photo.jpg Given Name :
Family name :
Education :
Position :

E-mail :
Phone :
Fax :
Skype :

For appointments : 		Patrick
Bogaert
Doctor in agronomy
Professor

patrick.bogaert@uclouvain.be
+32 (0)10 47.36.82
+32 (0)10 47.88.98
patrick.bogaert

in general (pdf file)
Keywords | Research activities | List of publications | Teaching | Some links |

Keywords

Geostatistics, Bayesian Maximum Entropy, space-time variability, random fields.

Research activities

Space-time analysis of environmental variables

Due to the increasing amount of space-time information provided by automatic measurement networks and their storage into easily handled databases, the statistical scientific community has taken an interest in the analysis of these data for the last decade. Integrating spatial and temporal aspects of the variability for natural processes has been recognized as a subject of tremendous importance by many authors. The research conducted aims at developing powerful and efficient space-time analysis and modeling techniques, that would be versatile enough in order to be applied to various kind of environmental data.

Bayesian Maximum entropy (BME) methods

The Bayesian maximum entropy (BME) methods is a set of statistical techniques which can rigorously and efficiently handle space/time mapping applications of considerable practical importance. BME, which belongs to the field of Enviroinformatics, can integrate and process physical knowledge that belongs to two major bases: general knowledge (i.e., obtained from general principles and laws, summary statistics, and background information) and specificatory knowledge (i.e., obtained through experience with the specific situation). BME allows considerable flexibility regarding the choice of an appropriate spatiotemporal map, offers a complete assessment of the mapping uncertainty, and contributes to the scientific understanding of the underlying natural phenomenon. Classical geostatistics results are obtained as special cases of the BME approach. In addition, a more accurate and informative analysis is possible by incorporating various sources of physical knowledge that cannot be processed by classical geostatistics methods.

List of publications

Updated May 26, 2009 (pdf)

Teaching

Some links