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BARTONĚK, D.
Original Title
THE POSSIBILITIES OF BIG GIS DATA PROCESSING ON THE DESKTOP COMPUTERS
Type
conference paper
Language
English
Original Abstract
The paper submits the method how to solve big projects in the sphere of geographic information systems (GIS). Our aim is to answer the question whether we can or cannot solve similar projects on commonly used hardware and software. This method is based on making use of parallelism and optimization of individual processes. The whole GIS project is divided according to the territory principle into the individual projects which can be processed concurrently. In the frame of sub-projects data optimization of main theme is performed. After the finishing of the particular phases of the project a manual check of partial results follows. The final step consists in completing the separate results into common database. The project was solved 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 more than 500 GB. The data analysis was carried out in the special created application in Python language with the support of ESRI libraries and also in ArcGIS 10.0 environment.
Keywords
big data, GIS, optimization, desktop computer
Authors
Released
17. 10. 2016
Publisher
Springer International Publishing AG
Location
Switzerland
ISBN
978-3-3194-5122-0
Book
The Rise of Big Spatial Data
Edition
Lecture Notes in Geoinformation and Cartography
Edition number
1
1863-2351
Periodical
State
Swiss Confederation
Pages from
273
Pages to
287
Pages count
15
URL
http://www.springer.com/gp/book/9783319451220
BibTex
@inproceedings{BUT128928, author="Dalibor {Bartoněk}", title="THE POSSIBILITIES OF BIG GIS DATA PROCESSING ON THE DESKTOP COMPUTERS", booktitle="The Rise of Big Spatial Data", year="2016", series="Lecture Notes in Geoinformation and Cartography", journal="Lecture Notes in Geoinformation and Cartography", number="1", pages="273--287", publisher="Springer International Publishing AG", address="Switzerland", doi="10.1007/978-3-319-45123-7\{_}20", isbn="978-3-3194-5122-0", issn="1863-2351", url="http://www.springer.com/gp/book/9783319451220" }