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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Towards a Compact Representation of Temporal Rasters
verfasst von : Ana Cerdeira-Pena, Guillermo de Bernardo, Antonio Fariña, José Ramón Paramá, Fernando Silva-Coira
Erschienen in: String Processing and Information Retrieval
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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.