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 6 E 1 Fairfax, VA 22030 ldi@gmu. edu http: //csiss. gmu. edu CSISS Page Center for Spatial Information Science and Systems 1
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 CSISS Page Center for Spatial Information Science and Systems 2
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 CSISS elements to conduct needed studies. Page Center for Spatial Information Science and Systems 3
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 CSISS Page Center for Spatial Information Science and Systems 4
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 CSISS Page Center for Spatial Information Science and Systems 5
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 CSISS Page Center for Spatial Information Science and Systems 6
Geo. Brain CI • Geo. Brain is a Geospatial CI – Funded by NASA REASo. N program – Developed and operated by a project team led by CSISS at George Mason University. • The Geo. Brain 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. CSISS Page Center for Spatial Information Science and Systems 7
Geo. Brain 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. CSISS Page Center for Spatial Information Science and Systems 8
Geo. Brain 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 Geo. Brain form the common cyberinfrastructure for conducting data-intensive Earth science research CSISS Page Center for Spatial Information Science and Systems 9
Geo. Brain 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 Geo. Brain through the CEOS WGISS Integrated Catalog (CWIC) project that CSISS is working on. • User statistics – Currently about 2400 unique users/month using the Geo. Brain services. CSISS Page Center for Spatial Information Science and Systems 10
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. – Geo. Brain 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 Geo. Brain – serve as exemplars on how valid scientific research can be conducted on Geo. Brain quickly and effectively CSISS Page Center for Spatial Information Science and Systems 11
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 Geo. Brain” – 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 • Geo. Brain is one of two CIs used in the project as the data and computing sources CSISS Page Center for Spatial Information Science and Systems 12
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 Jiao. Tong 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 CSISS Page Center for Spatial Information Science and Systems 13
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 CSISS Page Center for Spatial Information Science and Systems 14
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