Publications of Jean-Paul Kasprzyk
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See detailA Built Heritage Information System Based on Point Cloud Data: HIS-PC
Poux, Florent ULiege; Billen, Roland ULiege; Kasprzyk, Jean-Paul ULiege et al

in ISPRS International Journal of Geo-Information (2020), 9(10), 588

The digital management of an archaeological site requires to store, organise, access and represent all the information that is collected on the field. Heritage building information modelling ... [more ▼]

The digital management of an archaeological site requires to store, organise, access and represent all the information that is collected on the field. Heritage building information modelling, archaeological or heritage information systems now tend to propose a common framework where all the materials are managed from a central database and visualised through a 3D representation. In this research, we offer the development of a built heritage information system prototype based on a high-resolution 3D point cloud data set. The particularity of the approach is to consider a user-centred development methodology while avoiding meshing/down-sampling operations. The proposed system is initiated by a close collaboration between multi-modal users (managers, visitors, curators) and a development team (designers, developers, architects). The developed heritage information system permits the management of spatial and temporal information, including a wide range of semantics using relational along with NoSQL databases. The semantics used to describe the artifacts are subject to conceptual modelling. Finally, the system proposes a bi-directional communication with a 3D interface able to stream massive point clouds, which is a big step forward to provide a comprehensive site representation for stakeholders while minimising modelling costs. [less ▲]

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See detailIntegration of multiple sensor data into a 3D GIS for cities monitoring
Kasprzyk, Jean-Paul ULiege; Nys, Gilles-Antoine ULiege; Billen, Roland ULiege

Conference (2019, October 18)

This research is part of a larger project, called “Ecocity Tools”, which aims to establish environment and energy diagnostics for cities at the neighborhood scale. Experts in different fields provide ... [more ▼]

This research is part of a larger project, called “Ecocity Tools”, which aims to establish environment and energy diagnostics for cities at the neighborhood scale. Experts in different fields provide information based on both scientific models (climatology, pollutant dispersions) and sensor data (energetic cadaster, air quality) to a 3D GIS for decision support in urban planning. This paper focuses on two interconnected problematics about the use of GIS in a “Smart City” approach: an appropriate 3D geometric model and the integration of sensor data into this model. As buildings can be equipped by several sensors in multiples locations (rooms, floors, walls, etc), information should be attachable to specific geometric parts (like walls). It is thus important for 3D city models to be adapted to detailed scale levels. Thanks to the consideration of different levels of details (LoD), from buildings footprints (LoD 0) to interiors (LoD 4), the CityGML standard (OGC) can theoretically fit any 3D application. Nevertheless, these data are not always available at very detailed levels. For example, Belgian authorities deliver open data in CityGML LoD 2 (representing buildings as volumes with simplified roof shapes) for important cities like Brussels or Namur. Therefore, this paper proposes a PostGIS data model able to attach information to specific building parts even in poorly detailed city models (LoD 1 or 2). The second part of this research is the implementation of other OGC standards specifically for the visualization of sensor data into a GIS: Sensor Observation Service (SOS) and SensorThings API (STA). As Web Feature Service (WFS) does for geographical features, SOS allows any compatible GIS client to import georeferenced sensor data and metadata through a simple http request (including filters on space, time and other attributes). More recently, STA, in addition to SOS functions, supports JSON format for data exchanges and also provides a “Tasking Part”: the STA server is able to ask sensors and actuators to do specific tasks like “start/stop measurements”. In this research, a SOS server, able to communicate with the 3D GIS, is implemented thanks to the open source tool provided by 52North. [less ▲]

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See detailA Semantic Retrieval System for Remote Sensing Web Platforms
Nys, Gilles-Antoine ULiege; Kasprzyk, Jean-Paul ULiege; Hallot, Pierre ULiege et al

Conference (2019, June 13)

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See detailA Semantic Retrieval System for Remote Sensing Web Platforms
Nys, Gilles-Antoine ULiege; Kasprzyk, Jean-Paul ULiege; Hallot, Pierre ULiege et al

in International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2019, June 05), XLII-2(W13), 1593-1599

This paper proposes a solution to reduce the semantic gap between final users and data/processing providers in a web market place dedicated to remote sensing products. Nowadays, search engine are common ... [more ▼]

This paper proposes a solution to reduce the semantic gap between final users and data/processing providers in a web market place dedicated to remote sensing products. Nowadays, search engine are common tools on the Internet. Users are accustomed to use them and used to get tabular classification of provided answers. These smart agents are set up to answer basic questions using automatic pages redirection or chitchat. In this research, to ensure coherence between user’s requests and platform answers, natural language processing algorithms and knowledge graphs are integrated within a web platform thanks to a NoSQL graph database connected to open thesauri and Geographic Information Systems (GIS). Therefore, the most pertinent services can be proposed based on input sentences including non-technical vocabulary but also geographical components (the user interface includes a text area and an interactive map). While processing chains and remote sensing ontologies were presented in one of our previous studies, this article focuses on natural languages algorithms and knowledge mining. [less ▲]

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See detailTOWARDS AN ONTOLOGY FOR THE STRUCTURING OF REMOTE SENSING OPERATIONS SHARED BY DIFFERENT PROCESSING CHAINS
Nys, Gilles-Antoine ULiege; Kasprzyk, Jean-Paul ULiege; Hallot, Pierre ULiege et al

in International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2018, September 19), XLII(4), 483-490

This paper proposes an ontology to structure and describe processing chains in the remote sensing field. These chains are made up of elementary elements (operations) organized in collections. The ... [more ▼]

This paper proposes an ontology to structure and describe processing chains in the remote sensing field. These chains are made up of elementary elements (operations) organized in collections. The collection notion, including information about order and repeatability of the elements, is widely defined by using the relations between their constituting items and relations to the whole data store. Applications of the ontology are illustrated with web services provided by a platform for users and providers of processing chains. A graphical interface facilitates data integration in a RDF triple store. Thanks to the management of metadata (ISO19115-3), relevant information can be requested by intelligent search engines. Graph analysis, errors management and consistency rules are computed in order to gather coherent information from the different sources. Results of these analyses are then used by machine learning algorithms for new knowledge discovery. [less ▲]

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See detailCoupling an Unstructured NoSQL Database with a Geographic Information System
Holemans, Amandine; Kasprzyk, Jean-Paul ULiege; Donnay, Jean-Paul ULiege

in Rückemann, Claus-Peter; Doytsher, Yerach (Eds.) GEOProcessing 2018. The Tenth International Conference on Advanced Geographic Information (2018, March)

The management of unstructured NoSQL (Not only Structured Query Language) databases has undergone a great development in the last years mainly thanks to Big Data. Nevertheless, the specificity of spatial ... [more ▼]

The management of unstructured NoSQL (Not only Structured Query Language) databases has undergone a great development in the last years mainly thanks to Big Data. Nevertheless, the specificity of spatial information is not purposely taken into account. To overcome this difficulty, we propose to couple a NoSQL database with a spatial Relational Data Base Management System (RDBMS). Exchanges of information between these two systems are illustrated with relevant examples involving spatial queries. The spatial data stored in MongoDB consists of field surveys (points, photos, etc.) and scanned plans, while reference data (cadastre) is recorded in PostGIS. The extensions required to allow this coupling are written in Python. [less ▲]

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See detailEO_Regions_Science: Basic Research in support of EO_Regions!
Orban, Anne ULiege; Barbier, Christian ULiege; Billen, Roland ULiege et al

Conference (2018, January)

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See detailAnalyse de la Mobilité dans les Systèmes d'Information Géographique
Kasprzyk, Jean-Paul ULiege

Conference (2017, November 27)

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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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