Results 171 to 180 of about 7,932,226 (201)
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2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
The empirical orthogonal function (EOF) technique is used to investigate the spatial and temporal distributions of fires in insular Southeast Asia. Different fire regimes were extracted by unsupervised classification of the second to fifth EOF components.
Soo Chin Liew
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The empirical orthogonal function (EOF) technique is used to investigate the spatial and temporal distributions of fires in insular Southeast Asia. Different fire regimes were extracted by unsupervised classification of the second to fifth EOF components.
Soo Chin Liew
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IEEE Journal of Oceanic Engineering, 2011
This paper presents a novel approach to synthesize realistic environment for ocean-acoustic parametric studies. In its current form, this methodology applies to internal waves and tides. Empirical orthogonal function (EOF) decomposition is applied to a temporal series of temperature profiles.
Thomas Folégot
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This paper presents a novel approach to synthesize realistic environment for ocean-acoustic parametric studies. In its current form, this methodology applies to internal waves and tides. Empirical orthogonal function (EOF) decomposition is applied to a temporal series of temperature profiles.
Thomas Folégot
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Finding Acoustically Stable Areas Through Empirical Orthogonal Function (EOF) Classification
IEEE Journal of Oceanic Engineering, 2012Validity of sonar performance models is generally limited by environmental uncertainty, and particularly uncertainty in the sound-speed profile (SSP). Rapid environmental assessment (REA) missions, e.g., using gliders, and advanced ocean models may be used to reduce this uncertainty before sonar operation in hostile waters.
Jan Kristian Jensen +2 more
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Chinese Journal of Oceanology and Limnology, 2000
A Monte Carlo experiment was done to create a statistically significant test table for selecting EOF modes whose signals are above the noise level. Numerical analysis showed that it is feasible to choose a shorter data set between temporal and spatial dimensions for conducting an EOF analysis, and thus simplify calculation of the covariance matrix and ...
Li Xiao-feng +3 more
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A Monte Carlo experiment was done to create a statistically significant test table for selecting EOF modes whose signals are above the noise level. Numerical analysis showed that it is feasible to choose a shorter data set between temporal and spatial dimensions for conducting an EOF analysis, and thus simplify calculation of the covariance matrix and ...
Li Xiao-feng +3 more
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SPIE Proceedings, 2006
Remote sensing with the new generation of highly spectrally resolving instruments like the Atmospheric Research Interferometer Evaluation System (ARIES) or the assimilation of highly resolved spectra from satellites into Numerical Weather Prediction (NWP) systems requires radiative transfer computations that deliver results essentially instantaneous ...
Stephan Havemann
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Remote sensing with the new generation of highly spectrally resolving instruments like the Atmospheric Research Interferometer Evaluation System (ARIES) or the assimilation of highly resolved spectra from satellites into Numerical Weather Prediction (NWP) systems requires radiative transfer computations that deliver results essentially instantaneous ...
Stephan Havemann
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Design Current Profiles Using Empirical Orthogonal Function (EOF) and Inverse FORM Methods
Offshore Technology Conference, 1997Abstract In the past, the oil industry has used highly simplified design current profiles. The simplification process produces errors which are typically unimportant in shallow water but the errors can be substantial in deeper water where currents are more complex and some design concepts are sensitive to current ...
George Z. Forristall, Cortis K. Cooper
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Positrontopography, and ocean-land interactions, which shape weather patterns and rainfall intensity variability. This study analyzes rainfall patterns in Sulawesi Island from 1981 to 2015 using the Empirical Orthogonal Function (EOF) method and composite analysis with machine learning. The results show that the EOF method successfully identifies three primary
Melly Ariska +5 more
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Geostationary Satellite Observation of Precipitable Water Vapor Using an Empirical Orthogonal Function (EOF) Based Reconstruction Technique Over Eastern China [PDF]
Remote Sensing, 2015 Water vapor, as one of the most important greenhouse gases, is crucial for both climate and atmospheric studies. Considering the high spatial and temporal variations of water vapor, a timely and accurate retrieval of precipitable water vapor (PWV) is urgently needed, but has long been constrained by data availability.
George Zhizhao LIU +2 more
exaly +5 more sources
SPIE Proceedings, 2010
°Empirical orthogonal function (EOF) analysis was used to study spatio-temporal variability of the Moderate Resolution Imaging Spectroradiometer (MODIS) imagery of sea surface temperature (SST (C)) and chlorophyll (mg m -3 ) for the eastern Bering Sea for May, June, July, August, September (MJJAS) for a period of 7 years (2003 - 2009).
Puneeta Naik, Eurico J. D'Sa
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°Empirical orthogonal function (EOF) analysis was used to study spatio-temporal variability of the Moderate Resolution Imaging Spectroradiometer (MODIS) imagery of sea surface temperature (SST (C)) and chlorophyll (mg m -3 ) for the eastern Bering Sea for May, June, July, August, September (MJJAS) for a period of 7 years (2003 - 2009).
Puneeta Naik, Eurico J. D'Sa
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Volume 6: Materials Technology; C.C. Mei Symposium on Wave Mechanics and Hydrodynamics; Offshore Measurement and Data Interpretation, 2009
This paper presents a methodology to estimate deep water design current profiles using Complex Empirical Orthogonal Function (C-EOF) and a structural reliability response based model. The advantage of C-EOF is the capability of directly obtaining directional extreme current profiles.
Wellington Ceccopieri
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This paper presents a methodology to estimate deep water design current profiles using Complex Empirical Orthogonal Function (C-EOF) and a structural reliability response based model. The advantage of C-EOF is the capability of directly obtaining directional extreme current profiles.
Wellington Ceccopieri
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