EAASI invites submissions for 2026 Outstanding Thesis Award

Postgraduate researchers working on connecting geospatial innovation with tangible business outcomes are encouraged to apply for the Outstanding Thesis Award by the European Association of Aerial Surveying Industries (EAASI).

Now on its third edition, the award – titled Spatial Business Bridge – has already carved out a distinct role in the geospatial sector: identifying emerging talent and demonstrating how advanced academic research can generate real operational value. It reflects a broader shift underway across the industry, from data acquisition towards integrated workflows where analysis, interpretation and application drive competitive advantage.

"The previous editions have demonstrated the strong potential of academic research to address real industry challenges," said EAASI Secretary General Marcos Martínez. "We are seeing a growing alignment between innovation in universities and the needs of the aerial surveying sector."

As demand for professionals who can translate technical expertise into business impact continues to grow, EAASI positions the award as a practical mechanism for closing the gap between university research and industry need. The initiative is led by the association's Student and University Engagement Committee, chaired by Patrik Meixner, and forms part of a longer-term strategy to build a skilled, future-oriented workforce.

Submissions are open to postgraduate students at master's, doctorate, or post-doctoral level who have submitted a thesis or equivalent project report to a European university in 2024, 2025 or 2026. The deadline is 31 August 2026.

Further information and submission details are available at eaasi.eu or via info@eaasi.eu.

In 2025, EAASI recognized Weixiao Gao, Delft University of Technology, for his PhD dissertation “Semantic Understanding of Urban Scenes from Textured Meshes”. His research developed new automated methods for semantically rich urban modelling, directly addressing longstanding challenges in photogrammetric 3D data processing.