I hold a PhD in Geography with a specialization in Geomatics. My research focuses on remote sensing and spatial analysis approaches aimed at mapping and monitoring the dynamics of forested and non-forested environments. My work particularly explores their characterization in a context of (i) intensifying climate change and anthropogenic pressures, as well as (ii) the increasing availability of Earth observation data. Within this framework, I develop methodological approaches to detect and describe land cover classes across multiple spatial scales. I place strong emphasis on producing generalizable models and reliable, interpretable cartographic outputs.

My main contributions include:

• The characterization of exotic forest stands in a steep insular territory such as Réunion Island, using machine learning algorithms (e.g., Random Forest, K-means) and graph-based analysis methods (e.g., Dijkstra).
• The development of a semantic vocabulary to harmonize land cover change descriptions derived from applied change detection protocols.

These results have been disseminated through scientific publications and conference presentations, both in France and internationally.

I have also been involved in undergraduate and graduate teaching (L3 and M1 levels), introducing students to spatial problem-solving using GIS software such as QGIS. The objective of these sessions was not only to train students in the use of such tools, but also to foster autonomy in tasks such as (i) data acquisition and structuring, (ii) geoprocessing and spatial or attribute-based querying, and (iii) the production of problem-oriented cartographic and spatial analyses.