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Layered classification techniques for remote sensing applications
The single-stage method of pattern classification utilizes all available features in a single test which assigns the unknown to a category according to a specific decision strategy (such as the maximum likelihood strategy). The layered classifier classifies the unknown through a sequence of tests, each of which may be dependent on the outcome of previous tests. Although the layered classifier was originally investigated as a means of improving classification accuracy and efficiency, it was found that in the context of remote sensing data analysis, other advantages also accrue due to many of the special characteristics of both the data and the applications pursued. The layered classifier method and several of the diverse applications of this approach are discussed.
Satellite and Surface Data Synergy for Developing a 3D Cloud Structure and Properties Characterization Over the ARM SGP. Stage 1: Cloud Amounts, Optical Depths, and Cloud Heights Reconciliation
One of the primary Atmospheric Radiation Measurement (ARM) Program objectives is to obtain measurements applicable to the development of models for better understanding of radiative processes in the atmosphere. We address this goal by building a three-dimensional (3D) characterization of the cloud structure and properties over the ARM Southern Great Plains (SGP). We take the approach of juxtaposing the cloud properties as retrieved from independent satellite and ground-based retrievals, and looking at the statistics of the cloud field properties. Once these retrievals are well understood, they will be used to populate the 3D characterization database. As a first step we determine the relationship between surface fractional sky cover and satellite viewing angle dependent cloud fraction (CF). We elaborate on the agreement intercomparing optical depth (OD) datasets from satellite and ground using available retrieval algorithms with relation to the CF, cloud height, multi-layer cloud presence, and solar zenith angle (SZA). For the SGP Central Facility, where output from the active remote sensing cloud layer (ARSCL) valueadded product (VAP) is available, we study the uncertainty of satellite estimated cloud heights and evaluate the impact of this uncertainty for radiative studies.
A layered abduction model of perception: Integrating bottom-up and top-down processing in a multi-sense agent
A layered-abduction model of perception is presented which unifies bottom-up and top-down processing in a single logical and information-processing framework. The process of interpreting the input from each sense is broken down into discrete layers of interpretation, where at each layer a best explanation hypothesis is formed of the data presented by the layer or layers below, with the help of information available laterally and from above. The formation of this hypothesis is treated as a problem of abductive inference, similar to diagnosis and theory formation. Thus this model brings a knowledge-based problem-solving approach to the analysis of perception, treating perception as a kind of compiled cognition. The bottom-up passing of information from layer to layer defines channels of information flow, which separate and converge in a specific way for any specific sense modality. Multi-modal perception occurs where channels converge from more than one sense. This model has not yet been implemented, though it is based on systems which have been successful in medical and mechanical diagnosis and medical test interpretation.
Microwave remote sensing of a two-layer random medium
A two-variable expansion technique is used to solve for the mean Green's. function from the Dyson equation under the nonlinear approximation. The Bethe-Salpeter equation then gives rise to a set of modified radiative transfer (MRT) equations which accommodate coherent effects essential to bounded media. It is found that the nonlinear approximation, instead of the more popular bilocal approximation, should be used for the case of bounded media. The two approximations yield identical results for unbounded media. The MRT equations are then solved for a two-layer random medium. The MRT equations give rise to simple and useful solutions which are applicable to both active and passive microwave remote sensing.
Radiative transfer theory for scattering by layered media
Remote sensing of brightness temperatures of a scattering medium composed of spherical scatterers beneath a homogeneous surface layer is studied by using Mie scattering functions. We illustrate the effects of a surface layer by plotting the brightness temperatures as functions of frequency and viewing angle for different layer thicknesses, dielectric constants, and fractional scattering volumes. It is found that the brightness temperature increases when the loss tangent of the surface layer is increased and when the fractional volume occupied by the scatterers is decreased. In the absence of a surface layer the brightness temperature is usually decreasing as a function of frequency. The presence of a homogeneous layer may cause the brightness temperature to increase with frequency. At all viewing angles the vertical polarization is brighter than the horizontal polarization.
Two-axis magnetic field sensor
A ferromagnetic thin-film based magnetic field sensor with first and second sensitive direction sensing structures each having a nonmagnetic intermediate layer with two major surfaces on opposite sides thereof having a magnetization reference layer on one and an anisotropic ferromagnetic material sensing layer on the other having a length in a selected length direction and a smaller width perpendicular thereto and parallel to the relatively fixed magnetization direction. The relatively fixed magnetization direction of said magnetization reference layer in each is oriented in substantially parallel to the substrate but substantially perpendicular to that of the other. An annealing process is used to form the desired magnetization directions.
Active microwave remote sensing of an anisotropic random medium layer
A two-layer anisotropic random medium model has been developed to study the active remote sensing of the earth. The dyadic Green's function for a two-layer anisotropic medium is developed and used in conjunction with the first-order Born approximation to calculate the backscattering coefficients. It is shown that strong cross-polarization occurs in the single scattering process and is indispensable in the interpretation of radar measurements of sea ice at different frequencies, polarizations, and viewing angles. The effects of anisotropy on the angular responses of backscattering coefficients are also illustrated.
A Melting Layer Model for Passive/Active Microwave Remote Sensing Applications: Simulation of TRMM Observations - Part 2
The one-dimensional, steady-state melting layer model developed in Part I of this study is used to calculate both the microphysical and radiative properties of melting precipitation, based upon the computed concentrations of snow and graupel just above the freezing level at applicable horizontal gridpoints of 3-dimensional cloud resolving model simulations. The modified 3-dimensional distributions of precipitation properties serve as input to radiative transfer calculations of upwelling radiances and radar extinction/reflectivities at the TRMM Microwave Imager (TMI) and Precipitation Radar (PR) frequencies, respectively. At the resolution of the cloud resolving model grids (approx. 1 km), upwelling radiances generally increase if mixed-phase precipitation is included in the model atmosphere. The magnitude of the increase depends upon the optical thickness of the cloud and precipitation, as well as the scattering characteristics of ice-phase precipitation aloft. Over the set of cloud resolving model simulations utilized in this study, maximum radiance increases of 43, 28, 18, and 10 K are simulated at 10.65, 19.35 GHz, 37.0, and 85.5 GHz, respectively. The impact of melting on TMI-measured radiances is determined not only by the physics of the melting particles but also by the horizontal extent of the melting precipitation, since the lower-frequency channels have footprints that extend over 10''s of kilometers. At TMI resolution, the maximum radiance increases are 16, 15, 12, and 9 K at the same frequencies. Simulated PR extinction and reflectivities in the melting layer can increase dramatically if mixed-phase precipitation is included, a result consistent with previous studies. Maximum increases of 0.46 (-2 dB) in extinction optical depth and 5 dBZ in reflectivity are simulated based upon the set of cloud resolving model simulations.
Remote sensing of ocean current boundary layer
There are no author-identified significant results in this report.
Remote sensing of ocean current boundary layer
There are no author-identified significant results in this report.
Remote sensing of ocean current boundary layer
The author has identified the following significant results. A time series of the Loop Current in the Gulf of Mexico, covering an annual cycle of growth, spreading, and decay, has been obtained in synchronization with ERTS-1. Computer enhanced images, which are necessary to extract useful oceanic information, show that the current can be observed either by color or sea state effects associated with the cyclonic boundary. The color effect relates to the spectral variations in the optical properties of the water and its suspended particles, and is studied by radiative transfer theory. Significant oceanic parameters identified are: the probability of forward scattering, and the ratio of scattering to total attenuation. Several spectra of upwelling diffuse light are computed as a function of the concentration of particles and yellow substance. These calculations compare favorably with experimental measurements and show that the ratio of channels method gives ambiguous interpretative results. These results are used to discuss features in images where surface measurements were obtained and are extended to tentative explanation in others.
Remote sensing of ocean current boundary layer
There are no author-identified significant results in this report.
Remote sensing of ocean current boundary layer
There are no author-identified significant results in this report.
Remote sensing of ocean current boundary layer
There are no author-identified significant results in this report.
Remote sensing of ocean current boundary layer
There are no author-identified significant results in this report.
Remote sensing of ocean current boundary layer
There are no author-identified significant results in this report.