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Medellín, Colombia

Federico Gómez

Geoscientist · Geohazards · Remote Sensing · UAS

Geohazards Remote Sensing UAS Geo Data Science
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About

About Me

I am a Colombian geoscientist dedicated to understanding and mitigating geological and hydrometeorological hazards in the tropical Andes.

My academic path combines a B.Sc. in Geological Engineering (2017) and an M.Sc. in Water Resources Engineering (2022) from the Universidad Nacional de Colombia.

From 2017 to 2022 I worked at the same university, producing susceptibility maps, numerical simulations, and satellite-based analyses for landslides, floods, and debris flows across diverse Colombian terrains.

Since 2021 I have been part of Medellín's Sistema de Alerta Temprana (SIATA), where I design real-time algorithms that fuse field instrumentation, remote sensing, and machine learning to issue early warnings for landslide events.

In 2024 I joined Universidad EAFIT as an adjunct professor, leading a postgraduate course on geotechnical instrumentation that blends theory with hands-on interpretation of sensor data from an active slope case study.

I routinely manage interdisciplinary projects, process large geospatial datasets in Python and R, conduct UAS surveys in the field, and translate technical findings into actionable guidance for risk managers.

Expertise

What I Do

My work spans four interconnected domains — each informing the others to build a more complete picture of Earth's hazardous processes.

Geohazards

Physically-based modeling of landslides, debris flows, and floods. Real-time early warning algorithm design fusing rainfall thresholds, instrumentation, and ML classifiers.

SHALSTAB TRIGRS FLO-2D Early Warning Hazard Mapping

Remote Sensing

Multispectral and SAR image processing for land cover mapping and ground deformation monitoring. Change detection and time-series analysis at regional scale.

Google Earth Engine SAR / InSAR Multispectral Change Detection SNAP

UAS / Drones

Field photogrammetric surveys for high-resolution DEM generation, orthomosaic production, and volumetric change analysis in landslide and construction sites.

Photogrammetry OpenDroneMap Point Clouds Orthomosaics DEM Generation

Geospatial Data Science

End-to-end Python and R pipelines for geospatial analysis, machine learning susceptibility mapping, spatial statistics, and interactive visualization.

Python GeoPandas Rasterio scikit-learn QGIS / ArcGIS Pro
Education

Education

Academic background highlighting degrees and institutions.

Experience

Work

Professional experience and roles I've held.

Code

Repositories

Most recently updated public code repositories on GitHub, reflecting ongoing work and contributions.

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Research

Publications

Key publications from my research career. Click to explore the details.

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