Christoph Traun

Christoph Traun is a Researcher in Geoinformatics at Paris Lodron University Salzburg, affiliated with the International Institute for Geoinformatics. With continuous project involvement since 2001, he currently contributes to ongoing initiatives including TStour (Tien Shan tourism development, 2025-2026) and previously led roles in GI-N2K and ENERGEO projects focused on geospatial workforce development and environmental monitoring.

His research centers on advanced cartographic techniques and geospatial analysis, with significant contributions to animated choropleth maps, value generalization methods, and spatial autocorrelation applications. Recent work explores AI integration in cartography (e.g., generative KI systems) and GIS education innovation, particularly examining ChatGPT's impact on teaching methodologies. He maintains strong focus on practical applications in urban planning, sustainability assessment, and tourism development.

Traun's publication record reveals evolving trends from foundational GIS education research toward cutting-edge geovisualization and AI-driven spatial analysis. His 2021-2025 output demonstrates increasing emphasis on temporal data visualization, ethical AI implementation, and interdisciplinary urban studies.

• Award for outstanding teaching (2015)
• Special Achievement in GIS Award: UNIGIS (2014)

As project staff in five major grants totaling over 15 years of continuous funding, Traun has secured significant resources for geospatial research including EU-funded initiatives like ENERGEO (environmental impact of energy use) and VESTA-GIS (vocational GIS training). His collaborative approach involves partnerships across Europe and Central Asia, with recent work focusing on workforce development and sustainable tourism metrics.

He actively participates in the UNIGIS network and contributes to academic discourse through conference workshops and public lectures on geovisualization principles, most recently presenting at the u3Green Workshop (2024) and TStour seminar series.