Machine learning for spatial disaggregation of regional transport data in the EU
Fernandez, Juan R · RI ITBA · 2026
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This thesis develops a machine learning framework for the spatial disaggregation of transport-related data across European Union regions. Using a self-supervised hybrid regression approach combined with dasymetric mapping and ancillary geospatial data, the study improves estimation accuracy at NUTS-3 level. Results demonstrate the potential of data-driven methods to support regional decarbonization strategies.
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APA 7
Fernandez, J. R. (2026). Machine learning for spatial disaggregation of regional transport data in the EU. RI ITBA. https://hdl.handle.net/20.500.14769/5275
MLA
Fernandez, Juan R. Machine learning for spatial disaggregation of regional transport data in the EU. RI ITBA, 2026. https://hdl.handle.net/20.500.14769/5275.
Chicago
Fernandez, Juan R. 2026. Machine learning for spatial disaggregation of regional transport data in the EU. RI ITBA. https://hdl.handle.net/20.500.14769/5275.
Harvard
Fernandez, J. R. 2026, Machine learning for spatial disaggregation of regional transport data in the EU, RI ITBA, available at: https://hdl.handle.net/20.500.14769/5275 [Accessed 28 Jun. 2026].
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- Título
- Machine learning for spatial disaggregation of regional transport data in the EU
- Autor / colaboradores
- Fernandez, Juan R
- Editorial
- RI ITBA
- Año de publicación
- 2026
- Idioma
- en
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