I grew up in a small village on the Breton coast, in a working-class family. That starting point shaped a way of looking at the world: through concrete realities, material constraints and real territories rather than abstractions.

My path into science, research and international work was built through public education, study, work, encounters and a few decisive turns. That trajectory still shapes my relationship to science: measuring and modelling should help better qualify situations, risks and possible decisions.

My scientific path began with geology and volcanology: observing forms, structures, rocks and landscapes, then relating them to physical processes such as deformation, fracturing or magma propagation.

That training gave me a method: start from the field, accept heterogeneity, reason across scales, and connect incomplete observations, indirect data and physical models.

After several years in academic research, my work moved toward applied geoscience. I worked as a geotechnical engineer on damage cases linked to clay shrink–swell, within the French CatNat drought recognition framework.

That experience deeply changed how I look at risk. Behind maps, hazard classes and technical reports, there are cracked houses, exhausted residents, conflicting assessments and decisions that are often difficult to understand.

Clay shrink–swell is a slow, heterogeneous process linked to soils, climate, vegetation, buildings and land use. It cannot be reduced to a colour on a map.

Satellites do not replace fieldwork, geotechnics or local expertise. But they provide a unique capability: observing slow, repeated and spatially continuous deformation over long periods.

InSAR can measure ground motion at millimetric scale from satellite radar images. It is not a magic wand: signals are noisy, acquisition geometries are complex and time series must be interpreted carefully.

Used properly, this information can document dynamics invisible to the naked eye: seasonality, amplitude, recurrence, drought response, relationships with soil moisture, and differences between urban, geological or vegetated contexts.

fiñv aims to transform heterogeneous data into readable territorial indicators: trends, seasonal amplitudes, signal quality, hydrological correlations, spatial coherence and comparisons across sources and periods.

The goal is not to add yet another map to an already saturated GIS landscape. The goal is to produce analyses that help understand, prioritise and decide.

Applications include clay shrink–swell, urban deformation, subsidence, slow instabilities and the territorial effects of climate change on soils, buildings and infrastructure.

An analysis only has value if its assumptions, limits and uncertainties can be explained. This is what guides fiñv: turning complex data into elements of understanding, without hiding uncertainties or selling fragile certainties.

If you work on a territory, a building portfolio, an infrastructure network or a dataset related to ground motion, I offer a first 30-minute call to understand the need, identify available data and assess what Earth observation can bring.

Book a 30-minute call