abstract
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Visualization of the CReSIS Greenland Datasets for the PolarGrid High Performance Computing System . Abstract. - PowerPoint PPT PresentationTRANSCRIPT
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Visualization of the CReSIS Greenland
Datasets for the PolarGrid High
Performance Computing System
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AbstractThe Center for Remote Sensing of Ice Sheets (CReSIS) has been compiling
Greenland ice sheet thickness data since 1993. The airborne program utilizes a 150 MHz radar echo sounder to measure the ice thickness. The data is currently available on the CReSIS web site in various formats including PDF, Matlab, and plain text files. These formats are not usable in the classroom environment as a visual representation of the ice depth for each expedition.
During the Undergraduate Research Experience in Ocean, Marine and Polar Science 2009 program, the Greenland Data Visualization Team took the CReSIS data and created a 4-D visualization consisting of depth, time, latitude, and longitude. This visualization was created utilizing HTML, JavaScript, and PHP. Microsoft Excel was used to filter the raw data downloaded from the CReSIS site. The team then statistically analyzed the Greenland ice sheet thickness data for calculated, missing, and actual depth readings. The goal of this project was to present the CReSIS data via the web in a visual format to elementary, undergraduate, and graduate students for research and education. This visualization package and corresponding data will eventually be migrated to the Elizabeth City State University Polar Grid High Performance Computing System. The research that follows involved converting plain text files to comma separated values to be used by PHP and JavaScript to produce data visualizations in Google Maps and HTML pages.
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Overview
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Data Visualization & Terminology
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Excel
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Project Phases
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Phase One
Download files
Storage on flash drive or personal computers
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Phase Two
Index Date Comment
Added Columns
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Phase Three
New Longitude formula: =(E1-360)
Replace -999 or NAN to 0 formula: =IF((D1=“0”),”0”-(D1))
Comment in column J formula: =IF((D1=“0”),”M”,IF((I1=“CALCD”), “C”, “A”))
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Phase Four
Combine files into one folder
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Phase Five
Sort by time and redo index
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Phase Six Line Graph
=IF(sheet name_05!$A2/ROUNDUP(COUNT(sheetname_05!$A:$A)/32000,0)=INT(sheet name_05!$A2/ROUNDUP(COUNT(sheet name_05!$A:$A)/32000,0)),sheet name_05!A2,"")
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Scatter Plot
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Flight Plan
May 30, 2002 data of flight
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Phase Seven
Copy phase fiveRecorded and analyzeCount for actual, calculating , and
missing lines
Formula:=COUNTIF(J:J,”A”)
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Phase Eight
Formula:
=IF(S1$A1/ROUNDUP(COUNT(S1!$A:$A)/200,0)=INT(S1!$A1/ROUNDUP(COUNT(S1!$A:$A)/200,0))1!A1””)
Copy phase five folder
Reduce to 200 lines
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Phase Nine Deleted columns A, E, H, and I
Replace “p” (paragraph mark ) with ^p for PHP
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Phase Ten
Remove calculations and formulas from excel
Delete A, E, H, and I again
Overwritten, Producing In Google Map
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Final Product
Flight Pathshttp://mmt.cs.ecsu.edu/pgdataviz/pg-data-set-flightlines.php
4-D Visualizationhttp://mmt.cs.ecsu.edu/pgdataviz/pg-data-set-request.php
Data Downloadshttp://mmt.cs.ecsu.edu/pgdataviz/dd.php
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1993 1995 1996 1997 1998 1999 2001 2002 2003 2005 2006 2007
0
100000
200000
300000
400000
500000
600000
700000
139398131401
36976
163261 188814223892
85661133708
110705
605362 632087
413628
Total Lines
Outcome
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1993 1995 1996 1997 1998 1999 2001 2002 2003 2005 2006 2007
0
2
4
6
8
10
12
14
9 9
3
11 11
13
5
8
6 6
11
5
Days per Year
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1993 1995 1996 1997 1998 1999 2001 2002 2003 2005 2006 20070.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
ActualCalculated
Missing
Actual/Calculated/Missing Data Averages by Year
Actual Calculated Missing
Depth Type
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Future Work
2008- Present- Future data could can be utilized to produce a more accurate visual of what is happening to the now.
Antarctic Data- The calculation of lost ice could be compared to see if there is the same amount of loss or if the climate is changing differently in the two locations.
Excel Macros-In phases IV and VII macros were used to perform some of the tedious task. In phase IV the task was to combine the data by days. Since there were multiple files per day, Visualization is used often in the area of teaching, research, and development.
Standardized Data Collection Format CReSIS used different formats, which made out work more challenging by précising the information together.
At some point the data will be moved to a high computing cluster at ECSU. This cluster will be able to handle the data faster. The high computer cluster will be located in the E.V. Wilkins Building on the ECSU campus.
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Dr. Linda B. Hayden
Acknowledgments
Jeff Wood
CReSIS
CERSER
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References1. http://serc.carleton.edu/introgeo/mathstatmodels/UsingXL.htm
2. (https://www.cresis.ku.edu/research/data/greenland_data.htm
3. Greenland Data Sets,CReSIS,2009- https://www.cresis.ku.edu/research/data/greenland_data.html
4. Climate Change,CReSIS,2008- https://www.cresis.ku.edu/news/documents/ClimateChangeFAQ.pdf
5. Microsoft Excel, 2007 http://office.microsoft.com/en- us/Excel/default.aspx [5] Roman, Steven. Writing Excel Macros with VBA. O'Reilly Media, Inc, 2002.
6. Microsoft, "VBA for Excel". Microsoft. 2008 http://www.Excel- vba.com/Excel-vba-contents.html.
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