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Fast analysis of upstream features on spatial networks (GIS cup)

Published: 06 November 2018 Publication History

Abstract

We present a fast linear time algorithm that uses a block-cut tree for identifying upstream features from a set of starting points in a network. Our implementation has been parallelized and it can process a dataset with 32 million features in less than 8 seconds on a 8-core workstation. This problem is the 2018 ACM SIGSPATIAL CUP challenge and presents several applications mainly on the field of utility networks. Our code is freely available for nonprofit research and education at https://github.com/sallesviana/FastUpstream

References

[1]
Petko Bakalov, Erik G. Hoel, and Sangho Kim. 2017. A Network Model for the Utility Domain. In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL'17). ACM, New York, NY, USA, Article 32, 10 pages.
[2]
Frank Harary. 1969. Graph Theory. Addison-Wesley, Reading, MA.
[3]
Dev Oliver, Bo Xu, and Yuanyuan Pao. 2018. GISCUP - ACM SIGSPATIAL CUP 2018. (2018). http://sigspatial2018.sigspatial.org/giscup2018 (accessed Aug-2018).
[4]
Robert Tarjan. 1972. Depth-first search and linear graph algorithms. SIAM journal on computing 1, 2 (1972), 146--160.

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  • (2019)ACM SIGSPATIAL cup 2018 - identifying upstream features in large spatial networksSIGSPATIAL Special10.1145/3355491.335549811:1(32-35)Online publication date: 5-Aug-2019

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  1. Fast analysis of upstream features on spatial networks (GIS cup)

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    cover image ACM Conferences
    SIGSPATIAL '18: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
    November 2018
    655 pages
    ISBN:9781450358897
    DOI:10.1145/3274895
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 06 November 2018

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    Author Tags

    1. GISCUP
    2. graph algorithms
    3. parallel programming
    4. spatial networks

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    SIGSPATIAL '18 Paper Acceptance Rate 30 of 150 submissions, 20%;
    Overall Acceptance Rate 220 of 1,116 submissions, 20%

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    • (2019)ACM SIGSPATIAL cup 2018 - identifying upstream features in large spatial networksSIGSPATIAL Special10.1145/3355491.335549811:1(32-35)Online publication date: 5-Aug-2019

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