Developing the next generation of Earth science data systems: the Global Land Cover Facility

TitleDeveloping the next generation of Earth science data systems: the Global Land Cover Facility
Publication TypeConference Papers
Year of Publication1999
AuthorsLindsay FE, Townshend JRG, JaJa JF, Humphries J, Plaisant C, Shneiderman B
Conference NameGeoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International
Date Published1999///
ISBN Number0-7803-5207-6
KeywordsComputer architecture, data archiving, data distribution system, Data systems, Distributed computing, Earth science data products, Earth science data system, ESIP, geographic information system, geographic information systems, Geography, geophysical measurement technique, geophysical signal processing, geophysical techniques, Geoscience, GIS, GLCF, Global Land Cover Facility, High performance computing, Indexing, information service, Information services, Institute for Advanced Computer Studies, land cover, NASA, next generation, PACS, Remote sensing, terrain mapping, UMIACS, University of Maryland, User interfaces, web-based interface

A recent initiative by NASA has resulted in the formation of a federation of Earth science data partners. These Earth Science Information Partners (ESIPs) have been tasked with creating novel Earth science data products and services as well as distributing new and existing data sets to the Earth science community and the general public. The University of Maryland established its ESIP activities with the creation of the Global Land Cover Facility (GLCF). This joint effort of the Institute for Advanced Computer Studies (UMIACS) and the Department of Geography has developed an operational data archiving and distribution system aimed at advancing current land cover research efforts. The success of the GLCF is tied closely to assessing user needs as well. As the timely delivery of data products to the research community. This paper discusses the development and implementation of a web-based interface that allows users to query the authors' data holdings and perform user requested processing tasks on demand. The GLCF takes advantage of a scaleable, high performance computing architecture for the manipulation of very large remote sensing data sets and the rapid spatial indexing of multiple format data types. The user interface has been developed with the cooperation of the Human-Computer Interaction Laboratory (HCIL) and demonstrates advances in spatial and temporal querying tools as well as the ability to overlay multiple raster and vector data sets. Their work provides one perspective concerning how critical earth science data may be handled in the near future by a coalition of distributed data centers