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in Little PEI Dr. Robert Gilmour Jr., Dr. Adam Fenech, Stephanie Arnold and Alex Chen 13 July 2015

2015 07 13 Big Data in Little PEI.pptx

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Page 1: 2015 07 13 Big Data in Little PEI.pptx

in Little PEI

Dr. Robert Gilmour Jr., Dr. Adam Fenech, Stephanie Arnold and Alex Chen13 July 2015

Page 2: 2015 07 13 Big Data in Little PEI.pptx

Big Data Outline

1. Global Climate Models

2. Visualizing Big Data for Motivating Community Action - CLIVE

3. Big Data for Understanding Small Environments

Page 3: 2015 07 13 Big Data in Little PEI.pptx

1. Global Climate Models

Cray 1 Supercomputer Iphone 5

1985 2013

Functionality is the Same

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Global Climate ModelsAR2 (1992) AR3 (2000) AR4 (2007) AR5 (2014)

CCSRNIES CCSRNIES BCM2.0 ACCESS1-0CGCM1 CGCM2 CGCM3T47 ACCESS1-3CSMK1 CSIROMk2b CGCM3T63 bcc-csm1-1ECHAM3 GFDL30 CNRM-CM3 bcc-csm1-1-mGFDLR15 HADCM3 CSIROMk3.0 BNU-ESMHADCM2 NCARPCM CSIROMk3.5 CanESM2

ECHAM5OM CCSM4

35 33 ECHO-G CESM1-BGC FGOALS-g1.0 CESM1-CAM5 GFDLCM2.0 CMCC-CESM GFDLCM2.1 CMCC-CM GISS-AOM CMCC-CMS GISS-EH CNRM-CM5 GISS-ER CSIRO-Mk3-6-0 HADCM3 FGOALS-g2 HADGEM1 FIO-ESM INGV-SXG GFDL-CM3 INMCM3.0 GFDL-ESM2G IPSLCM4 GFDL-ESM2M MIROC3.2 hires GISS-E2-H MIROC3.2 medres GISS-E2-H-CC MRI CGCM2.3.2a GISS-E2-R NCARCCSM3 GISS-E2-R-CC NCARCCSM3(Run 9) HadCM3 NCARPCM HadGEM2-AO

HadGEM2-CC

171 HadGEM2-ESinmcm4IPSL-CM5A-LRIPSL-CM5B-LRMIROC-ESMMIROC-ESM-CHEMMIROC4hMIROC5MPI-ESM-LRMPI-ESM-MRMRI-CGCM3NorESM1-MNorESM1-ME

311

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Global Climate Models

• UPEI Climate, Ocean, Atmosphere Data Exchange (COADE)

• Database 11TB = 11,000 GB

• Output from all global climate models (GCMs) used in all IPCC assessment reports (AR2, AR3, AR4, AR5)

• downloaded in their native format to the UPEI COADE

• Output converted, formatted, interpreted, analyzed and mapped

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Global Climate Models“Most Likely Change” in Annual Mean Temperature (ºC) by 2050s

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Global Climate Models“Most Likely Change” in Annual Total Precipitation (%) by 2050s

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Global Climate ModelsChanges in Annual Mean Temperature (ºC) at Niagara Falls, NY

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Global Climate ModelsChanges in Annual Total Precipitation (%) at Niagara Falls, NY

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2. Visualizing Big Data for Motivating Community Action - CLIVE

https://www.youtube.com/watch?v=Cg6dZHg76kA&feature=youtu.be

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LiDAR – “light” “radar”

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Orthorectified Aerial Photos

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UNITY Gaming Software

LiDAR

and

Orthorectified

Aerial Photos

+

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CLIVE Data Compression

• Clickable File on Desktop (no software required)

• Data compressed to less than 2.5%

• Keyboard, mouse, Xbox controller or LEAP (easy interface)

• Accessible by all

Original Data: 250 GB

CLIVE PEI: 6 GB

• GIS License• Large memory required• Plunky user interface• Prone to crashing

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Public Consultations Summer 2014

• 8 communities across PEI

• concern went from “high” to “very high”

• “willingness to adapt” increased

• Sense of anxiety followed by urgency

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Prince Edward Island Association of PlannersMurray Pinchuk Community Builder Award

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3. Big Data for Small EnvironmentsPrecision Hawk - Lancaster

• Up to 1.0 cm/pixel resolution

• 3D point clouds with densities exceeding 250 points per square meter

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Multiple Applications

ecology, coastal geomorphology, agriculture, forestry

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3D Terrain Mapping and CLIVE

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Building Virtual Realities

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Conclusions

• Big Data everywhere

• Allows for simulations that can help motivate communities to action

• Big Data is moving to small applications – a new paradigm in environmental science

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