University of Twente Student Theses


Facilitating real-time inundation prediction using geo web services

Obi, Kingsley Nnaemeka (2012) Facilitating real-time inundation prediction using geo web services.

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Abstract:Real time inundation prediction is a challenge in many areas in the world which lack sufficient data. Such challenging scenarios are the July 2010 Pakistan flood, the May 2011 Colombian flood and the October 2011 Thailand floods. In these cases, future flood extents could not be predicted from the current flood extents and timely information could not passed in a consistent manner. Thereby leading to losses of lives and properties. Effective prediction of real time inundation is a very time and data consuming process for flood modelers. The recent development in web technology, standards and protocols could make predictions faster in these data scarce regions. This research involves exploring the use of web service for inundation prediction modeling since nowadays large amounts of geospatial data (raster and vector) are available on the internet as web services. Presently, there are two major web standard protocols for sharing remote sensing and gridded data. The Open-source Project for a Network Data Access Protocol (OPeNDAP) used largely by the Earth Science (ES) communities and the Open Geospatial Consortium’s (OGC) Web Coverage Service (WCS) standard used mainly by the GIS communities. For the discovery of these data, both ES and GIS communities adopts different catalogue standards. ES community use the Thematic Realtime Environmental Distributed Data Services (THREDDS) as catalogue service for the discovery of data. Similarly, the OGC’s Catalogue Service for Web (CS/W) designed to support the registry and discovery of geospatial information is used by the GIS communities. There is a need to use data discovered from both catalogues for timely inundation prediction modeling. But there are challenges in interoperable access of metadata between both communities. Two experiments were conducted. The first, was done by implementing a unified data discovery mechanism by harvesting THREDDS dataset records into GeoNetwork CS/W. Thereby creating a rich metadata for datasets used for inundation prediction modeling from both the ES and GIS communities. The experiment also focused on the problems faced in harvesting THREDDS records into GeoNetwork and discussed solutions to such problems. The second experiment involved retrieving dataset after they have been found from the data discovery mechanism. We designed a three-tier stand-alone prototype web service which retrieved datasets based on the access URL and bounding box given by the user. The experiment accessed both OPeNDAP and WCS servers using open source python libraries Pydap and OWSLib respectively as clients to these servers. Both experiments formed an integral part of a loosely coupled prototype web service infrastructure, that could facilitate the consistent discovery and access to datasets required as inputs in hydrodynamic models for inundation prediction modeling. The datasets gotten the web service infrastructure was visualized using client software, so users could access its applicability based on the quality of datasets for inundation prediction modeling. The infrastructure was partially evaluated, with each component evaluated as a separate unit using certain criteria like spatial and temporal subsetting. But this infrastructure equally had its limitations. In all, these experiments served as a proof of concept demonstration that would enable flood modelers (users) further explore the accuracy and suitability of data gotten from these web services for inundation prediction modeling. Keywords WCS, OPeNDAP, THREDDS, CS/W, Web services (geo web services), Inundation prediction, hydro-dynamic model, inundation prediction modeling (flood extent modeling
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
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