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- W2892275325 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." @default.
- W2892275325 created "2018-09-27" @default.
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- W2892275325 date "2018-01-01" @default.
- W2892275325 modified "2023-09-28" @default.
- W2892275325 title "Towards a Compact Representation of Temporal Rasters" @default.
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- W2892275325 doi "https://doi.org/10.1007/978-3-030-00479-8_10" @default.
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