TopoLens: Building a CyberGIS community data service for enhancing the usability of high-resolution national topographic datasets

Hao Hu, Dandong Yin, Yan Y. Liu, Jeff Terstriep, Xingchen Hong, Jeff Wendel, Shaowen Wang

Research output: Contribution to journalArticlepeer-review

Abstract

In recent years, geospatial data have exploded to massive volume and diversity and subsequently cause serious usability issues for researchers in various scientific areas. This paper describes a cyberGIS community data service framework to facilitate geospatial big data access, processing, and sharing based on a hybrid supercomputer architecture. Specifically, the framework aims to enhance the usability of national elevation dataset released by the U.S. Geological Survey in the contiguous United States at the resolution of 1/3 arc-second. A community data service, namely TopoLens, is created to demonstrate the workflow integration of national elevation dataset and the associated computation and analysis. Two user-friendly environments, including a publicly available web application and a private workspace based on the Jupyter notebook, are provided for users to access both precomputed and on-demand computed high-resolution elevation data. The system architecture of TopoLens is implemented by exploiting the ROGER supercomputer, the first cyberGIS supercomputer dedicated to geospatial problem-solving. The usability of TopoLens has been acknowledged in the topographic user community evaluation.

Original languageEnglish (US)
Article numbere4682
JournalConcurrency Computation
Volume31
Issue number16
DOIs
StatePublished - Aug 25 2019

Keywords

  • CyberGIS
  • geospatial big data
  • microservices
  • science gateway
  • topographic data

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computer Science Applications
  • Computer Networks and Communications
  • Computational Theory and Mathematics

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