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@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
• humanity’s 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
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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
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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 online 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)
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An open customizable geospatial data source.
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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
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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.
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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 scientistbased 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
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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 Agrogeoinformatics 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
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