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At least 19 records

Mapping vegetation types with the multiple spectral feature mapping algorithm in both emission and absorption

Vegetation covers a large portion of the Earth's land surface. Remotely sensing quantitative information from vegetation has proven difficult because in a broad sense, all vegetation is similar from a chemical viewpoint, and most healthy plants are green. Plant species are generally characterized by the leaf and flower or fruit morphology, not by remote sensing spectral signatures. But to the human eye, many plants show varying shades of green, so there is direct evidence for spectral differences between plant types. Quantifying these changes in a predictable manner has not been easy. The Clark spectral features mapping algorithm was applied to mapping spectral features in vegetation species.

Clark, Roger N.

An Example of Unsupervised Networks Kohonen's Self-Organizing Feature Map

Kohonen's self-organizing feature map belongs to a class of unsupervised artificial neural network commonly referred to as topographic maps. It serves two purposes, the quantization and dimensionality reduction of date. A short description of its history and its biological context is given. We show that the inherent classification properties of the feature map make it a suitable candidate for solving the classification task in power system areas like load forecasting, fault diagnosis and security assessment.

Kohonen Feature Map

Mapping the mineralogy and lithology of Canyonlands, Utah with imaging spectrometer data and the multiple spectral feature mapping algorithm

The sedimentary sections exposed in the Canyonlands and Arches National Parks region of Utah (generally referred to as 'Canyonlands') consist of sandstones, shales, limestones, and conglomerates. Reflectance spectra of weathered surfaces of rocks from these areas show two components: (1) variations in spectrally detectable mineralogy, and (2) variations in the relative ratios of the absorption bands between minerals. Both types of information can be used together to map each major lithology and the Clark spectral features mapping algorithm is applied to do the job.

Clark, Roger N.

Control of the NASA Langley 16-Foot Transonic Tunnel with the Self-Organizing Feature Map

A predictive, multiple model control strategy is developed based on an ensemble of local linear models of the nonlinear system dynamics for a transonic wind tunnel. The local linear models are estimated directly from the weights of a Self Organizing Feature Map (SOFM). Local linear modeling of nonlinear autonomous systems with the SOFM is extended to a control framework where the modeled system is nonautonomous, driven by an exogenous input. This extension to a control framework is based on the consideration of a finite number of subregions in the control space. Multiple self organizing feature maps collectively model the global response of the wind tunnel to a finite set of representative prototype controls. These prototype controls partition the control space and incorporate experimental knowledge gained from decades of operation. Each SOFM models the combination of the tunnel with one of the representative controls, over the entire range of operation. The SOFM based linear models are used to predict the tunnel response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal. Each SOFM provides a codebook representation of the tunnel dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the minimization of a similarity metric which is the essence of the self organizing feature of the map. Thus, the SOFM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme than selects the best available model for the applied control. Experimental results of controlling the wind tunnel, with the proposed method, during operational runs where strict research requirements on the control of the Mach number were met, are presented. Comparison to similar runs under the same conditions with the tunnel controlled by either the existing controller or an expert operator indicate the superiority of the method.

Motter, Mark A.

Understanding COMPTEL Al-26 1.8 MeV map features

The COMPTEL sky map of the 1.8 MeV line emission from Al-26 shows an extended diffuse distribution along the Galactic plane with a peculiar large scale asymmetry about the Galactic center (GC) and a clumpy structure with several noticeable hot spots. The most prominent hot spot at the GC appears shifted to positive longitude by about 2 deg. Nearby supernova remnants or Wolf-Rayet stars are plausible explanations for individual hot spots such as in the Vela region. We show that the global asymmetry and most hot spots can be understood by a more general model: the Al-26 sources are confined in the spiral arms of our Galaxy, and coagent star formation is responsible for additional clumpiness. The off-centered GC hot spot is probably due to the observed asymmetrically distributed circumnuclear molecular gas interacting with a central stellar bar, whose existence has been inferred from IR observations.

Chen, Wan

The 3.3 micron emission feature: Map of the galactic disk, 10 deg less than 1 less than 35 deg, - 6 deg less than b less than 6 deg

The 3.3 micron aromatic feature has been detected in the diffuse galactic emission with the AROME balloon-borne instrument. The results are presented in the form of an map of the 3.3 micron feature's intensity. The AROME instrument consists in a Cassegrain telescope with wobbling secondary mirrors and a liquid/solid nitrogen cooled photometer. The instrumental output is modified by the impulse response of the system. So the galactic surface brightness was restored in Fourier space by an inverse optimal filtering. The map of the feature's intensity is presented for a region of galactic coordinates. All the known H II giant molecular cloud complexes are visible in the 3.3 micron feature emission showing a good correlation with the infrared dust emission.

Giard, Martin

Sea-Ice Feature Mapping using JERS-1 Imagery

JERS-1 SAR and OPS imagery are examined in combination with other data sets to investigate the utility of the JERS-1 sensors for mapping fine-scale sea ice conditions. Combining ERS-1 C band and JERS-1 L band SAR aids in discriminating multiyear and first-year ice. Analysis of OPS imagery for a field site in the Canadian Archipelago highlights the advantages of OPS's high spatial and spectral resolution for mapping ice structure, melt pond distribution, and surface albedo.

Maslanik, James

New Geologic Map of the Argyre Region of Mars: Deciphering the Geologic History Through Mars Global Surveyor, Mars Odyssey, and Mars Express Data

The primary objective of the mapping effort is to produce a geologic map of the Argyre basin and surrounding region at 1:5,000,000 scale in both digital and print formats that will detail the stratigraphic and crosscutting relations among rock materials and landforms (30 deg. S to 65 deg. S, 290 deg. E to 340 deg E). There has not been a detailed geologic map produced of the Argyre region since the Viking-era mapping investigation. The mapping tasks include stratigraphic mapping, crater counting, feature mapping, quantitative landform analysis, and spectroscopic/ stratigraphic investigation feature mapping. The regional geologic mapping investigation includes the Argyre basin floor and rim materials, the transition zone that straddles the Thaumasia plateau, which includes Argyre impactrelated modification, and the southeast margin of the Thaumasia plateau using important new data sets from the Mars Global Surveyor, Mars Odyssey, Mars Express, and Mars Reconnaissance Orbiter. The geologic information unfolded by this new mapping project will be useful to the community for constraining the regional geology, paleohydrology, and paleoclimate, which includes but is not limited to the assessment of: (1) whether the Argyre basin contained lakes, (2) the extent of reported flooding and glaciation, (3) existing interpretations of the origin of the narrow ridges located in the southeast part of the basin floor, and (4) the extent of Argyre-related tectonism and its influence on the surrounding regions.

Dohm, J. M.

Toward autonomous driving: The CMU Navlab. I - Perception

The Navlab project, which seeks to build an autonomous robot that can operate in a realistic environment with bad weather, bad lighting, and bad or changing roads, is discussed. The perception techniques developed for the Navlab include road-following techniques using color classification and neural nets. These are discussed with reference to three road-following systems, SCARF, YARF, and ALVINN. Three-dimensional perception using three types of terrain representation (obstacle maps, terrain feature maps, and high-resolution maps) is examined. It is noted that perception continues to be an obstacle in developing autonomous vehicles.

Thorpe, Charles

Small-scale imagery: A useful tool for mapping geological features in the Texas Gulf Coastal plain

A sample of satellite imagery includes photographs and multispectral scanner imagery from the Apollo, LANDSAT, and Skylab spacecraft over an area west of Houston, Texas. Large circular features and lineaments can readily be mapped. One of the circular features identified by drainage, vegetation, and soil-tone anomalies, occurs in Fort Bend County, Texas, and covers an area about 25 miles in diameter. Another circular feature lies to the north, immediately west of Houston, and is about 15 miles in diameter. These features represent the surface expression of deeply-buried positive structures. It is recommended that regional geological studies begin with photointerpretations of high-altitude aircraft and synoptic space imagery, space imagery provides the synoptic view of rapid evaluation of large-scale features, and, at enlarged scales, the resolution required for detailed study of selected areas of structures.

Amsbury, D. L.

Interpretable and flexible non-intrusive reduced-order models using reproducing kernel Hilbert spaces

This paper develops an interpretable, non-intrusive reduced-order modeling technique using regularized kernel interpolation. Existing non-intrusive approaches approximate the dynamics of a reduced-order model (ROM) by solving a data-driven least-squares regression problem for low-dimensional matrix operators. Our approach instead leverages regularized kernel interpolation, which yields an optimal approximation of the ROM dynamics from a user-defined reproducing kernel Hilbert space. We show that our kernel-based approach can produce interpretable ROMs whose structure mirrors full-order model structure by embedding judiciously chosen feature maps into the kernel. The approach is flexible and allows a combination of informed structure through feature maps and closure terms via more general nonlinear terms in the kernel. We also derive a computable a posteriori error bound that combines standard error estimates for intrusive projection-based ROMs and kernel interpolants. In conclusion, the approach is demonstrated in several numerical experiments that include comparisons to operator inference using both proper orthogonal decomposition and quadratic manifold dimension reduction.

Data-driven model reduction

Mapping electrodynamic features of the high-latitude ionosphere from localized observations - Technique

This paper describes a novel procedure for mapping high-latitude electric fields and currents and their associated magnetic variations, using sets of localized observational data derived from different types of measurements. The technique provides a formalism for incorporating simultaneously such different classes of data as electric fields from radars and satellites, electric currents from radars, and magnetic perturbations at the ground and at satellite heights; the technique also uses available statistical information on the averages and variances of electrodynamic fields. The technique provides a more rigorous way of quantitatively estimating high-latitude electric field and current patterns than other methods and has a capability to quantify the errors in the mapped fields, based on the distribution of available data, their errors, and the statistical variances of the fields. The technique is illustrated by an application to a substorm which was analyzed by Kamide et al. (1982) by an earlier technique.

Richmond, A. D.

Spectral Ratio Imaging with Hyperion Satellite Data for Geological Mapping

Since the advent of LANDSAT I in 1972, many different multispectral satellites have been orbited by the U.S. and other countries. These satellites have varied from 4 spectral bands in LANDSAT I to 14 spectral bands in the ASTER sensor aboard the TERRA space platform. Hyperion is a relatively new hyperspectral sensor with over 220 spectral bands. The huge increase in the number of spectral bands offers a substantial challenge to computers and analysts alike when it comes to the task of mapping features on the basis of chemical composition, especially if little or no ground truth is available beforehand from the area being mapped. One approach is the theoretical approach of the modeler, where all extraneous information (atmospheric attenuation, sensor electronic gain and offset, etc.) is subtracted off and divided out, and laboratory (or field) spectra of materials are used as training sets to map features in the scene of similar composition. This approach is very difficult to keep accurate because of variations in the atmosphere, solar illumination, and sensor electronic gain and offset that are not always perfectly recorded or accounted for. For instance, to apply laboratory or field spectra of materials as data sets from the theoretical approach, the header information of the files must reflect the correct, up-to-date sensor electronic gain and offset and the analyst must pick the exact atmospheric model that is appropriate for the day of data collection in order for classification procedures to accurately match pixels in the scene with the laboratory or field spectrum of a desired target on the basis of the hyperspectral data. The modeling process is so complex that it is difficult to tell when it is operating well or determine how to fix it when it is incorrect. Recently RSI has announced that the latest version of their ENVI software package is not performing atmospheric corrections correctly with the FLAASH atmospheric model. It took a long time to determine that it was wrong, and may take an equally long time (or longer) to fix.

Vincent, Robert K.

Communications and control for electric power systems: Power flow classification for static security assessment

This report investigates the classification of power system states using an artificial neural network model, Kohonen's self-organizing feature map. The ultimate goal of this classification is to assess power system static security in real-time. Kohonen's self-organizing feature map is an unsupervised neural network which maps N-dimensional input vectors to an array of M neurons. After learning, the synaptic weight vectors exhibit a topological organization which represents the relationship between the vectors of the training set. This learning is unsupervised, which means that the number and size of the classes are not specified beforehand. In the application developed in this report, the input vectors used as the training set are generated by off-line load-flow simulations. The learning algorithm and the results of the organization are discussed.

Niebur, D.

Mapping soil features from multispectral scanner data

In being able to identify quickly gross variations in soil features, the computer-aided classification of multispectral scanner data can be an effective aid to soil surveying. Variations in soil tone are easily seen as well as variations in features related to soil tone, e.g., drainage patterns and organic matter content. Changes in surface texture also affect the reflectance properties of soils. Inasmuch as conventional soil classes are based on both surface and subsurface soil characteristics, the technique described here can be expected only to augment and not replace traditional soil mapping.

Kristof, S. J.

Evaluation of aircraft microwave data for locating zones for well stimulation and enhanced gas recovery

Imaging radar was evaluated as an adjunct to conventional petroleum exploration techniques, especially linear mapping. Linear features were mapped from several remote sensor data sources including stereo photography, enhanced LANDSAT imagery, SLAR radar imagery, enhanced SAR radar imagery, and SAR radar/LANDSAT combinations. Linear feature maps were compared with surface joint data, subsurface and geophysical data, and gas production in the Arkansas part of the Arkoma basin. The best LANDSAT enhanced product for linear detection was found to be a winter scene, band 7, uniform distribution stretch. Of the individual SAR data products, the VH (cross polarized) SAR radar mosaic provides for detection of most linears; however, none of the SAR enhancements is significantly better than the others. Radar/LANDSAT merges may provide better linear detection than a single sensor mapping mode, but because of operator variability, the results are inconclusive. Radar/LANDSAT combinations appear promising as an optimum linear mapping technique, if the advantages and disadvantages of each remote sensor are considered.

Macdonald, H.

An analysis of a satellite multibeam altimeter

Since the GEOS-3 and SEASAT-1 radar altimeters measured altitude over a narrow swath along the satellite subtrack, ocean current and mesoscale feature maps could only be generated after a large number of satellite revolutions. The present paper analyzes a new multibeam altimeter technique that has the potential to cover wide swaths. The multibeam altimeter uses two antenna elements, simple parabolic dishes with offset feeds, deployed cross-track on singly hinged booms into a fixed measurement geometry to generate an interferometer pattern over the desired swath extent. Range gating allows the isolation of a single interferometeric lobe, and the desired altitude measurements are extracted by using a modified altitude tracker design. Implementing this sensor on future altimetry missions would allow the timely generation of ocean current and mesoscale feature maps for the first time.

Bush, G. B.