40 research outputs found
Towards a compact representation of temporal rasters
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 k^2 raster. 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.Comment: This research has received funding from the European Union's Horizon
2020 research and innovation programme under the Marie Sklodowska-Curie
Actions H2020-MSCA-RISE-2015 BIRDS GA No. 690941. Published in SPIRE 201
Space- and Time-Efficient Storage of LiDAR Point Clouds
LiDAR devices obtain a 3D representation of a space. Due to the large size of
the resulting datasets, there already exist storage methods that use
compression and present some properties that resemble those of compact data
structures. Specifically, LAZ format allows accesses to a given datum or
portion of the data without having to decompress the whole dataset and provides
indexation of the stored data. However, LAZ format still have some drawbacks
that should be faced. In this work, we propose a new compact data structure for
the representation of a cloud of LiDAR points that supports efficient queries,
providing indexing capabilities that are superior to those of LAZ format.Comment: This research has received funding from the European Union's Horizon
2020 research and innovation programme under the Marie Sk{\l}odowska-Curie
Actions H2020-MSCA-RISE-2015 BIRDS GA No. 69094