further examination.