DBPapers
DOI: 10.5593/SGEM2014/B23/S11.116

TECHNOLOGY OF PROCESSING OF ENORMOUS AMOUNTS OF GEOGRAPHICAL DATA

D. Bartonek,J. Bures, I.Opatrilova
Wednesday 1 October 2014 by Libadmin2014

References: 14th International Multidisciplinary Scientific GeoConference SGEM 2014, www.sgem.org, SGEM2014 Conference Proceedings, ISBN 978-619-7105-12-4 / ISSN 1314-2704, June 19-25, 2014, Book 2, Vol. 3, 917-924 pp

ABSTRACT
The article describes the technology of data analysis of the storage of underground utilities under certain types of terrain surfaces on extensive territories. This analysis was done in order to determine reproductive values of these utilities and the valuation of costs which would be necessary to spend for building new utilities. The process of data analysis that is based on the classification uses raster datasets of orthophoto, vector datasets of Fundamental Base of Geographic Data (ZABAGED) and vector datasets of the route of line of underground engineering networks. The aim is the mining of the maximum information from the raster image of orthophoto and its transfer to the database and vector form. The advantage of technology is a high degree of automation of the whole process and the efficiency of use especially in large areas. The technology was tested in the project of data analysis of storage of gas facilities under certain types of terrain surface in the Czech Republic (CR). The authors solved this project for the GasNet, Ltd. Company which is a part of a RWE group in the Czech Republic. Input data were datasets of orthophoto with a resolution of 25 cm/pixel, layers of communications of ZABAGED CR and vector sets of the route of line of underground engineering networks. Due to the territorial coverage of the CR with the area of 64,350 km2, these were massive tasks with total data volume of 500 GB. The data analysis was carried out in the assigned created application in Python language with support for ESRI libraries and also in ArcGIS 10.0 environment. The results demonstrated the high efficiency of the technology and the low error rate in the range of 2% - 3% was achieved over the whole modeled area.

Keywords: image classification, spatial analysis, GIS,

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