TopoLens: Building a cyberGIS community data service for enhancing the usability of high-resolution National Topographic datasets
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Abstract
Geospatial data, often embedded with geographic references, are important to many application and science domains, and represent a major type of big data. The increased volume and diversity of geospatial data have caused serious usability issues for researchers in various scientific domains, which call for innovative cyberGIS solutions. To address these issues, this paper describes a cyberGIS community data service framework to facilitate geospatial big data access, processing, and sharing based on a hybrid supercomputer architecture. Through the collaboration between the CyberGIS Center at the University of Illinois at Urbana-Champaign (UIUC) and the U.S. Geological Survey (USGS), a community data service for accessing, customizing, and sharing digital elevation model (DEM) and its derived datasets from the 10-meter national elevation dataset, namely TopoLens, is created to demonstrate the workflow integration of geospatial big data sources, computation, analysis needed for customizing the original dataset for end user needs, and a friendly online user environment. TopoLens provides online access to precomputed and on-demand computed high-resolution elevation data by exploiting the ROGER supercomputer. The usability of this prototype service has been acknowledged in community evaluation.
| Publication type | Conference Paper |
|---|---|
| Publication Subtype | Conference Paper |
| Title | TopoLens: Building a cyberGIS community data service for enhancing the usability of high-resolution National Topographic datasets |
| DOI | 10.1145/2949550.2949652 |
| Year Published | 2016 |
| Language | English |
| Publisher | ACM |
| Contributing office(s) | Center for Geospatial Information Science (CEGIS) |
| Description | 8 p. |
| Larger Work Type | Book |
| Larger Work Subtype | Conference publication |
| Larger Work Title | Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale |
| Google Analytic Metrics | Metrics page |