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Towards a Compact Representation of Temporal Rasters

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String Processing and Information Retrieval (SPIRE 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11147))

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Abstract

Big research efforts have been devoted to efficiently manage spatio-temporal data. However, most works focused on vectorial data, and much less, on raster data. This work presents a new representation for raster data that evolve along time named Temporal \(\mathsf {k^2raster} \). It faces the two main issues that arise when dealing with spatio-temporal data: the space consumption and the query response times. It extends a compact data structure for raster data in order to manage time and thus, it is possible to query it directly in compressed form, instead of the classical approach that requires a complete decompression before any manipulation. In addition, in the same compressed space, the new data structure includes two indexes: a spatial index and an index on the values of the cells, thus becoming a self-index for raster data.

Funded in part by European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 690941 (project BIRDS); by Xunta de Galicia/FEDER-UE [CSI: ED431G/01 and GRC: ED431C 2017/58]; by MINECO-AEI/FEDER-UE [Datos 4.0: TIN2016-78011-C4-1-R; Velocity: TIN2016-77158-C4-3-R; and ETOME-RDFD3: TIN2015-69951-R]; and by MINECO-CDTI/FEDER-UE [INNTERCONECTA: uForest ITC-20161074].

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Notes

  1. 1.

    http://www.opengeospatial.org/standards/netcdf.

  2. 2.

    From now on, asume \(rank_b(B,i)\) returns the number of bits set to b in \(B[0,i-1]\), and \(rank_b(B,0)=0\). Note that the first index of T, eqB, Lmax, and Lmin is 0.

  3. 3.

    Since in \(\mathsf {k^2raster'} \) we have to deal both with positive and negative values, we actually apply a zig-zag encoding for the gaps \((max_t -max_s)\).

  4. 4.

    https://gitlab.lbd.org.es/fsilva/k2-raster.

  5. 5.

    https://www.unidata.ucar.edu/software/netcdf/.

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Authors and Affiliations

  1. Fac. Informática, CITIC, Universidade da Coruña, A Coruña, Spain

    Ana Cerdeira-Pena, Guillermo de Bernardo, Antonio Fariña, José Ramón Paramá & Fernando Silva-Coira

  2. Enxenio S.L., A Coruña, Spain

    Guillermo de Bernardo

Authors
  1. Ana Cerdeira-Pena
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  2. Guillermo de Bernardo
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  3. Antonio Fariña
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  4. José Ramón Paramá
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  5. Fernando Silva-Coira
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Corresponding author

Correspondence to José Ramón Paramá .

Editor information

Editors and Affiliations

  1. Diego Portales University, Santiago, Chile

    Travis Gagie

  2. The University of Melbourne, Melbourne, VIC, Australia

    Alistair Moffat

  3. University of Chile, Santiago, Chile

    Gonzalo Navarro

  4. Universidad de Ingeniería y Tecnología, Lima, Peru

    Ernesto Cuadros-Vargas

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Cerdeira-Pena, A., de Bernardo, G., Fariña, A., Paramá, J.R., Silva-Coira, F. (2018). Towards a Compact Representation of Temporal Rasters. In: Gagie, T., Moffat, A., Navarro, G., Cuadros-Vargas, E. (eds) String Processing and Information Retrieval. SPIRE 2018. Lecture Notes in Computer Science(), vol 11147. Springer, Cham. https://doi.org/10.1007/978-3-030-00479-8_10

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  • DOI: https://doi.org/10.1007/978-3-030-00479-8_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00478-1

  • Online ISBN: 978-3-030-00479-8

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