Theoretical foundation
Position GeoAI as an enabler of accessibility, scalability, automation, decision-making and transparency.
GeoAI · EUDR · Smallholder inclusion
THE TRANSFORMATIVE POWER OF GEOAI: A CASE STUDY FOR SMALLHOLDER FARMERS' EUDR COMPLIANCE
Copernicus Master in Digital Earth (CDE)
Year & Place of Origin
2026 · Salzburg, Austria & Olomouc, Czech Republic
Submitted in partial fulfilment of the requirements for the joint Master's degree, awarded by Paris Lodron University of Salzburg and Palacký University Olomouc.
This research exposes a comprehensive framework responding to the rapid expansion of geospatial artificial intelligence (GeoAI) and demonstrating its practical applicability.
The framework is applied to a real-world case study that automates plot geolocation validation, integrates Earth Observation and GeoAI models, and communicates clear European Union Deforestation Regulation (EUDR) compliance results through an interactive dashboard.
Thesis aim
Bridging regulation and smallholder realities
Applied case study
Support Colombian smallholder coffee and cacao farmers under EUDR compliance pressure.
Transferable blueprint
Document a reusable architecture and assessment logic that can extend beyond the case study.
Research objectives
From GeoAI theory to a tangible compliance solution
- 01
Establish the relevance of GeoAI
Explain its role in regulatory and sustainability-focused environments.
- 02
Design a scalable compliance pipeline
Automate geolocation validation and integrate GeoAI and Earth Observation evidence.
- 03
Develop a user-centred dashboard
Translate technical outputs into accessible and interpretable plot-level information.
- 04
Ensure transferability and scientific rigour
Present the methodology at an abstract level while protecting project-specific interests.
Results · GeoAI compliance pipeline
Five connected phases into one explainable workflow
Choose a phase to inspect its purpose and contribution.
P0 · Harmonization
Prepare heterogeneous geospatial inputs
Normalize formats, coordinate reference systems and attributes so every production plot can enter a consistent and reproducible workflow.
- GeoJSON, Shapefile, GeoPackage and related inputs
- CRS detection and reprojection
- Schema and attribute normalization
INPUT→STANDARD
Results · Farmer-in-the-loop Dashboard prototype
Explore the protoype
Six connected windows guide farmers from parcel registration and geometry verification to EUDR evidence and reporting.
Manage production plots at a glance
Review the plot inventory, geometry confidence and parcels that require action.
Real impact
Bridge the gap between geospatial intelligence and low-capacity end users
The case study combines technological innovation with a human-centred compliance perspective.
Digital inclusion
Make complex geospatial evidence more accessible to smallholder farmers with limited technical capacity.
Conclusion
From framework to field-ready tool
This research tested whether GeoAI can make EUDR compliance both rigorous and accessible for the farmers most affected by it.
Validated pipeline
The five-phase workflow reliably automates plot geolocation validation and EO evidence integration end to end.
Farmer-first design
The dashboard prototype shows technical compliance evidence can be made legible to non-technical, low-connectivity users.
A transferable blueprint
The architecture generalizes beyond coffee and cacao, to other commodities and regulatory frameworks facing similar pressure.
GeoAI won't close the compliance gap alone, but paired with human-centred design, it can make regulation legible to the people it affects most.
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Thesis materials
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LET'S CONNECT!
Questions about the methodology, data, or case study region are welcome.
Nicole Salazar-Cuellar · Geoscientist