Relevant bibliographies by topics / Spectral mapping

Academic literature on the topic 'Spectral mapping'

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Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Spectral mapping"

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Müller, Vladimir, and Aljoša Peperko. "Lower spectral radius and spectral mapping theorem for suprema preserving mappings." Discrete & Continuous Dynamical Systems - A 38, no. 8 (2018): 4117–32. http://dx.doi.org/10.3934/dcds.2018179.

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González, M., and V. M. Onieva. "On the spectral mapping theorem for essential spectra." Publicacions Matemàtiques 29 (November 1, 1985): 105–10. http://dx.doi.org/10.5565/publmat_292385_05.

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Verma, R. U., and S. S. Jou. "Some spectral inclusions onD-commuting systems." International Journal of Mathematics and Mathematical Sciences 13, no. 1 (1990): 115–20. http://dx.doi.org/10.1155/s016117129000014x.

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Pe’eri, Oren, Michael A. Golub, and Menachem Nathan. "Mapping of spectral signatures with snapshot spectral imaging." Applied Optics 56, no. 15 (May 12, 2017): 4309. http://dx.doi.org/10.1364/ao.56.004309.

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Aiena, Pietro, and Maria Teresa Biondi. "Some spectral mapping theorems through local spectral theory." Rendiconti del Circolo Matematico di Palermo 53, no. 2 (June 2004): 165–84. http://dx.doi.org/10.1007/bf02872869.

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Brodský, L., A. Klement, V. Penížek, R. Kodešová, and L. Borůvka. "Building soil spectral library of the Czech soils for quantitative digital soil mapping." Soil and Water Research 6, No. 4 (November 28, 2011): 165–72. http://dx.doi.org/10.17221/24/2011-swr.

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  Spectral libraries are the data archives of spectral signatures measured on natural and/or man-made materials. Here, the objective is to build a soil spectral library of the Czech soils (SSL-CZ). Further on, the overall aim is to apply diffuse reflectance spectroscopy as a tool for digital soil mapping. An inevitable part of the library is a metadata database that stores the corresponding auxiliary information on the soils: type of material (soil, parent material), sample preparation, location of the sample with geographic coordinates, soil classification, morphological features, soil laboratory measurements – chemical, physical, and potential biological properties, geophysical features of and climatological information on the sample location. The metadata database consists of seven general tables (General, Spatial, Soil class, Environmental, Auxiliary, Analytical and Spectra) relationally linked together. The stored information allows for a wide range of analyses and for modelling developments of digital soil mapping applications. An example of partial least-square regression (PLSR) modelling for soil pH and clay content with 0.84 and 0.68 coefficients of determination is provided on the subset of the collected data. Currently, the SSL-CZ database contains more than 500 records in the first phase of development. Spectral reflectance signatures are stored in the range of 350 to 2500 nm with a step of 1 nm measured by ASD FieldSpec 3. The soil spectral library developed is fully compatible with Global Soil Spectral Library (Soil Spectroscopy Group).
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Mazur, T., and M. Skwarczyński. "Spectral properties of holomorphic automorphism with fixed point." Glasgow Mathematical Journal 28, no. 1 (January 1986): 25–30. http://dx.doi.org/10.1017/s0017089500006297.

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The Hilbert space methods in the theory of biholomorphic mappings were applied and developed by S. Bergman [1, 2]. In this approach the central role is played by the Hilbert space L2H(D) consisting of all functions which are square integrable and holomorphic in a domain D ⊂ ℂN. A biholomorphic mapping φ:D ⃗ G induces the unitary mapping Uφ:L2H(G) ⃗ L2H(D) defined by the formulaHere ∂φ/∂z denotes the complex Jacobian of φ. The mapping Uϕ is useful, since it permits to replace a problem for D by a problem for its biholomorphic image G (see for example [11], [13]). When ϕ is an automorphism of D we obtain a unitary operator Uϕ on L2H(D).
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Leahy, J. P., and T. W. B. Muxlow. "Spectral Mapping of Classical Double Radio Sources." Symposium - International Astronomical Union 199 (2002): 179–88. http://dx.doi.org/10.1017/s0074180900168834.

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We review the evidence that spectral curvature in the extended emission of radio galaxies is caused by synchrotron losses, and that the spatial variation can be interpreted to yield ages and expansion speeds. One of the biggest worries has been the true value of the magnetic field, but X-ray detections of inverse-Compton radiation are beginning to suggest that “minimum energy” estimates are remarkably accurate. A critical test is to compare model and observed spectra over a broad frequency range; to date this has has only been done for Cygnus A, and the results proved controversial. Here we discuss several more cases and begin to draw some general conclusions.Hotspots are usually well fitted by continuous injection models, as expected. In two cases the implied injection index is flatter than 0.5, too flat to be produced by standard Fermi acceleration in a non-relativistic shock. The bridge spectra are reasonably fitted by single-burst models, but in some objects the injection index is not constant across the lobes, showing instead a tendency to steepen in the inner bridge, where the break frequencies are lowest. The true spectral shape may be a more gradual curve than the standard models, possibly because of mixing of electron populations with different ages. Our results are limited by the inaccuracy of the absolute flux density scale, especially at low frequencies, and a fresh attack on the flux scale would be timely.
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Tsutsumi, Shohei, Mitchell R. Rosen, and Roy S. Berns. "Spectral Gamut Mapping using LabPQR." Journal of Imaging Science and Technology 51, no. 6 (2007): 473. http://dx.doi.org/10.2352/j.imagingsci.technol.(2007)51:6(473).

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HABA, Kazumoto, Wataru HOTTA, Akihito HATA, Kazuaki WATANABE, and Muneo HORI. "SPECTRAL STOCHASTIC RETURN MAPPING ALGORITHM." Journal of Japan Society of Civil Engineers, Ser. A2 (Applied Mechanics (AM)) 73, no. 1 (2017): 34–45. http://dx.doi.org/10.2208/jscejam.73.34.

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Dissertations / Theses on the topic "Spectral mapping"

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Cannon, Robert William. "Automated Spectral Identification of Materials using Spectral Identity Mapping." Cleveland State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=csu1377031729.

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Elling, Volker Wilhelm. "A spectral method for mapping dataflow graphs." Thesis, Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/8161.

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Blanchette, Damon Arthur. "Adaptive Spectral Mapping for Real-Time Dispersive Refraction." Digital WPI, 2012. https://digitalcommons.wpi.edu/etd-theses/110.

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Spectral rendering, or the synthesis of images by taking into account the wavelengths of light, allows effects otherwise impossible with other methods. One of these effects is dispersion, the phenomenon that creates a rainbow when white light shines through a prism. Spectral rendering has previously remained in the realm of off-line rendering (with a few exceptions) due to the extensive computation required to keep track of individual light wavelengths. Caustics, the focusing and de-focusing of light through a refractive medium, can be interpreted as a special case of dispersion where all the wavelengths travel together. This thesis extends Adaptive Caustic Mapping, a previously proposed caustics mapping algorithm, to handle spectral dispersion. Because ACM can display caustics in real-time, it is quite amenable to be extended to handle the more general case of dispersion. A method is presented that runs in screen-space and is fast enough to display plausible dispersion phenomena in real-time at interactive frame rates.
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Earle, Alissa M. "Spectral mapping and long-term seasonal evolution of Pluto." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117915.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 169-186).
NASA's New Horizons mission has provided a wealth of new data about the Pluto system, including detailed surface geology and volatile distribution maps revealing striking latitudinal and longitudinal variations. We begin by studying the methane distribution and surface colors using data from New Horizons' Ralph/MVIC instrument. From this study we find that Pluto's equatorial region shows a broader diversity of terrains and more stark longitudinal contrasts than the more homogeneous north polar region. Pluto's south polar region is currently in constant shadow and thus was not observed by New Horizons. We consider how this diversity formed and survived in the context of Pluto's extreme Milancovid cycles and resultant "super seasons". Over timescales of roughly 3 million years Pluto's obliquity varies by 23 degrees (between 103 degrees and 126 degrees) while its longitude of perihelion regresses. This pair of cycles create "super season" epochs where one pole experiences a short intense summer and long winter in constant darkness, while the other experiences a short winter and much longer, but less intense summer. Through thermal modeling and volatile sublimation and deposition modeling we determined that Pluto's high obliquity creates conditions at its equator that favor albedo contrast and can support them on million year timescales more effectively than Pluto's polar regions can. Finally, we look ahead to a possible next step in small body spacecraft exploration, a study of Apophis during its 2029 close approach to Earth. Since the earlier portion of this thesis focused on the encounter, data collection, and scientific analysis portion of a spacecraft mission (New Horizons), we go full circle by exploring the early stage of the
by Alissa M. Earle.
Ph. D.
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Spalt, Taylor Brooke. "Constrained Spectral Conditioning for the Spatial Mapping of Sound." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/70868.

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In aeroacoustic experiments of aircraft models and/or components, arrays of microphones are utilized to spatially isolate distinct sources and mitigate interfering noise which contaminates single-microphone measurements. Array measurements are still biased by interfering noise which is coherent over the spatial array aperture. When interfering noise is accounted for, existing algorithms which aim to both spatially isolate distinct sources and determine their individual levels as measured by the array are complex and require assumptions about the nature of the sound field. This work develops a processing scheme which uses spatially-defined phase constraints to remove correlated, interfering noise at the single-channel level. This is achieved through a merger of Conditioned Spectral Analysis (CSA) and the Generalized Sidelobe Canceller (GSC). A cross-spectral, frequency-domain filter is created using the GSC methodology to edit the CSA formulation. The only constraint needed is the user-defined, relative phase difference between the channel being filtered and the reference channel used for filtering. This process, titled Constrained Spectral Conditioning (CSC), produces single-channel Fourier Transform estimates of signals which satisfy the user-defined phase differences. In a spatial sound field mapping context, CSC produces sub-datasets derived from the original which estimate the signal characteristics from distinct locations in space. Because single-channel Fourier Transforms are produced, CSC's outputs could theoretically be used as inputs to many existing algorithms. As an example, data-independent, frequency-domain beamforming (FDBF) using CSC's outputs is shown to exhibit finer spatial resolution and lower sidelobe levels than FDBF using the original, unmodified dataset. However, these improvements decrease with Signal-to-Noise Ratio (SNR), and CSC's quantitative accuracy is dependent upon accurate modeling of the sound propagation and inter-source coherence if multiple and/or distributed sources are measured. In order to demonstrate systematic spatial sound mapping using CSC, it is embedded into the CLEAN algorithm which is then titled CLEAN-CSC. Simulated data analysis indicates that CLEAN-CSC is biased towards the mapping and energy allocation of relatively stronger sources in the field, which limits its ability to identify and estimate the level of relatively weaker sources. It is also shown that CLEAN-CSC underestimates the true integrated levels of sources in the field and exhibits higher-than-true peak source levels, and these effects increase and decrease respectively with increasing frequency. Five independent scaling methods are proposed for correcting the CLEAN-CSC total integrated output levels, each with their own assumptions about the sound field being measured. As the entire output map is scaled, these do not account for relative source level errors that may exist. Results from two airfoil tests conducted in NASA Langley's Quiet Flow Facility show that CLEAN-CSC exhibits less map noise than CLEAN yet more segmented spatial sound distributions and lower integrated source levels. However, using the same source propagation model that CLEAN assumes, the scaled CLEAN-CSC integrated source levels are brought into closer agreement with those obtained with CLEAN.
Ph. D.
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Behjat, Hamid. "Statistical Parametric Mapping of fMRI data using Spectral Graph Wavelets." Thesis, Linköpings universitet, Medicinsk informatik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-81143.

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In typical statistical parametric mapping (SPM) of fMRI data, the functional data are pre-smoothed using a Gaussian kernel to reduce noise at the cost of losing spatial specificity. Wavelet approaches have been incorporated in such analysis by enabling an efficient representation of the underlying brain activity through spatial transformation of the original, un-smoothed data; a successful framework is the wavelet-based statistical parametric mapping (WSPM) which enables integrated wavelet processing and spatial statistical testing. However, in using the conventional wavelets, the functional data are considered to lie on a regular Euclidean space, which is far from reality, since the underlying signal lies within the complex, non rectangular domain of the cerebral cortex. Thus, using wavelets that function on more complex domains such as a graph holds promise. The aim of the current project has been to integrate a recently developed spectral graph wavelet transform as an advanced transformation for fMRI brain data into the WSPM framework. We introduce the design of suitable weighted and un-weighted graphs which are defined based on the convoluted structure of the cerebral cortex. An optimal design of spatially localized spectral graph wavelet frames suitable for the designed large scale graphs is introduced. We have evaluated the proposed graph approach for fMRI analysis on both simulated as well as real data. The results show a superior performance in detecting fine structured, spatially localized activation maps compared to the use of conventional wavelets, as well as normal SPM. The approach is implemented in an SPM compatible manner, and is included as an extension to the WSPM toolbox for SPM.
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Alvarez, Manuela. "Mapping forest habitats in protected areas by integrating LiDAR and SPOT Multispectral Data." Thesis, KTH, Geoinformatik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189199.

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KNAS (Continuous Habitat Mapping of Protected Areas) is a Metria AB project that produces vegetation and habitat mapping in protected areas in Sweden. Vegetation and habitat mapping is challenging due to its heterogeneity, spatial variability and complex vertical and horizontal structure. Traditionally, multispectral data is used due to its ability to give information about horizontal structure of vegetation. LiDAR data contains information about vertical structure of vegetation, and therefore contributes to improve classification accuracy when used together with spectral data. The objectives of this study are to integrate LiDAR and multispectral data for KNAS and to determine the contribution of LiDAR data to the classification accuracy. To achieve these goals, two object-based classification schemes are proposed and compared: a spectral classification scheme and a spectral-LiDAR classification scheme. Spectral data consists of four SPOT-5 bands acquired in 2005 and 2006. Spectral-LiDAR includes the same four spectral bands from SPOT-5 and nine LiDAR-derived layers produced from NH point cloud data from airborne laser scanning acquired in 2011 and 2012 from The Swedish Mapping, Cadastral and Land Registration Authority. Processing of point cloud data includes: filtering, buffer and tiles creation, height normalization and rasterization. Due to the complexity of KNAS production, classification schemes are based on a simplified KNAS workflow and a selection of KNAS forest classes. Classification schemes include: segmentation, database creation, training and validation areas collection, SVM classification and accuracy assessment. Spectral-LiDAR data fusion is performed during segmentation in eCognition. Results from segmentation are used to build a database with segmented objects, and mean values of spectral or spectral-LiDAR data. Databases are used in Matlab to perform SVM classification with cross validation. Cross validation accuracy, overall accuracy, kappa coefficient, producer’s and user’s accuracy are computed. Training and validation areas are common to both classification schemes. Results show an improvement in overall classification accuracy for spectral-LiDAR classification scheme, compared to spectral classification scheme. Improvements of 21.9 %, 11.0 % and 21.1 % are obtained for the study areas of Linköping, Örnsköldsvik and Vilhelmina respectively.
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Stanislavova, Milena. "Spectral mapping theorems and invariant manifolds for infinite-dimensional Hamiltonian systems /." free to MU campus, to others for purchase, 2000. http://wwwlib.umi.com/cr/mo/fullcit?p9988702.

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Praeger, Matthew. "Development and spatio-spectral mapping of a capillary high harmonic source." Thesis, University of Southampton, 2008. https://eprints.soton.ac.uk/66192/.

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This work describes the development and operation of a capillary based High Harmonic Generation (HHG) system. Using this system a coherent beam of soft x-rays is generated, studied and applied. A series of experiments was then undertaken in order to deepen our knowledge of the HHG process and to optimise the performance of the source. Notable contributions made to the field are: A novel laser mode quality measuring device. (Laser mode quality strongly affects the efficiency of the capillary launch). A study of the spectral output of the system as a function of gas pressure, laser power, and laser spectral phase. An analysis technique for recovering spatially-resolved spectral information about a beam by studying the Fresnel diffraction pattern produced at an array of apertures. A study of pulse compression using cascaded quadratic nonlinearity for spectral broadening.
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Zhao, Yonghui. "Image segmentation and pigment mapping of cultural heritage based on spectral imaging /." Online version of thesis, 2008. http://hdl.handle.net/1850/7050.

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Books on the topic "Spectral mapping"

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Harte, Robin. Spectral Mapping Theorems. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05648-7.

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Overman, Andrea L. Mapping implicit spectral methods to distributed memory architectures. Hampton, Va: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1991.

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Lemeshewsky, George. Land cover classification from SPOT multispectral and panchromatic images using neural network classification of fuzzy clustered spectral and textural features. [Reston, VA]: U.S. Geological Survey, 1995.

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Bemigisha, Jane. Spectral and human sensors: Hyperspectral remote sensing and participatory GIS for mapping livestock grazing intensity and vegetation in transhumant Mediterranean Conservation areas. Wageningen: Wageningen University, 2008.

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Ford, Gary E. Landsat D thematic mapper image dimensionality reduction and geometric correction accuracy: Final report. [Washington, DC: National Aeronautics and Space Administration, 1987.

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Substitution dynamical systems, spectral analysis. 2nd ed. Heidelberg: Springer-Verlag, 2010.

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Yurko, V. A. Method of spectral mappings in the inverse problem theory. Utrecht: VSP, 2002.

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Isoscapes: Understanding movement, pattern, and process on earth through isotope mapping. Dordrecht: Springer, 2010.

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Signatures spectrales de roches en milieu tempéré: Valeurs réelles et valeurs perçues par le satellite. Orléans, France: Editions du BRGM, 1989.

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Landsat-4 Science Characterization Early Results Symposium (1983 Greenbelt, Md.). Landsat-4 science characterization early results: Proceedings of the Landsat-4 Science Characterization Early Results Symposium, February 22-24, 1983, held at NASA Goddard Space Flight Center, Greenbelt, Maryland. Edited by Barker John L, United States. National Aeronautics and Space Administration, and Landsat-4 Early Results Symposium (1983 : Greenbelt, Md.). Washington, D.C: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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Book chapters on the topic "Spectral mapping"

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van Neerven, Jan. "Spectral mapping theorems." In The Asymptotic Behaviour of Semigroups of Linear Operators, 25–71. Basel: Birkhäuser Basel, 1996. http://dx.doi.org/10.1007/978-3-0348-9206-3_2.

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Fašanga, Eva. "Spectral Mapping Theorems and Spectral Space-Independence." In Evolution Equations: Applications to Physics, Industry, Life Sciences and Economics, 157–68. Basel: Birkhäuser Basel, 2003. http://dx.doi.org/10.1007/978-3-0348-8085-5_12.

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Livšic, M. S., N. Kravitsky, A. S. Markus, and V. Vinnikov. "Joint Spectrum and the Spectral Mapping Theorem." In Theory of Commuting Nonselfadjoint Operators, 73–80. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-015-8561-3_5.

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Harte, Robin. "Erratum to: Spectral Mapping Theorems." In SpringerBriefs in Mathematics, E1. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05648-7_7.

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YENTSCH, CHARLES S., and DAVID A. PHINNEY. "Fluorescence Spectral Signatures for Studies of Marine Phytoplankton." In Mapping Strategies in Chemical Oceanography, 259–74. Washington, D.C.: American Chemical Society, 1985. http://dx.doi.org/10.1021/ba-1985-0209.ch013.

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Kumar, G. Krishna, and S. H. Kulkarni. "An Analogue of the Spectral Mapping Theorem for Condition Spectrum." In Concrete Operators, Spectral Theory, Operators in Harmonic Analysis and Approximation, 299–316. Basel: Springer Basel, 2013. http://dx.doi.org/10.1007/978-3-0348-0648-0_19.

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Trentin, Edmondo, Diego Giuliani, and Cesare Furlanello. "Spectral Mapping: a Comparison of Connectionist Approaches." In Neural Nets WIRN VIETRI-96, 270–77. London: Springer London, 1997. http://dx.doi.org/10.1007/978-1-4471-0951-8_31.

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Schmidt, Michael, and Peter Scarth. "Spectral Mixture Analysis for Ground-Cover Mapping." In Lecture Notes in Geoinformation and Cartography, 349–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-93962-7_27.

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Rudol, K. "Spectral Mapping Theorems for Analytic Functional Calculi." In Advances in Invariant Subspaces and Other Results of Operator Theory, 331–40. Basel: Birkhäuser Basel, 1986. http://dx.doi.org/10.1007/978-3-0348-7698-8_23.

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Einsiedler, Manfred, and Thomas Ward. "Uniform Boundedness and the Open Mapping Theorem." In Functional Analysis, Spectral Theory, and Applications, 121–33. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58540-6_4.

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Conference papers on the topic "Spectral mapping"

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Dosiev, Anar. "Spectral mapping framework." In Topological Algebras, their Applications, and Related Topics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2005. http://dx.doi.org/10.4064/bc67-0-13.

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Rosen, Mitchell R., and Maxim W. Derhak. "Spectral gamuts and spectral gamut mapping." In Electronic Imaging 2006, edited by Mitchell R. Rosen, Francisco H. Imai, and Shoji Tominaga. SPIE, 2006. http://dx.doi.org/10.1117/12.651191.

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Laake, Andreas. "Structural mapping with spectral attributes." In SEG Technical Program Expanded Abstracts 2012. Society of Exploration Geophysicists, 2012. http://dx.doi.org/10.1190/segam2012-0435.1.

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Xu, Xiao-Hua, Ping He, and Ling Chen. "Learning spectral graph mapping for classification." In 2010 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2010. http://dx.doi.org/10.1109/icmlc.2010.5580573.

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Han, Kun, Yuxuan Wang, and DeLiang Wang. "Learning spectral mapping for speech dereverberation." In ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2014. http://dx.doi.org/10.1109/icassp.2014.6854479.

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Pfingsthorn, Max, Andreas Birk, Sören Schwertfeger, Heiko Bülow, and Kaustubh Pathak. "Maximum likelihood mapping with spectral image registration." In 2010 IEEE International Conference on Robotics and Automation (ICRA 2010). IEEE, 2010. http://dx.doi.org/10.1109/robot.2010.5509366.

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Ryan, Conor J., Dylan D. Ross, Janusz Murakowski, J. Garrett Schneider, Dennis W. Prather, and Christopher A. Schuetz. "k-Space Tomography for Spatial-Spectral Mapping." In 2018 IEEE Research and Applications of Photonics In Defense Conference (RAPID). IEEE, 2018. http://dx.doi.org/10.1109/rapid.2018.8508996.

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Yathigiri, Anisha, Meenalatha Bathula, Susmitha Kothapalli, Susmitha Vekkot, and Shikha Tripathi. "Voice transformation using pitch and spectral mapping." In 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2017. http://dx.doi.org/10.1109/icacci.2017.8126060.

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Ding, Chao, Hong Yao, Xingzhao Peng, and Haomin Li. "Fuzzy community-detection algorithm on spectral mapping." In 2013 3rd International Conference on Computer Science and Network Technology (ICCSNT). IEEE, 2013. http://dx.doi.org/10.1109/iccsnt.2013.6967132.

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Brunskill, Emma, Thomas Kollar, and Nicholas Roy. "Topological mapping using spectral clustering and classification." In 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2007. http://dx.doi.org/10.1109/iros.2007.4399611.

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Reports on the topic "Spectral mapping"

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Hendrickson, B., and R. Leland. An improved spectral graph partitioning algorithm for mapping parallel computations. Office of Scientific and Technical Information (OSTI), September 1992. http://dx.doi.org/10.2172/6970738.

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Yan, Long. Metabolic Mapping of Breast Cancer with Multiphoton Spectral and Lifetime Imaging. Fort Belvoir, VA: Defense Technical Information Center, March 2008. http://dx.doi.org/10.21236/ada493646.

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Yan, Long. Metabolic Mapping of Breast Cancer with Multiphoton Spectral and Lifetime Imaging. Fort Belvoir, VA: Defense Technical Information Center, March 2007. http://dx.doi.org/10.21236/ada469761.

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Thomas, Donald M., Barry R. Lienert, Erin L. Wallin, and Erika Gasperikova. Spectral SP: A New Approach to Mapping Reservoir Flow and Permeability. Office of Scientific and Technical Information (OSTI), May 2014. http://dx.doi.org/10.2172/1345903.

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Staenz, K., C. Nadeau, J. Secker, and P. Budkewitsch. Spectral Unmixing Applied to Vegetated Environments in the Canadian Arctic for Mineral Mapping. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2000. http://dx.doi.org/10.4095/219649.

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Stellman, Christopher M., Geoffrey G. Hazel, Jonathon M. Schuler, Frank Bucholtz, and Joseph V. Michalowicz. Spectral Calibration, Spatial Mapping and Flat Fielding Studies of the Dark HORSE 1 (DH1) March Data Collection. Fort Belvoir, VA: Defense Technical Information Center, January 1999. http://dx.doi.org/10.21236/ada359348.

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Rencz, A., J. Harris, D. Sangster, and P. Budkewitsch. Spectral characteristics of bedrock map units using LANDSAT TM and topographic data: application to bedrock mapping in Borden Peninsula, Nunavut. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2000. http://dx.doi.org/10.4095/211100.

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Harris, J. R., and M. St-Onge. Case study 3. The advantages of high-resolution spectral and spatial hyperspectral data for lithological mapping: an example from southeast Baffin Island. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2008. http://dx.doi.org/10.4095/226016.

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Ruiz, Pablo, Craig Perry, Alejando Garcia, Magali Guichardot, Michael Foguer, Joseph Ingram, Michelle Prats, Carlos Pulido, Robert Shamblin, and Kevin Whelan. The Everglades National Park and Big Cypress National Preserve vegetation mapping project: Interim report—Northwest Coastal Everglades (Region 4), Everglades National Park (revised with costs). National Park Service, November 2020. http://dx.doi.org/10.36967/nrr-2279586.

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Abstract:
The Everglades National Park and Big Cypress National Preserve vegetation mapping project is part of the Comprehensive Everglades Restoration Plan (CERP). It is a cooperative effort between the South Florida Water Management District (SFWMD), the United States Army Corps of Engineers (USACE), and the National Park Service’s (NPS) Vegetation Mapping Inventory Program (VMI). The goal of this project is to produce a spatially and thematically accurate vegetation map of Everglades National Park and Big Cypress National Preserve prior to the completion of restoration efforts associated with CERP. This spatial product will serve as a record of baseline vegetation conditions for the purpose of: (1) documenting changes to the spatial extent, pattern, and proportion of plant communities within these two federally-managed units as they respond to hydrologic modifications resulting from the implementation of the CERP; and (2) providing vegetation and land-cover information to NPS park managers and scientists for use in park management, resource management, research, and monitoring. This mapping project covers an area of approximately 7,400 square kilometers (1.84 million acres [ac]) and consists of seven mapping regions: four regions in Everglades National Park, Regions 1–4, and three in Big Cypress National Preserve, Regions 5–7. The report focuses on the mapping effort associated with the Northwest Coastal Everglades (NWCE), Region 4 , in Everglades National Park. The NWCE encompasses a total area of 1,278 square kilometers (493.7 square miles [sq mi], or 315,955 ac) and is geographically located to the south of Big Cypress National Preserve, west of Shark River Slough (Region 1), and north of the Southwest Coastal Everglades (Region 3). Photo-interpretation was performed by superimposing a 50 × 50-meter (164 × 164-feet [ft] or 0.25 hectare [0.61 ac]) grid cell vector matrix over stereoscopic, 30 centimeters (11.8 inches) spatial resolution, color-infrared aerial imagery on a digital photogrammetric workstation. Photo-interpreters identified the dominant community in each cell by applying majority-rule algorithms, recognizing community-specific spectral signatures, and referencing an extensive ground-truth database. The dominant vegetation community within each grid cell was classified using a hierarchical classification system developed specifically for this project. Additionally, photo-interpreters categorized the absolute cover of cattail (Typha sp.) and any invasive species detected as either: Sparse (10–49%), Dominant (50–89%), or Monotypic (90–100%). A total of 178 thematic classes were used to map the NWCE. The most common vegetation classes are Mixed Mangrove Forest-Mixed and Transitional Bayhead Shrubland. These two communities accounted for about 10%, each, of the mapping area. Other notable classes include Short Sawgrass Marsh-Dense (8.1% of the map area), Mixed Graminoid Freshwater Marsh (4.7% of the map area), and Black Mangrove Forest (4.5% of the map area). The NWCE vegetation map has a thematic class accuracy of 88.4% with a lower 90th Percentile Confidence Interval of 84.5%.
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Hamilton, S. M. The use of wide spectrum groundwater geochemistry in regional groundwater mapping in Ontario. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2018. http://dx.doi.org/10.4095/306532.

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