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Education, research experience and open-source work in geodetic sciences and collaborative cartography.
General Information
| Full Name | Kauê de Moraes Vestena |
| Position | Professor, Federal Technological University of Paraná (UTFPR), Pato Branco |
| Location | Pato Branco, Paraná, Brazil |
| kauemv2@gmail.com | |
| ORCID | 0000-0003-1225-2371 |
| Google Scholar | qc6CJjYAAAAJ |
| GitHub | kauevestena |
Education
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2021–2025 PhD in Geodetic Sciences
Federal University of Paraná (UFPR) - Dissertation: Toward a Global Pedestrian-Centered Map: An Open Framework for Mapping, Validating and Publishing Active Mobility Networks (advisor: Silvana Philippi Camboim; co-advisor: Daniel Rodrigues dos Santos)
- Degree conferred October 3, 2025
- Sandwich research period at the Politecnico di Milano (Oct 2023–Mar 2024, advisor Maria Antonia Brovelli)
- Research on accessibility mapping with open data and collaborative cartography
- Automated methodologies for sidewalk network mapping in OpenStreetMap
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2017–2020 MSc in Geodetic Sciences
Federal University of Paraná (UFPR) - Research on terrestrial mobile mapping systems for urban environment assessment
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2013–2017 BSc in Cartographic and Surveying Engineering
Federal University of Paraná (UFPR) -
2009–2012 Technical Diploma in Surveying
Federal Technological University of Paraná (UTFPR)
Experience
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2026–present Professor (Magistério Superior)
Federal Technological University of Paraná (UTFPR), Pato Branco - Started August 4, 2026
- Full-time, exclusive-dedication teaching and research position
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2021–2025 PhD Researcher
Federal University of Paraná (UFPR), Graduate Program in Geodetic Sciences - Research on accessibility mapping, collaborative cartography and OpenStreetMap data quality
- Development and maintenance of open-source geospatial tools
- Collaboration with the Polytechnic University of Milan on open-vocabulary classification of urban pathways
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2017–2020 Graduate Researcher
Federal University of Paraná (UFPR) - Development of a low-cost terrestrial mobile mapping system
- Convolutional neural networks applied to urban vegetation detection
Open Source Projects
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2022–present OSM SidewalKreator
- QGIS plugin that generates sidewalk geometries automatically from OpenStreetMap street data
- Over 23,000 downloads across all releases from the QGIS Plugin Repository
- Includes a QGIS Processing Provider for batch and scripted workflows
- Published in the European Journal of Geography (2023) and presented at State of the Map 2022
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2023–present OpenSidewalkMap
- Inventory and visualisation of pedestrian networks built from OpenStreetMap data
- Aims to make sidewalk and accessibility information easier to explore and reuse
Publications
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2016–2025 Peer-reviewed journal articles, book chapters and conference papers
- Topics span accessibility mapping, collaborative cartography, mobile mapping, photogrammetry and GNSS positioning
- Full list on the publications page, mirrored from ORCID
Research Interests
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Accessibility mapping and collaborative cartography
- Pedestrian and sidewalk network mapping in OpenStreetMap
- Quality assessment of crowdsourced geospatial data
- Integration of community-mapped data into official topographic mapping
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Mobile mapping and photogrammetry
- Low-cost terrestrial mobile mapping systems
- Deep learning for detection of urban infrastructure from terrestrial imagery
- RGB-D data registration and point cloud processing
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Geodesy and satellite positioning
- Precise Point Positioning (PPP) and ambiguity resolution
- Tropospheric modelling and its effect on positioning accuracy
Technical Skills
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Programming
- Python — QGIS plugin development (PyQGIS), geospatial analysis, automation
- SQL / PostGIS — spatial database management
- JavaScript, HTML, CSS — web mapping and visualisation
- Git and GitHub — version control, CI, collaborative development
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Geospatial
- QGIS and the wider OSGeo stack
- OpenStreetMap — editing, validation, tooling and community engagement
- GNSS surveying and precise positioning
- Photogrammetry, LiDAR and point cloud processing
- Remote sensing and machine learning for feature extraction
Other Interests
- Outdoors: hiking and travelling, usually with a GPS receiver in hand
- Open source: contributing to and advocating for open geospatial software and open data