Abstract:
ParaView is an open-source, multi-platform application designed to visualize data sets of size varying from small to very large. The goals of the ParaView project include the following:
-Develop an open-source, multi-platform visualization application. -Support distributed computation models to process large data sets. -Create an open, flexible, and intuitive user interface. -Develop an ... extensible architecture based on open standards.
Main animation ParaView runs on distributed and shared memory parallel as well as single processor systems and has been successfully tested on Windows, Mac OS X, Linux and various Unix workstations, clusters and supercomputers. Under the hood, ParaView uses the Visualization Toolkit as the data processing and rendering engine and has a user interface written using Qt.
Use Constraints
Copyright (c) 2005,2006 Sandia Corporation, Kitware Inc.
Sandia National Laboratories, New Mexico PO Box 5800 Albuquerque, NM 87185
Kitware Inc. 28 Corporate Drive Clifton Park, NY 12065 USA
Under ... the terms of Contract DE-AC04-94AL85000, there is a non-exclusive license for use of this work by or on behalf of the U.S. Government.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
* Neither the name of Kitware nor the names of any contributors may be used to endorse or promote products derived from this software without specific prior written permission.
* Modified source versions must be plainly marked as such, and must not be misrepresented as being the original software.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHORS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. =============================================================
Name:
KITWARE, INC.
Phone:
518-371-3971
Fax:
518-371-3971
Email:
kitware at kitware.com
Contact Address:
Kitware, Inc.
28 Corporate Drive
Suite 204 City:
Clifton Park
Province or State:
NY
Postal Code:
12065
Country:
USA
Distribution Media
Distribution_Media:
Online
Fees:
No fees
Personnel
TYLER
B.
STEVENS Role:
SERF AUTHOR
Phone:
(301) 614-6898
Fax:
301-614-5268
Email:
Tyler.B.Stevens at nasa.gov
Contact Address:
NASA Goddard Space Flight Center
Global Change Master Directory City:
Greenbelt
Province or State:
MD
Postal Code:
20771
Country:
USA
KITWARE, INC. Role:
TECHNICAL CONTACT
Phone:
518-371-3971
Fax:
518-371-3971
Email:
kitware at kitware.com
Contact Address:
Kitware, Inc.
28 Corporate Drive
Suite 204 City:
Clifton Park
Province or State:
NY
Postal Code:
12065
Country:
USA
Publications/References
Cavalieri, D. and J. Comiso. 2000. Algorithm Theoretical Basis Document for the AMSR-E Sea Ice Algorithm, Revised December 1. Landover, MD, USA: Goddard Space Flight Center. Cavalieri, D.J., K.M. St. Germain, and C.T. Swift. 1995. Reduction of weather effects in the calculation of sea ice concentration with the DMSP SSM/I. Journal of Glaciology 41(139): 455-464. Cavalieri, D.J., P. Gloersen, ... and W.J. Campbell. 1984. Determination of sea ice parameters with the NIMBUS-7 SMMR. Journal of Geophysical Research 89(D4):5355-5369. Comiso, J., D. Cavalieri, and T. Markus. 2003. Sea ice concentration, ice temperature, and snow depth using AMSR-E data. IEEE Transactions on Geoscience and Remote Sensing 41(2): 243-252. Comiso, J., and K. Steffen. 2001. Studies of Antarctic sea ice concentrations from satellite data and their applications. Journal of Geophysical Research 106(C12): 31,361-31,385. Comiso, J. C., D. J. Cavalieri, C. L. Parkinson, and P. Gloersen. 1997. Passive Microwave Algorithms for Sea Ice Concentration - A Comparison of Two Techniques. Remote Sensing of the Environment 60: 357-384. Comiso, J.C. 1995. SSM/I ice concentrations using the Bootstrap Algorithm. NASA RP 1380, 50 pp. Conway, D. 2002. Advanced Microwave Scanning Radiometer - EOS Quality Assurance Plan. Huntsville, AL: Global Hydrology and Climate Center. Eppler, D. T. and 14 others. 1992. Passive Microwave Signatures of Sea Ice, in Microwave Remote Sensing of Ice. Geophysical Monograph Series 68: 47-71. AGU, Washington, D.C. Fraser R. S., Gaut, N. E., Reifenstein, E. C., and H. Sievering. 1975. Interaction Mechanisms Within the Atmosphere Including the Manual of Remote Sensing. American Society of Photogrammetry 181-233. Falls Church, VA. Gloersen P. and D.J. Cavalieri. 1986. Reduction of weather effects in the calculation of sea ice concentration from microwave radiances. Journal of Geophysical Research 91(C3):3913-3919. Gloersen P, W. J. Cambell, D. J. Cavalieri, J. C. Comiso, C. L. Parkinson, and H. J. Zwally. 1992. Arc tic and Antarctic Sea Ice, 1978-1987: Satellite Passive Microwave Observations and Analysis. National Aeronautics and Space Administration, Special Publication 511, Washington, D.C., pp.290. Kummerow, C. 1993. On the accuracy of the Eddington approximation for radiative transfer in the microwave frequencies. Journal of Geophysical Research 98: 2757-2765. Lubin, D., C. Garrity, R. O. Ramseier, and R. H. Whritner. 1997. Total Sea Ice Concentration Retrieval from the SSM/I 85.5 GHz Channels During the Arctic Summer, Rem. Sens. Environ 62: 63-76. Markus, Thorsten and Donald J. Cavalieri. 2008. Supplement AMSR-E Algorithm Theoretical Basis Document: Sea Ice Products. Greenbelt, MD, USA: Goddard Space Flight Center. (view pdf) Markus, Thorsten and Donald J. Cavalieri. 1998. Snow depth distribution over sea ice in the Southern Ocean from satellite passive microwave data. Antarctic Sea Ice: Physical Processes, Interactions, and Variability. Antarctic Research Series 74:19-39. Wash ington, DC, USA: American Geophysical Union. Markus, Thorsten and Donald J. Cavalieri. 2000. An enhancement of the NASA Team sea ice algorithm. IEEE Transactions on Geoscience and Remote Sensing 38: 1387-1398. Matzler, C., R. O. Ramseier, and E. Svendsen. 1984. Polarization Effects in Sea-ice Signatures. IEEE Journal of Oceanic Engineering 9: 333-338. Pearson, F. 1990. Map projections: Theory and applications. CRC Press. Boca Raton, Florida. 372 pages. Snyder, J.P. 1987. Map projections - a working manual. U.S. Geological Survey Professional Paper 1395. U.S. Government Printing Office. Washington, D.C. 383 pages. Snyder, J. P. 1982. Map Projections Used by the U.S. Geological Survey. U.S. Geological Survey Bulletin 1532. For more information regarding related publications, see the Research Using AMSR-E Data Web page.
Creation and Review Dates
SERF Creation Date:
2007-11-28
SERF Last Revision Date:
2012-08-16
Links
