Thomas P. Kersten is a Professor at HafenCity University Hamburg within the School of Geodesy and Geoinformatics , leading the Photogrammetry & Laser Scanning laboratory. His work bridges geomatics , 3D imaging , and cultural heritage preservation through cutting-edge UAV photogrammetry , terrestrial laser scanning , and virtual reality applications. Research interests focus on: Accuracy validation of photogrammetric and LiDAR systems Low-cost 3D sensor development (e.g., Raspberry Pi-based systems) Virtual Reality for cultural heritage sites (e.g., Al Zubarah Fortress, Michaelsen House) Historical building documentation using 4D modeling Mobile mapping for archaeological and urban contexts Article trends reveal expertise in UAV-based cadastral surveying , smartphone photogrammetry validation, and multi-sensor 3D reconstruction of archaeological and architectural sites. He leads fieldwork in Portugal, Qatar, and Germany while fostering academic collaboration through conference editorship (DGPF, ISPRS workshops).
Angelo Furno is an Associate Professor at ENTPE (National School of Public Works) within Université Gustave Eiffel in Lyon, France. He serves as a researcher at the LICIT laboratory and collaborates with INRIA AGORA and the CITI-Lab of INSA-Lyon. His academic journey began at the University of Sannio in Italy where he earned his degree in Computer Engineering in 2010, followed by a PhD in Information Engineering completed in 2014 with a thesis titled "Scalable Service Composition in Autonomic Computing." After his PhD, he conducted post-doctoral research at both the University of Sannio and INRIA in Lyon. Furno's research spans multiple domains with a strong focus on transportation systems and network analysis. His work integrates distributed systems, mobile networking, and data science to address urban mobility challenges. He specializes in analyzing multi-source traffic data to support urban planning and transportation infrastructure management. His research interests include mobility pattern recognition, travel demand estimation, road-network modeling, land use detection, and social network analysis. He has developed expertise in graph analysis, clustering algorithms, and recommendation techniques applied to transportation contexts. His technical skills encompass Python, Scala, Java, and various web technologies. His publication record demonstrates consistent contributions to transportation research, with recent work focusing on park-and-ride systems optimization, traffic demand prediction using deep learning, privacy-preserving analysis of origin-destination data, and geometric classification of urban road networks. His research often addresses practical urban challenges, including pandemic-related transportation adaptations and accessibility analysis of transit networks in cities like Lyon. Best Paper Award (2012) Furno teaches courses on Intelligent Transportation Systems, Data Science and Machine Learning, and Big Data at ENTPE. His reviewing activities span numerous prestigious journals including IEEE Transactions on Mobile Computing, Transportation Research Part C, and Sensors. His collaborative work extends to multiple institutions across Europe, with particular emphasis on French research networks.
Ana-Maria Olteanu-Raimond is a Senior Researcher (Directrice de Recherche DR2) at the Institut National de l'Information Géographique et Forestière (IGN), where she co-directs the LASTIG Laboratory and leads the MEIG research team. She is actively involved in national and international research projects, including ANR IntForOut (2024–2027), and has previously coordinated ANR CHOUCAS and H2020 LandSense. She teaches in the M2IGAST Master program at ENSG, focusing on spatial statistics and geographic data quality. Her educational background includes a PhD in Geographical Information Science from Université Paris-Est (2008) and a Habilitation (HDR) from Université Gustave Eiffel (2020) on the integration of Volunteered Geographic Information with institutional data. Her research interests center on Volunteered Geographic Information (VGI) , citizen science , spatial data quality , fuzzy spatial reasoning , and the integration of heterogeneous geographic data . She explores how crowdsourced data can enhance authoritative datasets, particularly in urban monitoring, land use classification, and emergency response in mountainous regions. The recent articles highlight a strong trend in integrating multi-source data for land use and land cover mapping, assessing VGI quality, developing ontologies for emergency response, and advancing spatial analysis techniques such as network evolution and polygon matching. Her work bridges theoretical GIS advancements with practical applications in urban planning, environmental monitoring, and public safety. ANR IntForOut (2024–2027): Integration of multisource spatial data for ecosystem monitoring under recreational pressure. ANR CHOUCAS (2017–2022): Heterogeneous data integration and spatial reasoning for mountain rescue. H2020 LandSense (2016–2020): Citizen Observatory for Land Use and Land Cover monitoring. She supervises multiple PhD students including Stefan Ivanovic, Mattia Bunel, Ibrahim Abdi Maidaneh, Raphaël BRES, Martin CUBAUD, John Dawson, and Amir Badawi. Her leadership extends to international scientific networks, where she co-chairs ISPRS WG IV/8 on Digital Twins and has held roles in GdR CNRS MAGIS and COST Actions. She is also involved in developing tools and methodologies for metadata generation, spatial reasoning ontologies, and collaborative platforms for land use monitoring. Her work emphasizes methodological rigor, interdisciplinary collaboration, and real-world impact in geospatial science.
