Skip to main content

The Solution of Massive Tasks in GIS Exemplified by Determining Terrain Surface Types Above Gas Pipelines in the Czech Republic

  • Chapter
  • First Online:
Thematic Cartography for the Society

Abstract

The automated creation of cartographic products made with the software tools of geographic information systems (GIS) allow people to solve extensive and complicated tasks. These tasks lead to massive calculations which are very demanding in terms of data preparation, machine time and the memory capacity of hardware. This chapter deals with theoretic analysis of the complexity of tasks and the possibility of optimisation of sub-processes which lead to acceptable solutions. The quality of results achieved is also discussed here. Theoretical assumptions were verified through a data analysis project involving the storage of gas facilities under certain types of surface terrain in the Czech Republic. This analysis was performed in order to determine the re-built costs of gas facilities (pipelines) and the valuation of necessary costs in building new networks. The authors undertook this project for the GasNet, Ltd. Company which is a part of a RWE group in the Czech Republic. The results have general significance for the creation of cartographic products with GIS support.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Bartoněk D, Bureš J (2012) Expert GIS for locating of archaeological sites, 4th International Conference on Cartography & GIS Albena, Bulgaria, June 2012, ISSN 1314-0604

    Google Scholar 

  • Bartoněk D, Opatřilová I (2014) Design of man–machine interface for mobile mapping. Advanced Science Letters, Volume 20, Number 2, pp. 501-504 (4)

    Google Scholar 

  • Bureš J, Bartoněk D, Opatřilová I (2013) Data analysis of surfaces above RWE gas pipelines in the Czech Republic. Project AdMaS ED2.1.00/03.0097 Nr. HS12357021212200. Brno University of Technology, Czech Republic (in Czech)

    Google Scholar 

  • Cheby J, Wang W, Gao R (2012) Massive RDF data complicated query optimization based on MapReduce. Physics Procedia, Volume 25, pp. 1414-1419

    Google Scholar 

  • Chetyrkin K - G, Kühn J - K, Sturm C (2007) Recent progress in computing four-loop massive correlators. Nuclear Physics B - Proceedings Supplements, Volume 164, pp. 203-206

    Google Scholar 

  • Faro A, Giordano D, Majorána F (2011) Mining massive datasets by an unsupervised parallel clustering on a GRID: Novel algorithms and case study. Future Generation Computer Systems, Volume 27, Issue 6, pp. 711-724

    Google Scholar 

  • Forslund D - W, Hansen C, Junker P, John W - S, Tenbrink S, Breton J. (1992) High-speed networks, visualization, and massive parallelism in the Advanced Computing Laboratory. Computing Systems in Engineering, Volume 3, Issues 1–4, pp. 521-524

    Google Scholar 

  • Frache S, Chiabrando D, Graziano M, Vacca M, Boarino L, Zamboni M (2013) Enabling design and simulation of massive parallel nanoarchitectures. Journal of Parallel and Distributed Computing. Vol. 74, Issue 6, pp. 2530–2541

    Google Scholar 

  • Juany B (2011) A Short Note on Data-Intensive Geospatial Computing. in Information Fusion and Geographic Information Systems. Lecture Notes in Geoinformation and Cartography 2011, pp 13-17

    Google Scholar 

  • Juany L, Tang G, Liu X, Song X., Yang J, Liu K (2013) Parallel contributing area calculation with granularity control on massive grid terrain datasets. Computers & Geosciences, Volume 60, pp. 70-80

    Google Scholar 

  • Luo Y – W, Wang X – L, Xu Z - Q (2005) An agent approach to spatial information grid architecture design. Computing and Informatics, Volume: 24, Issue: 2, pp. 201-222

    Google Scholar 

  • Min J, -K; Park H, - H, Chung C - W (2005) Multi-way spatial join selectivity for the ring join graph: Information and Software Technology, Volume: 47, Issue: 12, pp. 785-795, DOI: 10.1016/j.infsof.2005.01.002

  • Park H - H, Min J - K, Chung, C - W, Chány T - G (2004) Multi-way R-tree joins using indirect predicates. Information and Software Technology, Volume 46, Issue 11, pp 739-751

    Google Scholar 

  • Richter R, Döllner J (2013) Concepts and techniques for integration, analysis and visualization of massive 3D point clouds. Computers, Environment and Urban Systems, Volume 45, pp. 114–124

    Google Scholar 

  • Sakellari G, Loukas G (2013) A survey of mathematical models, simulation approaches and testbeds used for research in cloud computing. Simulation Modelling Practice and Theory, Volume 39, pp. 92-103

    Google Scholar 

  • Steinfadt S (2013) Fine-grained parallel implementations for SWAMP+ Smith–Waterman alignment. Parallel Computing, Volume 39, Issue 12, pp. 819-833

    Google Scholar 

  • Sijbers J, den Dekker A – J, Scheunders P, Van Dyck D (1998) Maximum likelihood estimation of Rician distribution parameters. IEEE Transactions on Medical Imaging 17 (3): 357-361. doi:10.1109/42.712125. PMID 9735899

  • Xie Z, Wu L, Ye Z (2008) A Prototype Design of Parallelizing GIS operations. Conference: Geoinformatics 2008 and Joint Conference on GIS and Built Environment - Advanced Spatial Data Models and Analyses Location: Guangzhou, Republic of China, Proceedings of the SPIE, Volume 7146, pp. (2009), article id. 71462F, 9 pp

    Google Scholar 

  • Yang C, Goodchild M, Qunying H (2011) Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing? International Journal of Digital Earth. Volume: 4 Issue: 4, pp. 305-329, Article Number PII 938806602 DOI: 10.1080/17538947.2011.587547

  • Yang D, Feng Y, Juan Y, Han X, Wang J, Li J (2013) Ad-hoc aggregate query processing algorithms based on bit-store for query intensive applications in cloud computing. Future Generation Computer Systems, Volume 29, Issue 7, pp. 1725-1735

    Google Scholar 

  • Wang L, Tao J, Ranjan R, Marten H, Streit A., Chen J, Chen D (2013) G-Hadoop: MapReduce across distributed data centers for data-intensive computing. Future Generation Computer Systems, Volume 29, Issue 3, pp. 739-750

    Google Scholar 

  • Weiss B, Bailey M (2011) Massive Parallel Computing to Accelerate Genome-Matching. GPU Computing, Gems NVIDIA Press, pp. 173-184, DOI: 10.1016/B978-0-12-384988-5.00012-7

  • Wen, J., Ma, Y., Liu, P., Sun, S. (2013). Distributed multipliers in MWM for analyzing job arrival processes in massive HPC workload datasets. Future Generation Computer Systems, ELSEVIER, http://dx.doi.org/10.1016/j.future.2013.12.009

  • Zhang W, Zhao M, Tu Z, Lou S (2011) Research and Implement of Distributed Nodes Collaboration-Based Management and Publishing Technologies for Massive Geospatial Information. Massive Computing. Advances in Intelligent and Soft Computing 2011 Vol. 112, pp. 391-400

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Irena Opatřilová .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Bartoněk, D., Bureš, J., Opatřilová, I. (2014). The Solution of Massive Tasks in GIS Exemplified by Determining Terrain Surface Types Above Gas Pipelines in the Czech Republic. In: Bandrova, T., Konecny, M., Zlatanova, S. (eds) Thematic Cartography for the Society. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-08180-9_8

Download citation

Publish with us

Policies and ethics