Publications of Jean-Paul Kasprzyk
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See detailIntégration de la continuité spatiale dans la structure multidimensionnelle d’un entrepôt de données - SOLAP raster
Kasprzyk, Jean-Paul ULg

Doctoral thesis (2015)

Technological advances in recent decades have created a massive acquisition of digital data whose volume grows exponentially. To efficiently extract the information they contain, powerful tools have been ... [more ▼]

Technological advances in recent decades have created a massive acquisition of digital data whose volume grows exponentially. To efficiently extract the information they contain, powerful tools have been developed to collect, store and analyze these data. These tools are gathered in a discipline called “business intelligence”. Among them, data warehouses are responsible for archiving data by structuring them in a multidimensional way (time, space or others). They are called data hypercubes or data cubes when they are limited to three dimensions. Hypercubes can supply OLAP (On Line Analytical Processing) systems that aim at quickly synthesizing information in interactive tables and charts for decision-makers from various fields: marketing, environment, criminology, etc. Thus, users can navigate into hypercubes using OLAP operations such as slicing on dimension members (e.g. data aggregation for the month of January in the time dimension), or drilling into hierarchies (e.g. switching from the “year” level to the “month” level in the time dimension). When OLAP is coupled with spatial analysis techniques supplied by geographic information systems (GIS), a map interface then improves the exploration of data: OLAP operations can be applied to dimensions defined in the geographical space (spatial drilling or spatial slicing). This kind of tool is called SOLAP (Spatial OLAP). SOLAP tools currently available on the market all suffer from the same deficiency: they are unable to represent spatial dimensions (X, Y) in a continuous way. This representation is nevertheless essential for the management of spatially continuous phenomena (temperature, pollution, etc.) but also for visualizing spatially discrete events (product sales, crimes, etc.) while minimizing the Modifiable Areal Unit Problem (MAUP). This kind of visualization is used especially by the police to predict the location of future crimes through hotspot maps which are generated by the Kernel Density Estimation (KDE) method. In the field of GIS, raster data (as opposed to vector data) enable effective representation of spatial continuity through digital georeferenced grids. Whereas current SOLAP tools only consider vector data, our research uses the raster model to integrate spatial continuity into the multidimensional structure of a data warehouse feeding a SOLAP ("raster SOLAP"). Despite its underutilization in the SOLAP literature, the raster model has many similarities with a particular kind of data cube: the MOLAP cube (Multidimensional OLAP). Like a satellite image (raster) representing the two planimetric spatial dimensions and one "spectral band" dimension, a MOLAP cube is a three dimensional array whose cells’ coordinates (similar to raster pixels) enable an efficient indexation of dimensions’ members (describing the analyzed facts). In a first original model that we call "raster cube" we define the bases for a three-dimensional raster SOLAP, starting from the definition of a MOLAP cube. Unlike vector SOLAP - where spatiality is attached to a semantic dimension through pointers to geometries - our model directly integrates spatial dimensions (X, Y) in the multidimensional structure of the data warehouse. With this original feature, any geographical entity (country, building, road, etc.) can be imported on the fly as a member in the analysis of the user, which is hardly possible with conventional vector SOLAP tools. An extension of this SOLAP model, called "raster hypercube", is then developed by entrusting the management of extra non-spatial dimensions to a relational database management system (Relational OLAP or ROLAP). The raster hypercube is then populated by KDE raster fields representing crime densities, which are defined in a continuous space (raster dimensions) through time and crime types (ROLAP dimensions). Our model is able to combine the production of hotspot maps at different scales of analysis with SOLAP navigation operations: slicing on spatial or non-spatial members, and drilling into the hierarchy of spatial or non-spatial dimensions. Our raster hypercube model is validated by an operating prototype which is based on open source tools only. Several datasets are integrated through KDE fields, including crime data from London and Seattle. At the end of our work, the results of a comparative study between raster SOLAP and vector SOLAP demonstrate that hybrid vector/raster SOLAP architectures present the same interest for spatial data as hybrid ROLAP/MOLAP architectures do for purely semantic data (management of detailed hypercubes [less ▲]

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See detailPrototype SOLAP appliqué sur des champs continus en mode raster. Analyse de hot spots de criminalité.
Kasprzyk, Jean-Paul ULg

Conference (2014, November 24)

SOLAP (Spatial OnLine Analytical Processing) is a server which allows decision makers to quickly analyze archived data from a spatial datawarehouse. Until now, most of SOLAP tools only manage spatial data ... [more ▼]

SOLAP (Spatial OnLine Analytical Processing) is a server which allows decision makers to quickly analyze archived data from a spatial datawarehouse. Until now, most of SOLAP tools only manage spatial data through the vector mode. However, some visualization techniques use interpolation to transform them into continuous fields in raster mode. Crime hotspot mapping is one of them: data are modeled in raster with a KDE (Kernel Density Estimation) algorithm to offer a spatially continuous visualization of crimes. This research aims at combining hotspot mapping and SOLAP. First, we adapt SOLAP to continuous fields with a raster multidimensional data model. Then the raster model is adapted to KDE. The data model is validated with a prototype including London crime data. [less ▲]

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See detailMéthodologie de recherche en cartographie criminelle
Donnay, Jean-Paul ULg; Trotta, Marie ULg; Kasprzyk, Jean-Paul ULg

Scientific conference (2013, April 26)

Presentation of the original research methods conducted by the Geomatics unit of the University of Liege, on environmental criminology, geographic profiling, and business intelligence in crime mapping.

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See detailSpatial data warehouses and SOLAP: a new GIS technology
Kasprzyk, Jean-Paul ULg

Scientific conference (2011, October 14)

Multiplication, both in number and variety of databases in recent decades is a potential bottleneck in the process of decision making. Therefore, data warehouses and OLAP (Online Analytical Processing ... [more ▼]

Multiplication, both in number and variety of databases in recent decades is a potential bottleneck in the process of decision making. Therefore, data warehouses and OLAP (Online Analytical Processing) were born respectively to archive and analyse these data at different levels of aggregation. SOLAP (Spatial OLAP) is a technology that combines OLAP and GIS techniques for spatial data. This presentation will discuss the various tools (particularly open source tools) and approaches in this new domain of geomatics. [less ▲]

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See detailConception d'un entrepôt de données géographiques comme outil d'aide à l'analyse criminelle
Kasprzyk, Jean-Paul ULg

Scientific conference (2010, October)

After describing the data used by belgian federal police for criminal analysis, we justify the utility of a spatial data warehouse for the integration and the exploitation of the data: spatial online ... [more ▼]

After describing the data used by belgian federal police for criminal analysis, we justify the utility of a spatial data warehouse for the integration and the exploitation of the data: spatial online analytical processing (SOLAP) and data mining. [less ▲]

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See detailA Geocodification for 3D objects terrestrial surveys
Kasprzyk, Jean-Paul ULg; Billen, Roland ULg

in Neutens, Tijs; De Ryck, Marijke; De Maeyer, Philippe (Eds.) Proceedings of the 4th International Workshop on 3D Geo-information (2009, November)

Nowadays, mean 3D data aquisition techniques are photogrammetry and laserscanning. Their advantage is the huge amount of points that can be measured in a very short time on the field. Nevertheless, the ... [more ▼]

Nowadays, mean 3D data aquisition techniques are photogrammetry and laserscanning. Their advantage is the huge amount of points that can be measured in a very short time on the field. Nevertheless, the post-processing associated to these techniques allowing to build a real 3D model from the clouds of points is very long. Therefore, we developed a geocodification ("field to finish") for the 3D data acquisition at a low and/or middle level of details. Despite each point is measured one by one with a total station, the user can gain a lot of time because of the almost-absence of post processing. This paper shows some of the developed techniques and tries to demonstrate the possible complementarity between geocodification, laserscanning and photogrammtry. [less ▲]

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See detailDéveloppement d'une Géocodification 3D pour la modélisation du bâti
Kasprzyk, Jean-Paul ULg

Master's dissertation (2008)

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