A GIS-based management and publication framework for data handling of numerical model results

Yu, Jianjun; Qin, Xiaosheng; Larsen, Laurine; Larsen, Øystein; Jayasooriya, Adeesha; Shen, Xizhong

doi:10.1016/j.advengsoft.2011.10.010

Cited by 10 publications

(2 citation statements)

References 16 publications

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“…The services they provide include the provision of resources for processing large datasets, the automatizing of processing tasks, the reuse of algorithms, the modeling and documentation of workflows. Among others, the following advantages of online geoprocessing environments have been documented: the integration of heterogeneous data and services [21]; faster update cycles [22]; the use of open-source software to make systems cost-effective [22]; grid technology and cloud technology supporting the development of low-cost, scalable and efficient systems [23,24]; and the reuse of existing services for reducing development time [25].…”

Section: E-science and The Geographic Information Domainmentioning

confidence: 99%

Geospatial Cyberinfrastructure and Geoprocessing Web—A Review of Commonalities and Differences of E-Science Approaches

Hofer

2013

IJGI

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Online geoprocessing gains momentum through increased online data repositories, web service infrastructures, online modeling capabilities and the required online computational resources. Advantages of online geoprocessing include reuse of data and services, extended collaboration possibilities among scientists, and efficiency thanks to distributed computing facilities. In the field of Geographic Information Science (GIScience), two recent approaches exist that have the goal of supporting science in online environments: the geospatial cyberinfrastructure and the geoprocessing web. Due to its historical development, the geospatial cyberinfrastructure has strengths related to the technologies required for data storage and processing. The geoprocessing web focuses on providing components for model development and sharing. These components shall allow expert users to develop, execute and document geoprocessing workflows in online environments. Despite this difference in the emphasis of the two approaches, the objectives, concepts and technologies they use overlap. This paper provides a review of the definitions and representative implementations of the two approaches. The provided overview clarifies which aspects of e-Science are highlighted in approaches differentiated in the geographic information domain. The discussion of the two approaches leads to the conclusion that synergies in research on e-Science environments shall be extended. Full-fledged e-Science environments will require the integration of approaches with different strengths.

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Section: E-science and The Geographic Information Domainmentioning

confidence: 99%

Geospatial Cyberinfrastructure and Geoprocessing Web—A Review of Commonalities and Differences of E-Science Approaches

Hofer

2013

IJGI

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“…Works on visualisation systems and on sharing the results of the simulations with GIS environment have been carried out for a long time (e.g. : Clark, 1998;Ng et al, 2009Ng et al, , 2007Vivoni and Richards, 2005;Yu et al, 2012). In order to integrate a hydrodynamic model with the GIS system, it is necessary to match the method of geospatial data representation to the way in which the simulation is implemented, as well as to standardise the data and optimise the calculations.…”

Section: Motivationmentioning

confidence: 99%

3d Gis for Flood Modelling in River Valleys

Tymków¹,

Karpina²,

Borkowski³

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The objective of this study is implementation of system architecture for collecting and analysing data as well as visualizing results for hydrodynamic modelling of flood flows in river valleys using remote sensing methods, tree-dimensional geometry of spatial objects and GPU multithread processing. The proposed solution includes: spatial data acquisition segment, data processing and transformation, mathematical modelling of flow phenomena and results visualization. Data acquisition segment was based on aerial laser scanning supplemented by images in visible range. Vector data creation was based on automatic and semiautomatic algorithms of DTM and 3D spatial features modelling. Algorithms for buildings and vegetation geometry modelling were proposed or adopted from literature. The implementation of the framework was designed as modular software using open specifications and partially reusing open source projects. The database structure for gathering and sharing vector data, including flood modelling results, was created using PostgreSQL. For the internal structure of feature classes of spatial objects in a database, the CityGML standard was used. For the hydrodynamic modelling the solutions of Navier-Stokes equations in two-dimensional version was implemented. Visualization of geospatial data and flow model results was transferred to the client side application. This gave the independence from server hardware platform. A real-world case in Poland, which is a part of Widawa River valley near Wroclaw city, was selected to demonstrate the applicability of proposed system.

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An integrated environmental decision support system for water pollution control based on TMDL – A case study in the Beiyun River watershed

Zhang

et al. 2015

Journal of Environmental Management

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A GIS-based management and publication framework for data handling of numerical model results

Cited by 10 publications

References 16 publications

Geospatial Cyberinfrastructure and Geoprocessing Web—A Review of Commonalities and Differences of E-Science Approaches

Geospatial Cyberinfrastructure and Geoprocessing Web—A Review of Commonalities and Differences of E-Science Approaches

3d Gis for Flood Modelling in River Valleys

An integrated environmental decision support system for water pollution control based on TMDL – A case study in the Beiyun River watershed

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