Bérénice Le Mao
73 avenue de Paris · 94165 Saint-Mandé CEDEX · (+33)1 43 98 62 37 ·
berenice.le-mao@ign.fr
PhD student in map generalization
Member of the GEOVIS research team
Directeur de recherche IGN en sciences de l'information géographique, géovisualisation, et généralisation cartographique. Directeur adjoint du LASTIG.
Membre de l'équipe GEOVIS
Research Interests
Sujets de recherche
Progressiveness in cartography
Progressivité en cartographie
Experience
Past jobs and roles in research
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01-04-2021
Intern in the UMR LIENSs laboratory
Implementation of a collaborative geohistorical webGIS application for the Aunis region.
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01-03-2022
Intern in the LASTIG laboratory for the LostInZoom projet
Analysis of the needs of crisis management practitioners in terms of multi-scale cartographic representations based on several approaches: observation and exercise debriefing, online survey and individual interview.
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01-10-2022
PhD student
My PhD, supervised by Guillaume Touya deals with progressive map generalisation in pan-scalar maps.
Education
Université Gustave-Eiffel
PhD in Geographical Information Science
October 2022 - now
La Rochelle Université
Master in environmental sciences, applied geography for coastal management
Geomatics specialization
September 2020 - September 2022
Publications
[ACL] Journals
[ACL] Revues répertoriées par l'HCERES
[ACLN] Journals
[ACLN] Revues non répertoriées
[ASCL] Others
[ASCL] Revues sans comité de lecture
[ACTI] Conferences
[ACTI] Conférences internationales
[ACTN] Conferences
[ACTN] Conférences nationales
[COM] Conferences
[COM] Communications orales
[OS] Books and Chapters
[OS] Ouvrages ou chapitres d'ouvrages scientifiques
[DO] Books and Chapters
[DO] Directions d'ouvrages scientifiques
[AFF] Posters
[AFF] Posters
[AP] Preprints
[AP] Preprints
[TH] Dissertations
[TH] Thèse
[INV] Invited Talks
[INV] Conférences invitées
[PV] Popularization
[PV] Publications et communications de vulgarisation
Projects
On-going projects
LostInZoom
A project that seeks to establish a new zooming paradigms for multi-scale maps, based on multi-scale visual landmarks that act as anchors during the zoom and a progressive generalisation.