References of "Kasprzyk, Jean-Paul"
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See detailBig Data and Geomatics - Towards a new paradigm in spatial information management
Kasprzyk, Jean-Paul ULiege; Hallot, Pierre ULiege

Conference (2017, November 17)

Big Data and Geomatics : towards a new paradigm in spatial information management During the last decade, the technological advances allowed a massive acquisition of digital data whose volume grows ... [more ▼]

Big Data and Geomatics : towards a new paradigm in spatial information management During the last decade, the technological advances allowed a massive acquisition of digital data whose volume grows exponentially. Going from location-based social networks to smartphones, users produce huge amounts of data that are located in space and time. The various exploitations of these large and heterogeneous datasets have created a new field called “Big Data”. As most of these data are characterized by spatial and temporal components, it has become the next challenge to handle for geomatics researchers within the next incoming year. In this presentation, we provide an overview of the main domains in geomatics that are impacted by big data. Related fields are among other things: terrestrial spatial data acquisition where the rise of powerful laser scanners, that can acquire millions of points per second in order to precisely represent built heritage in 3D, revolutionized topography; Global Navigation Satellite Systems (GNSS), powered by the European constellation Galileo, imply original researches able to increase the position accuracy of a simple smartphone user; remote sensing is now enriched by a wide open access capability thanks to Copernicus satellites which provide timely information for the management of the environment. In order to effectively manage and analyse information related to each of these revolutions, Geographical Information System (GIS) research uses innovative data storage strategies based on CityGML for 3D data, semantic web linked-data and non-structured databases (NoSQL) for the integration of heterogeneous information, data warehouses and OnLine Analytical Processing (OLAP) for decision support. The presentation is based on concrete applications about smart cities, remote sensing, firefighting… [less ▲]

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See detailLiDAR aérien et autres nuages de points pour la cartographie multi-échelles
Poux, Florent ULiege; Neuville, Romain ULiege; Kasprzyk, Jean-Paul ULiege et al

Conference (2017, September 12)

Utilisation de nuage de points pour la cartographie 3D multi-échelles. Exemples d'utilisation et définition de workflows pour assurer l'interopérabilité lors de la fusion de données issues de différents ... [more ▼]

Utilisation de nuage de points pour la cartographie 3D multi-échelles. Exemples d'utilisation et définition de workflows pour assurer l'interopérabilité lors de la fusion de données issues de différents capteurs. [less ▲]

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See detailSpatial OnLine Analytical Processing Applied to Cities Security with Raster Data - A Case Study on Emergency Services of Brussels Agglomeration
Kasprzyk, Jean-Paul ULiege; Devillet, Guénaël ULiege

Conference (2017, June 29)

Public institutions in charge of cities security are confronted to always more complex and voluminous data. In particular, georeferenced data can be extracted from many sources: mobile phones, social ... [more ▼]

Public institutions in charge of cities security are confronted to always more complex and voluminous data. In particular, georeferenced data can be extracted from many sources: mobile phones, social media, cars, security camera, satellite images, crowdsourcing, geography portals, etc. Uses of these data are various. For instance, it is very precious to firefighters in order to fairly distribute their resources (equipment and men) on the territory. These large spatial data sets (“Big Data”) require powerful tools for their extraction and their analysis. For this purpose, an original Spatial OnLine Analytical Processing (SOLAP) model is developed for emergency services. A case study involving firefighters and medical aids of Brussels is presented [less ▲]

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See detailA Raster SOLAP Designed for the Emergency Services of Brussels Agglomeration
Kasprzyk, Jean-Paul ULiege; Donnay, Jean-Paul ULiege

in CLOUD COMPUTING 2017 - The Eighth International Conference on Cloud Computing, GRIDs, and Virtualization (2017, February 20)

In order to quickly reach incident locations, emergency services have to fairly distribute their resources on the territory. This distribution is based on an analysis which depends on heterogeneous ... [more ▼]

In order to quickly reach incident locations, emergency services have to fairly distribute their resources on the territory. This distribution is based on an analysis which depends on heterogeneous spatial data like past interventions (recurring risk), specific geographical places (sporadic risk), road network or socio-economic variables. On the other hand, Spatial Online Analytical Processing (SOLAP) tools are designed for the collection and the analysis of large spatial data sets. In this study, an original raster SOLAP model is implemented for emergency services of Brussels agglomeration. It allows decision-makers to freely generate risk maps (continuous fields), depending on several dimensions (time, intervention type, risk type, etc.), and to compare them with the accessibility of firefighters and ambulances. Simulations can also be performed on resources locations to see their impact on the main accessibility. [less ▲]

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See detailAnalyse de Risque SIAMU
Kasprzyk, Jean-Paul ULiege

Software (2017)

The tool allows users from SIAMU to generate different risk maps based on past interventions (recurring risk), punctual risk (schools, hospitals, etc.) and the accessibility of SIAMU resources ... [more ▼]

The tool allows users from SIAMU to generate different risk maps based on past interventions (recurring risk), punctual risk (schools, hospitals, etc.) and the accessibility of SIAMU resources (firestations and ambulance departures). This decision support tool helps SIAMU to fairly distribute their resources In Brussels agglomeration. [less ▲]

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See detailA Raster SOLAP for the Visualization of Crime Data Fields
Kasprzyk, Jean-Paul ULiege; Donnay, Jean-Paul ULiege

in Rückemann, Claus-Peter (Ed.) GEOProcessing 2016 (2016, April 19)

In order to effectively extract synthetic information from large spatial data sets, Spatial OnLine Analytical Processing (SOLAP) combines Geographic Information Systems (GIS) with Business Intelligence ... [more ▼]

In order to effectively extract synthetic information from large spatial data sets, Spatial OnLine Analytical Processing (SOLAP) combines Geographic Information Systems (GIS) with Business Intelligence (BI) to query data warehouses through interactive vector maps. On the other hand, crime strategical analysis is usually based on raster maps computed by Kernel Density Estimation (KDE), then independent of any artificial boundary. This paper introduces an alternative vision of SOLAP which uses the raster model (instead of the vector one) in order to integrate crime data fields computed by KDE. It allows a continuous visualization of spatial data which, until now, has not been compatible with other SOLAP tools. The original geo-model is validated by a prototype adapted to the police needs. [less ▲]

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See detailRaster Data Cube
Kasprzyk, Jean-Paul ULiege

Software (2015)

Prototype SOLAP développé dans le cadre d'une thèse doctorat intitulée "Intégration de la Continuité Spatiale dans la Structure Multidimensionnelle d'un Entrepôt de Données". Cet outil permet une ... [more ▼]

Prototype SOLAP développé dans le cadre d'une thèse doctorat intitulée "Intégration de la Continuité Spatiale dans la Structure Multidimensionnelle d'un Entrepôt de Données". Cet outil permet une navigation multidimensionnelle dans des cubes de données spatiales exploitant le format raster (contrairement aux outils SOLAP classiques exploitant le format vectoriel). L'outil est accessible en ligne et propose plusieurs jeux de données liés au domaine de la cartographie criminelle ("crime mapping"): http://nolap01.ulg.ac.be/rastercube/ [less ▲]

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

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 ULiege

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 detailPractical teaching of GIS at University of Liège
Kasprzyk, Jean-Paul ULiege

Conference (2013, May 24)

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

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 detailReconstitution of the Journeys to Crime and Location of Their Origin in the Context of a Crime Series. A Raster Solution for a Real Case Study
Kasprzyk, Jean-Paul ULiege; Trotta, Marie ULiege; Donnay, Jean-Paul ULiege et al

in Leitner, Michael (Ed.) Crime Modeling and Mapping Using Geospatial Technologies (2012)

In the region of Charleroi (Belgium), a series of criminal acts were committed by the same group, using the same vehicle. The events were located in space and time. The car used during these criminal ... [more ▼]

In the region of Charleroi (Belgium), a series of criminal acts were committed by the same group, using the same vehicle. The events were located in space and time. The car used during these criminal activities was stolen (first event) and was later retrieved (last event) after a period of 4 days of offences. Police recorded a crucial clue: the total mileage covered by the vehicle between the first and the last event was estimated with an admissible approximation. Thanks to this information, we were able to choose the most probable journey-to-crime among several scenarios. These depended on the combination of cost surfaces built with distance propagation algorithms starting from each criminal event in raster mode. The distance propagations were limited to the road network and the combinations of the cost surfaces had to respect the chronology of the facts. The most plausible scenario suggested that the criminals hided the car into a withdrawal site between their activities. In order to improve the precision of the location of this withdrawal site, we used a multi-criteria analysis taking account of the journey of the vehicle and other environment variables. At the end of these treatments, the small stretch of road that we isolated actually included the withdrawal site, as confirmed by the police later [less ▲]

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

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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