Earth Observation Data Cooperation and Sharing through Geospatial Cyberinfrastructure

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Earth Observation Data Cooperation and Sharing
through Geospatial Cyberinfrastructure

• Liping Di, Ph.D.
• Professor and Director
• Center for Spatial Information Science and
  Systems (CSISS)
• George Mason University (GMU)
• 4400 University Drive, MSN 6E1
• Fairfax, VA 22030
• ldi_at_gmu.edu
• http//csiss.gmu.edu

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Introduction

• Human beings depend on suitable
  climate/environment and services provided by
  ecosystems for food, water, shelter, and survival
• humanitys increasingly extensive socioeconomic
  activities have significantly altered global
  climate and life-sustaining ecosystems.
• The Asia-Pacific region, in particular, is
  critical to studying and understanding the human
  impact on climate, biodiversity and ecosystems
  due to its large and diverse demography,
  geographic size, and fast growing economies and
  population.
• Studies of global climate and environmental
  change are data intensive and require capacity to
  acquire and process huge volumes of Earth science
  data from diverse sources.
• Earth science data with large spatial and
  frequent temporal coverages

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Cooperation and sharing of Earth science resources

• The key method for acquiring Earth science data
  is the satellite remote sensing
• Many countries have engaged in satellite-based
  Earth observations
• Highly complementary spatially, temporally, or
  spectrally.
• Processed and archived at institutions around the
  world.
• in situ data collection, knowledge of local
  socioeconomic and physical conditions, and field
  validation are essential for understanding the
  underlying mechanisms of ecosystem changes,
  predicting regional and global impacts, and
  mitigating consequences of the changes.
• International cooperation and sharing of data,
  information, knowledge, sensors and computing
  facilities, human resources and Earth science
  wisdom are essential elements to conduct needed
  studies.

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Geospatial Cyberinfrastructure

• Cyberinfrastructure (CI) an coordinated cyber
  environment that supports advanced data
  acquisition, data storage, data management, data
  integration, data mining, data visualization and
  other computing and information processing
  services and facilities distributed over the
  Internet beyond the scope of a single
  institution.
• cyberinfrastructure is a technological and
  sociological solution to the problem of
  efficiently sharing data, information, sensors,
  models, computing resources with the goal of
  enabling derivation of novel scientific theories
  and knowledge.
• Geospatial CI-The cyberinfrastructure in Earth
  science domain.
• Essential and most effective way for Earth
  observation data cooperation and sharing

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GMU CSISS

• Established in January 2006 as one of GMU
  university research centers chartered by the
  provost.
• It originated from the Laboratory for Advanced
  Information Technology and Standards (LAITS)
  established in November 2000.
• Missions
• Developing technologies and standards for the
  implementation of national and international
  spatial cyberinfrastructures (e.g., NSDI, GSDI,
  Digital Earth, EOSDIS, GEOSS)
• Developing advanced information technologies and
  systems for automating the processes from
  geospatial data to information and knowledge.
• Leading the development of federal, national, and
  international standards in geographic information
  science and remote sensing.
• Developing new remote sensing algorithms for
  Earth system science research and applications.
• Goal
• Make geospatial information the mainstream
  information so that not only just experts but
  also everyone can easily obtain and use it.
• CSISS website http//www.csiss.gmu.edu

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CSISS Efforts on CI

• National and international standards on
  geographic Information
• Core geospatial cyberinfrastructure technology
• Data discovery, access, and integration
• Service discovery and execution
• Service chaining, geospatial processing modeling,
  workflows
• Resource management, metadata and provenance
• Knowledge and virtual organization
• Earth observation sensor web
• Coordinate and manage distributed sensor
  resources
• Construction and operation of geospatial CI
• Cyberinfrastructure-based Earth system/remote
  sensing research

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GeoBrain CI

• GeoBrain is a Geospatial CI
• Funded by NASA REASoN program
• Developed and operated by a project team led by
  CSISS at George Mason University.
• The GeoBrain CI
• provides innovative methods for publishing,
  accessing, visualizing, and analyzing geospatial
  data and for building and sharing geospatial
  knowledge
• establishes an unique online data-intensive
  learning and research environment freely
  available to users all over the world
• makes peta-bytes of NASA EOS data and information
  in both on-line data pools and near-line
  storages, easily accessible to and usable by
  higher-education users as if they have such
  resources locally.

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GeoBrain Capabilities (1)

• An open customizable geospatial data source.
• Work with all HDF-EOS data in EOSDIS online data
  storages.
• Provide interoperable, personalized, on-demand
  data access and services (IPODAS) to the data
  automatically
• Users will obtain data that exactly match their
  requirements in term of format, projection,
  spatial/temporal coverage and resolutions.
• OGC WCS, WMS, and CSW interfaces are provided.
• An on-line data analysis system.
• Several hundred geospatial web services are
  provided on-line for analyzing any of the EOSDIS
  online data.
• Services are developed in-house with OGC
  standards or converted from more than 200 GRASS
  GIS functions.

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GeoBrain Capabilities (2)

• An on-line platform for geospatial-processing
  modeling.
• A regular user can construct a geospatial
  processing model conceptually to tell step by
  step how a type of geospatial products can be
  generated from lower-level inputs.
• The model will be converted automatically to
  executable web-service workflow once the user
  specifies geospatial coverage and time of the
  model output and generate the output for users.
• After proper review, the model is kept in the
  system as a type of products the system can offer
  (virtual geospatial products).
• Automatic composition of the processing models
  with support of ontology and type matches are
  prototyped (OWL-S based).
• An platform for sharing geospatial knowledge
• The processing models at concept level represent
  the geospatial knowledge.
• The models should be sharable with other systems.
• All these capabilities of GeoBrain form the
  common cyberinfrastructure for conducting
  data-intensive Earth science research

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GeoBrain Operation

• Operational since 2005
• Data resources
• All NASA EOSDIS data
• USGS Landsat archives
• NOAA data All NOAA satellites and climate data
  archived in CLASS system
• Total data volumes over 6 Petabytes
• Additional data resources of other space agencies
  will become accessible to GeoBrain through the
  CEOS WGISS Integrated Catalog (CWIC) project that
  CSISS is working on.
• User statistics
• Currently about 2400 unique users/month using the
  GeoBrain services.

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CI-Based Research and Education

• Currently, scientists conducting data-intensive
  global change studies require significant
  computer resources and data management expertise
  locally.
• Only a few scientists have such resources now,
  and most are located in the developed countries.
• GeoBrain catalyzes the paradigm change on how
  data-intensive global change research will be
  conducted by providing such resources virtually
  to every scientist through the online platform.
• This paradigm change will transform
  data-intensive global change research from a
  local, isolated, individual scientist-based
  activity to CI-supported collaborative e-science
  endeavors.
• We are currently working on building a set of
  application and decision support systems using
  the common infrastructure and capabilities
  provided by GeoBrain
• serve as exemplars on how valid scientific
  research can be conducted on GeoBrain quickly and
  effectively

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US-China Cooperation on CI-based Geospatial
Research and Education (1)

• Demonstration Study on Advancing Global Change
  Research Approaches Based on Inter-Agency
  Collaboration and Data Infrastructure of GENESI
  and GeoBrain
• Funded by Asia-Pacific Network (APN) for Global
  Change Studies
• PI- Prof. Guoqing Li, The Center for Earth
  Observation and Digital Earth, Chinese Academy of
  Sciences
• Scientists from 6 countries participate in the
  project
• To demonstrate the advantage of CI-based
  scientific research
• Case study areas Tibet and Southeast Asia
• GeoBrain is one of two CIs used in the project
  as the data and computing sources

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US-China Cooperation on CI-based Geospatial
Research and Education (2)

• Enhancing Knowledgeable Agricultural Decision
  Support in Global Perspectives--Collaborative
  Partnership in Agro-geoinformatics Education and
  Research Exchange
• Funded by US Department of Agriculture (USDA)
• US participations- GMU/CSISS (PI), USDA/NASS
• Chinese Partners
• College of Agriculture, Shanghai JiaoTong
  University
• China National Engineering Research Center for
  Information Technology in Agriculture
• Institute of Agricultural Resources and Regional
  Planning, Chinese Academy of Agricultural
  Sciences
• Division of Agricultural Remote Sensing at
  Chinese Academy of Agricultural Engineering
• The State Key Laboratory of Information
  Engineering in Survey, Mapping, and Remote
  Sensing, Wuhan University

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Discussion and Conclusion

• Cooperation on Earth observations and sharing the
  resulting data are very important for Earth
  science research at regional to global scale.
• Geospatial Cyberinfrastructure is the essential
  infrastructure for sharing and cooperation.
• The cooperation and sharing are already fruitful
• Current data flow is mostly from U.S. to China
• Hope that more data flow from China to U.S.
• China has many Earth observation satellites on
  orbit now
• E.g., environmental satellite series,
  disaster-reduction satellite series
• Those data are useful to scientists worldwide
• Open data access policy