MSc Geoinformatics | Geospatial AI & Earth Observation
I specialize in bridging the gap between Deep Learning and Remote Sensing. My work focuses on building intelligent systems (GIS Agents) and high-precision mapping models using state-of-the-art foundation models and geospatial libraries.
| Category | Tools & Technologies |
|---|---|
| Languages |   |
| Geospatial |   GDAL |
| AI / Machine Learning |    |
| Data & Databases |    |
| DevOps & Cloud |    |
🛰️ Clay LULC
Foundation Model for Land Use and Land Cover (LULC).
- Utilized the Clay Foundation Model for fine-tuning on multi-spectral satellite imagery.
- Improved classification accuracy in heterogeneous landscapes by leveraging self-supervised pre-training weights.
Canopy Height Model Generation.
- Developed a high-resolution CHM estimation pipeline using the DinoV3 (Vision Transformer) architecture.
- Trained on the CHM2 dataset, pushing the boundaries of monocular height estimation from satellite/aerial imagery.
