GWASS: GRASS web application software system based on the GeoBrain web service

  • Authors:

  • Fang Qiu;Feng Ni;Bryan Chastain;Haiting Huang;Peisheng Zhao;Weiguo Han;Liping Di

  • Affiliations:

  • Geospatial Information Sciences, University of Texas at Dallas, Richardson, TX, USA;Geospatial Information Sciences, University of Texas at Dallas, Richardson, TX, USA;Geospatial Information Sciences, University of Texas at Dallas, Richardson, TX, USA;Geospatial Information Sciences, University of Texas at Dallas, Richardson, TX, USA;Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA;Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA;Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA

  • Venue:
  • Computers & Geosciences
  • Year:
  • 2012

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Abstract

GRASS is a well-known geographic information system developed more than 30 years ago. As one of the earliest GIS systems, GRASS has currently survived mainly as free, open-source desktop GIS software, with users primarily limited to the research community or among programmers who use it to create customized functions. To allow average GIS end users to continue taking advantage of this widely-used software, we developed a GRASS Web Application Software System (GWASS), a distributed, web-based, multi-tiered Geospatial Information System (GIS) built on top of the GeoBrain web service, a project sponsored by NASA using the latest service oriented architecture (SOA). This SOA enabled system offers an effective and practical alternative to current commercial desktop GIS solutions. With GWASS, all geospatial processing and analyses are conducted by the server, so users are not required to install any software at the client side, which reduces the cost of access for users. The only resource needed to use GWASS is an access to the Internet, and anyone who knows how to use a web browser can operate the system. The SOA framework is revitalizing the GRASS as a new means to bring powerful geospatial analysis and resources to more users with concurrent access.