Jacques Gautier - GrAPHiST, Une approche d’analyse exploratoire pour l’identification des dynamiques des phénomènes spatio-temporels

Organized by: 
Jacques Gautier
Jacques Gautier


Composition du jury :

  • Mme Anne Ruas, directrice de recherche HDR à l'IFSTTAR, rapporteure 
  • M. Christophe Claramunt , professeur HDR à l'École navale, rapporteur 
  • Mme Luciana Nedel, professeure à l'Université Fédérale du Rio Grande do Sul (UFRGS), examinatrice
  • M. Didier Josselin, directeur de recherche HDR au CNRS (UMR ESPACE), examinateur
  • Mme Paule-Annick Davoine, professeure HDR à l'Université Grenoble Alpes, directrice de thèse
  • Mme Claire Cunty, maître de conférences à l'Université Lumière-Lyon-II, co-encadrante de thèse


Datasets allowing the description of spatio-temporal phenomena are becoming ever more numerous. These new data can be very different from those usually observed for studying spatio-temporal phenomena. An analysis through a hypothetic-deductive approach, like is mainly done in statistic and GIS domains, can lead to miss some unsuspected, but relevant, information about the dynamics of these spatio-temporal phenomena.

It can be interesting then, to just present the data, to observe what they have to show, before analysing them. This is the principle of the exploratory data analysis: the process is to allow a user to freely explore data, through visual representations, in order to highlight unsuspected structures or relationships. Today, exploratory data analysis is possible through visualization environments, which integrate different graphic or cartographic interactive representations.

Visualization environments are mainly developed in an ad hoc manner, in the context of a particular thematic field. However, the constant appearance of new data encourages promoting analysis methods, which could be applied to several types of phenomena. According to the domain related to these phenomena, the analysis will be focused on different dynamics. Analysing a meteorological phenomenon, in a forecasting purpose, implies a focus on the cyclic recurrences of the phenomenon. Analysing the increase of a population, for the purpose of deciding public policies, implies an analysis of the phenomenon on a long-term, through different spatial areas.

Our objective is to propose a method for the exploratory analysis of spatio-temporal phenomena and their dynamics, which would be independent of the topic. In order to achieve this, we propose a geovisualization environment, GrAPHiST (Géovisualisation pour l'Analyse des PHénomènes Spatio-Temporels; Geovisualization for spatio-temporal phenomena analysis), allowing the analysis of several dynamics, through different spatial and temporal (linear or cyclic) scales. Developing this environment implies to focus on how spatial changes are modelled, on the nature of the spatio-temporal dynamics we have to study, and on the visual and interactive tools, which allow the identification of these dynamics.

So, the contributions of our research can be found at several levels:
a generic modelling approach of spatio-temporal phenomena, in the form of event series;
new graphical and interactive representation methods, which allow the investigation and the identification of spatio-temporal dynamics, including:
the introduction of interactive temporal diagrams, which allow the visual research of cyclic recurrences in spatio-temporal data;
the use of symbology rules, which allow the visualization of relationships between the spatial and temporal components of phenomena;
new methods to represent aggregated closed events, which allow to identify structures in their spatio-temporal distribution;
the formalization of an exploratory approach for the spatio-temporal dynamics analysis, divided into several scenarios, according to the purpose of the analysis.

We validate our proposition by applying it to the analysis of several datasets. The objective is to verify the possibility to identify dynamics, related to linear or cyclic time, through the use of GrAPHiST, and to illustrate the generic aspect of the approach, as well as the analysis opportunities given by the environment.