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TopoLens: Building a CyberGIS community data service for enhancing the usability of high‐resolution national topographic datasets
Author(s) -
Hu Hao,
Yin Dandong,
Liu Yan Y.,
Terstriep Jeff,
Hong Xingchen,
Wendel Jeff,
Wang Shaowen
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4682
Subject(s) - geospatial analysis , usability , computer science , workflow , supercomputer , service (business) , world wide web , data science , database , remote sensing , human–computer interaction , operating system , geography , economy , economics
Summary 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.