About
Nathan Damas Antonio is a researcher in GIScience and geospatial technologies, with a background in Cartographic and Land Survey Engineering and Geodetic Sciences. His work brings together collaborative cartography, OpenStreetMap, spatial and spatio-temporal analysis, semantic interoperability, spatial data infrastructures, photogrammetry, LiDAR, UAV-based data, and 3D cadastre.
His academic and professional trajectory combines research, teaching, and applied technical work. He is currently a Ph.D. candidate in Geodetic Sciences at the Federal University of Paraná, has worked as a visiting researcher at Heidelberg University, and has been involved in projects related to territorial data management, spatial database structuring, interoperability, and geospatial automation.
He has experience with Python, PostGIS, QGIS, GeoServer, GeoNode, spatial ETL, metadata management, geospatial standards, and collaborative geographic data. His broader research interests include OpenStreetMap, volunteered geographic information, urban mobility, spatial data quality, and emerging computational approaches such as NLP and large language models in geospatial contexts.
Education¶
| Year | Degree | Institution | Dissertation/Thesis |
|---|---|---|---|
| 2021–present | Ph.D. Candidate in Geodetic Sciences | Federal University of Paraná, Brazil | Research focused on GIScience, collaborative cartography, OpenStreetMap, spatial analysis, and semantic interoperability |
| 2023–2024 | Visiting Researcher | Heidelberg University, Germany | Doctoral research internship funded by CAPES-PRINT |
| 2013–2015 | M.Sc. in Geodetic Sciences | Federal University of Paraná, Brazil | A Methodological Approach to Representing Three-Dimensional Objects in a Spatial Information System |
| 2018 | B.Sc. in Physics | Federal University of Paraná, Brazil | — |
| 2008–2013 | B.Eng. in Cartographic and Land Survey Engineering | Federal University of Paraná, Brazil | A study of the Cycling Structure of Curitiba |
Research Interests¶
GIScience
collaborative cartography
OpenStreetMap and volunteered geographic information
spatial and spatio-temporal analysis
semantic interoperability of geospatial data
spatial data infrastructures
geospatial automation with Python
photogrammetry, LiDAR, and UAV-based mapping
3D cadastre
geospatial data quality
Technical Skills¶
Python, R, SQL
QGIS, ArcGIS, AutoCAD
PostgreSQL / PostGIS
GeoServer, GeoNode
Jupyter Notebook, PowerShell
GeoPandas, pandas, NumPy, SciPy, GDAL/OGR, Rasterio, PyProj
OHSOME API, OpenStreetMap/Overpass
ET-EDGV, Brazilian MGB Profile, ISO 19115, OGC