giscience driven r&d: interdisciplinary gist group at ornl
TRANSCRIPT
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Presented at
Purdue GIS Day
Marie Urban
November 7, 2014
www.ornl.gov/gist
GIScience Driven R&D: Interdisciplinary GIST Group at ORNL
Acknowledgment Prepared by Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, Tennessee 37831-6285, managed by UT-Battelle, LLC for the U. S. Department of Energy under contract no. DEAC05-00OR22725.
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Managed by UT-Battellefor the Department of Energy
Overview of presentation
⢠About usâ Three scientific focus areasâ Organization and programmatic thrusts
⢠Highlights of selected applicationsâ Population assessment at scaleâ Critical infrastructure mappingâ Energy assurance and climate impactsâ Scalable geospatial applications
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Managed by UT-Battellefor the Department of Energy
Oak Ridge National LaboratoryDOEâs largest science and energy laboratory
$1.5B budget
Worldâs most intense
neutronsource
4,400employees
World-class
research reactor
3,200researchguests annually$750M
modernization investment
Nationâs largest
materials research portfolio
Forefrontscientific
computing facilities
Nationâs most diverse
energy portfolio Managing
billion-dollar US ITER
project
⢠50 new Purdue alum at ORNL between 2002-2014
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Managed by UT-Battellefor the Department of Energy
Oak Ridge National Laboratory:Deliver scientific discoveries and technical breakthroughs that will accelerate the development and deployment of solutions in clean energy and global security, and in doing so create economic opportunity for the nation
Signature strengths
Neutron science and technology
Materials science and engineering
Computational science and engineering
Nuclear science and technology
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Managed by UT-Battellefor the Department of Energy
Undergraduate/ post-masterâs programs
Postdoctoral programs
Graduate degreeprograms/visiting faculty
Kâ12 programs
Education Programs to energize your career
ORNL Researcher
Science Saturdays
ARC and ORNL summer programs
Science City Adventure
HERE Lab Technology Program
Nuclear Engineering Science Lab Synthesis
ASTROUndergraduate
Laboratory Internship
Post-Bachelorâs/Post-
Masterâs Research
GEM Fellows
Bredesen Center@UT
GO! Graduate Opportunities
Postdoctoral program Fellowships
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Managed by UT-Battellefor the Department of Energy
Hig
hR
esol
utio
n Po
pula
tion
and
Soci
al
Dyn
amic
s ⢠Geographic Pattern Recognition
⢠Population-Infrastructure Dependency
⢠Demographic Analysis G
eogr
aphi
cD
ata
Scie
nces ⢠Spatiotemporal data mining
and uncertainty analysis
⢠Machine learning and pattern recognition
⢠Participatory sensing and volunteered geographic information
⢠High performance geocomputation
⢠Scalable visualization
⢠Emerging architectures
GIST Scientific focus areas
⢠An interdisciplinary group of > 50 researchers⢠Fostering advances in the nexus of GIScience and computing⢠One of the oldest GIScience R&D groups and uniquely focused within DOE
Disciplines
Geography, Anthropology
Computer Science and Computer Engineering
Electrical Engineering
Geosciences
Civil and EnvironmentalEngineering
Industrial and Information Engineering
Applied mathematics, Chemistry, Statistics
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Managed by UT-Battellefor the Department of Energy
Budhendra Bhaduri Group LeaderBeata Taylor
Ashton Brannon
Population Distribution and Dynamics
Eddie Bright
Jake McKeeAmy Rose
Marie UrbanJeanette Weaver
Eric WeberNicholas Nagle â JA
Daniel CobbJason KaufmanMegan MaloneyJessica MoehlBrian Moore
Melanie PhillipsHelen RoskoKelly Sims
Andrew ReithBrian MooreJayme Green
Janna CaspersenThomas GietemaLauryn Bingham
Geographic Data Sciences
Budhendra Bhaduri â JA
Anil CheriyadatRobert Stewart
Harini SridharanJiangye Yuan
Samantha DuchschererBenjamin Martin
April MortonHuina Mao - Fellowship
Scalable and High Performance
GeocomputationDevin White â JA
Rajasekar KarthikAaron MyersPhil NugentDilip Patlolla
Alex SorokineChris DavisNeil Thomas
Eric AxleyLee Walker
Katie CorcoranSophie Voisin
Infrastructure Dataand EP&RMark Tuttle
Cheng LiuSteve PetersonNagendra Singh
Wei LuKassie ErnstJesse Piburn
Matthew WhiteheadShane CutshawTaylor HauserErika Pham
Chris SanefordShane Cutshaw
Erik Schmidt
Critical Infrastructure and Climate ImpactsSteve Fernandez-JA
Daniel KochFemi Omitaomu
Melissa AllenLinda Sylvester
UT-BattelleSub-ContractorPost DocPost MasterPost BSIntern
Terminal Degree Staff Research
Associates
Ph.D. 12 7
MS/MA 13 8
BS/BA - 18
23 Staff; 35 Research AssociatesMission
Advance research, development, and applications of geographic information and analysis systems to support
the nationâs energy, environment, and security
programs, from local to global scales.
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Managed by UT-Battellefor the Department of Energy
Programmatic Focus Areas
Population and Critical Infrastructure Modeling⢠Population distribution in space and time⢠Socioeconomic characterization⢠Event specific population response
Energy Assurance
⢠Energy and water resources assurance and reliability⢠Modeling and visualizing the âSmart Gridâ⢠Bioenergy and renewable energy integration
Transportation M&S
⢠Multimodal route optimization⢠Intelligent evacuation planning
Emergency Preparedness and Response
⢠Time critical decision support⢠Disaster risk analysis
Climate Change Science
⢠Climate extremes and infrastructures⢠Climate change and population response⢠Energy and national security
Earth Science Informatics
⢠Real time data integration⢠Data and knowledge management
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Managed by UT-Battellefor the Department of Energy
Community leadership: Organized workshops
GIScience⢠Role of volunteered geographic information in advancing science
ACM SIGSPATIAL⢠Analytics for Big geospatial data
IEEE ICDM⢠Spatial and spatiotemporal data mining (SSTDM)⢠Knowledge discovery using cloud and distributed computing platforms
ACM KDD⢠Knowledge discovery from sensor data (SensorKDD)
IEE/ACM Supercomputing⢠Petascale (Big) data analytics: Challenges and opportunities
IEEE ICCV⢠Computer Vision for Converging Perspectives
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Managed by UT-Battellefor the Department of Energy
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Managed by UT-Battellefor the Department of Energy
LandScan Population Distribution and Dynamics Model and Database
Census
Gridded
DayNight
LandScan Global
LandScan USA
As the finest population distribution data ever produced for the world and the US, LandScan Global and LandScan USA are the
community standard for estimating population at risk
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Spatial refinement of LandScan Global
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Addis Ababa, Ethiopia
2 Xeon Quad core 2.4GHz CPUs + 4 Tesla GPUs + 48GB
Image analyzed (0.3m) 40,000x40,000 pixels
(800 sq. km) RGB bands
Overall accuracy 93% Settlement class 89% Non-settlement class
94%
Total processing time 27 seconds
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Rapid Scene
Analysis
Play uavrun1output.avi
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Kacha Garhi Camp, Pakistan⢠Established 1980 for Afghan Refugees
⢠QuickBird (2004 and 2009, 4B, 2.4m)
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Managed by UT-Battellefor the Department of Energy
Neighborhood mapping: From local interactions to global realizations
Damascus, Syria
â˘Very loosely structuredâ˘Historical ethnic quarters/neighborhoodsâ˘Poor residents currently being displaced in some areas with urban development/tourism
â˘Formal Urban Planningâ˘Typical Urban Servicesâ˘Middle to Upper Income
â˘Unstructured Settlementsâ˘Lowest to lower middle incomeâ˘Rural migrants
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Managed by UT-Battellefor the Department of Energy
Population Density Data from Open Source
⢠Population/1000 ft2
⢠50+ structural facility categories in 8 land use classes
⢠Documented data sources and methodology with traceable provenance
⢠Open source collection from reputed sources (> 14K)
â Academic journals, official government statistics, corporate and university webpages, tourism brochures.
â Utilizing other sources such as GeoCommunity, Wikipedia, Panoramia, and Wikimapia.
https://pdt.extranet.ornl.gov/
⢠Spatial resolution/extent⢠Temporal resolution
â Diurnalâ Workweek/weekendâ Episodic/holidays/special
eventâ Seasonal
⢠Political and socio-economic characteristics included
â Ethnicâ Religiousâ Racialâ Political affinityâ Economic strength
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Retaining Data Provenance is Critical
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Managed by UT-Battellefor the Department of Energy
Exploratory Spatiotemporal Analytics
World Spatio-Temporal Analysis Mapping Project
⢠Illuminate patterns of geopolitical and strategic importance from over 30+ data sources like the CIA World Fact book, World Bank, UN, and Correlates of War. â ~250 countries and geographic entitiesâ ~2100 socioeconomic and demographic attributesâ 25 years
⢠Develop geovisualization, geopolitical ontologies, and geonarratives
⢠Enable analysts to ask questions from data and just not look for answers
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Managed by UT-Battellefor the Department of Energy
Critical infrastructure data development
Prisons Day-care Centers
Rail lines/Rail points
Hospitals Solid Waste Landfills
Mobile Home Parks
Energy Data Layers
We develop and maintain spatially enabled, foundation level data for a number of critical infrastructures for research and operational communities.
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Managed by UT-Battellefor the Department of Energy
Readiness, Response, and Recovery
Population mobility and advanced evacuation
modeling and simulations
Global security infrastructure
protection support
Augmentation of EARSS
mobile and web services
Special events population
model
High Performance
SAR data processing for
disaster response
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Managed by UT-Battellefor the Department of Energy
Climate Change Science
⢠Feedback among climate, land use, and population distribution
⢠Climate induced hazards and infrastructure impacts
⢠Spatiotemporal translation of regional climate impacts on local decisions
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Managed by UT-Battellefor the Department of Energy
Population mobility modeling framework
⢠Quick response emergency evacuation system to analyze evacuation scenarios any place in the world.
⢠Ability to perform time variant modeling such as daily commuter traffic (engineering) modeling.
Flexible and global scope
⢠High resolution population (LandScan Global and LandScan USA) and street networks (NAVTEQ and OSM)
⢠Mesoscale (link based) to microscale simulations (TRANSIMS and MITSIM)
Scalable data integration and
modeling
⢠Web application using WebGL and data streaming techniques to display vehicular movement across the respective networks.
⢠Ongoing integration with mobile platforms and cloud computing.
Dynamic visualization and
access
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Managed by UT-Battellefor the Department of Energy
Climate influences the spatiotemporal distribution of human populations
⢠Understanding human exposure to climatic extremes and the local, regional and global distribution of resources provides insights into potential migration and resettlement patterns
⢠Bangladesh:162 Millions population, 27 millions household
⢠Full scale Bangladesh simulation is estimated to require 20,000 CPU hours or 400 GPU hours for a single simulation
Runtime for Different Numbers of Agents on GPU Based Parallel Computing Platforms (ORMAC ABM Platform)
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Managed by UT-Battellefor the Department of Energy
FETE - From Everywhere to Everywhere
⢠Provides a mechanism for understanding how people make decisions related to travel.
⢠The foundation is a least cost analysis â people make decisions to minimize costs.
⢠People behave fairly predictably in this regard, especially in aggregate, but may change course in certain situations.
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Energy Assurance
⢠Cyberphysical systems in energy
⢠Spatiotemporal assessment of renewable energy potential
⢠Early warning systems for climate extremes
⢠Bioresource monitoring for energy security
⢠Geographically scalable spatiotemporal optimization for energy supply chainâ PRISM
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Managed by UT-Battellefor the Department of Energy
Design and develop a robust and scalable spatiotemporal data mining framework utilizing high resolution spatial and temporal data streams (MODIS and AWiFS)
Geocomputation based strategy
Preprocessing
⢠Reprojection⢠Atmospheric
corrections⢠Time series
filtering
Change detection
⢠Time series prediction
⢠Unsupervised multidimensional geospatial image clustering
Change characterization
⢠Classification⢠Phenology-based⢠Crop Type-based
Google Earth
NASA World Wind
Other thin
clients
GreenupOnset Dormancy
Onset
Peak
Length of growingseason
Key features of crop phenology
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Managed by UT-Battellefor the Department of Energy
Wide area biomass monitoring in near real time is becoming a reality
⢠41,105 seconds (11.4 hours)Serial
⢠5,872 seconds (1.6 hours)Threads (16)
⢠604 seconds (10 minutes)MPI (96 nodes)
⢠34 secondsMPI + Threads (1536 cores)
⢠MODIS Tile (4800x4800 pixels)â ~23 million locations/time seriesâ 161 time steps (bi-weekly over 7
years)
⢠FROST: An SGI Altrix ICE 8200 Cluster at ORNLâ 128 compute nodes each with 16
virtual cores and 24 GB of RAM
⢠Multicore (multithreaded) and Distributed (message passing) computing strategy
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EARSS: Hurricane Irene (8/26, 1625)
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Managed by UT-Battellefor the Department of Energy
Spatial Analysis and Decision AssistanceSADA provides a spatially enabled modeling environment that integrates:
⢠advanced methods in sample design,
⢠risk assessment,
⢠remedial design, and cost-benefit analysis
Risk communication, uncertainty assessment and geovisualization are a central focus of the work.
18K+ users
www.sadaproject.net
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Managed by UT-Battellefor the Department of Energy
We support a global user community
LandScan Global⢠Spatial resolution of 30 arc seconds (~1km); Ambient population.⢠~1350 registered organizations worldwide since 2005; 115 commercial
licensees. Enterprise standard for NATO.⢠Google search returns 225,000 web pages.
LandScan USA⢠Spatial resolution of 3 arc seconds (~90m); Nighttime and daytime population.⢠836 organizational requests, to support over 110,734 users, for the HSIP Gold
2010 .
Bioenergy KDF⢠Bioenergy infrastructure analysis with 1600 Datasets; 1450 Map Services.⢠13,000 Visits from 134 Countries; Avg. Time on Site: 6:00. (Since Feb. 2013)⢠1156 registered users since January 2011.
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Managed by UT-Battellefor the Department of Energy
We support a global user community
WebTRAGIS⢠Multi-Modal Routing Analysis and Visualization Tool ⢠220 Visits Since Oct. 2013, Avg. Time on Site: 4:10⢠55 Registered users since September 2012.
Population Density Tables (PDT)⢠Open Source Data Collection for Population Density Modeling⢠55 Registered users since November 2011.
Centralized Used Fuel Resource for Information Exchange (CURIE)⢠2,235 Used Fuel related Documents, Data, and Images.⢠4,800 Visits from 65 Countries; Avg. Time on Site: 7:24. (Since Feb. 2013)⢠112 registered users since January 2013.
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Managed by UT-Battellefor the Department of Energy
We support a global user community
Energy Awareness Resiliency Standardized Services (EARSS)⢠Infrastructure Disruption Visualization Tool⢠105 unique users during Hurricanes Irene and Sandy⢠Re-publication from FEMA Geoportal to State Emergency Operation Centers
Homeland Security Extreme Weather Event Anticipation Tool (HEAT)⢠Interfaces Climate Impacts with Critical Infrastructure Disruption Models⢠25 Evaluation Accounts with DHS, EPA and Local planners as part of Regional
Risk Assessment Program
Production and Research Informatics for Strategic Materials (PRISM)⢠Collaboration, Data Management, Analytics, and Visualization Platform
supporting Strategic Materials Supply Chain Analysis community⢠Organizational Experimental Accounts with DLA, DOE, and NGA
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Managed by UT-Battellefor the Department of Energy
Oak Ridge Urban Dynamics Institute
⢠Science and informatics for energy and urban infrastructuresâ Data from individual components (sensors) of infrastructure
networks (energy, water, transportation, telecommunication,âŚ)â Data from users of infrastructure (human network)
⢠Characterization of the interaction between the human dynamics and integrated infrastructures
â Discovering emerging behavior of urban systems over large spatial and temporal scales (at unprecedented resolution)
⢠Efficient data management, analysis, creation, and visualization of meaningful information within useful timeframe
⢠Developing interdisciplinary bridge between foundational R&D, operational communities, and industry
Population
â˘Distribution and dynamics
â˘Land use change
â˘Citizen science
Mobility
â˘Connected vehicles
â˘Driver-assistance systems
â˘Safety
Energy
â˘Efficiencyâ˘Pollutionâ˘Sustainability
Resiliency
â˘Cyber securityâ˘Communicationâ˘Disaster management
Delivering transformational science and technology capabilities
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Managed by UT-Battellefor the Department of Energy
Data and computing for urban scienceSmart Cities
⢠Sustainable mobility
⢠Energy efficiency
⢠Resilient infrastructure
Energy
⢠Transportation⢠Electricity⢠Water⢠Buildings
Environment
⢠Pollution⢠Air⢠Water⢠Noise
⢠Public health
Security
⢠Cyber⢠Communication⢠Disaster
management
â˘SIFT/ SURFâ˘Node degreeâ˘âŚ
Feature Extraction
â˘Multi-resolutionâ˘Multi-sensorâ˘Multi-modal
Data Fusionâ˘PCAâ˘Compressionâ˘âŚ
Feature Selection
â˘Data Miningâ˘Machine Learning
Knowledge Discovery
Social Media LiDAR
Text Images
Sensors Video
Big Spatiotemporal Databases
Challenges (Increased I/O:150X, Computation: O(n2)-O(n3)
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