Artificial Intelligence for Spatial Data Quality and Uncertainty Modeling in Spatial Analyses

Workshop Overview

Research in smart spatial data governance must seize the opportunity to intelligently collect and retrieve the diverse geospatial data available today and use spatial analysis, spatial statistics and artificial intelligence (AI) methodologies like deep learning to address pressing environmental and socioeconomic challenges requiring solutions at local to global scales. A particular issue concerns the uncertainty and quality of spatial data and spatial analyses. To this end there is a need to explore AI potentials to intelligently evaluate the collection, management, fusion, and representation of spatial data and assess uncertainty modeling and their impacts of informed decision making to support sustainable development.

Workshop Theme

  • Artificial intelligence for big spatial data mining and data science evaluation
  • Spatial statistics for uncertainty assessment
  • Methods to assess quality of spatial smart governance decision-making processes
  • Artificial intelligence algorithms for spatial analysis and uncertainty modeling
  • Uncertainty modelling and visualization in SDI, LAS, BIM, Digital Twin, and UBGIS
  • Uncertainty modeling in smart sensors calibration, fusion and information extraction
  • Smart Data quality and uncertainty assessment in multidimensional GIS
  • Smart spatial quality control techniques and standards
  • Uncertainty assessment in smart cities

Workshop Organizers

Prof Gerhard Navratil

Dept. of Geodesy and Geoinformation, TU Wien Gußhausstr, Wien, Austria, gerhard.navratil@geo.tuwien.ac.at

Gerhard NAVRATIL holds a master (Dipl.-Ing., 1998) in Surveying and a PhD in technical sciences (2002), both from TU Wien. At the same university he received the right to teach (venia docendi) in 2007. His research covers land information systems, spatial data quality, legal and technical issues of geographical information systems, and spatial decision making.

Prof Umit Isıkdag

Department of Informatics, Mimar Sinan Fine Arts University, Bomonti Kampüsü Cumhuriyet Mah. Silahşör Cad, İstanbul, Turkey, uisikdag@gmail.com

Umit Isikdag is a Professor of Construction Informatics at the Department of Informatics in Mimar Sinan Fine Arts University. He holds PhD in Construction Informatics from the University of Salford. His research interests are in 3D GIS, BIM, BIM-GIS Integration, Machine and Deep Learning, Internet of Things, and Structural Equation Modelling. He is the co-chair of ISPRS WG IV/2 and currently the Associate Editor of SASBE and Frontiers in Built Environment BIM Section. He has published 6 books and numerous research papers in reputable journals and international conferences. He chaired various academic conferences until today.

Prof Inger Fabris-Rotelli

Department of Statistics, University of Pretoria, South Africa, inger.fabris-rotelli@up.ac.za

Prof Inger Fabris-Rotelli is an associate professor in the Department of Statistics at the University of Pretoria. She has been at the Department of Statistics since 2004 and holds a PhD Mathematical Sciences.  Her research interests are in spatial statistics and GIS, as well as remote sensing and general image processing. The research focuses on applied areas, developing mathematical and statistical methodology for image processing, remote sensing and spatial statistics with impact in areas of criminology, epidemiology (COVID-19) and biostatistics, and informal road modelling. She served on the executive of the South African Statistical Association (SASA) from 2012 until 2018, and as a director on the ICCSSA (Institute of Certificated and Chartered Statisticians in South Africa) board from 2019. She is the current president of SASA and the CEO of ICCSSA. Among others she is also a member of ISI, ISPRS and IMS internationally, and the Golden Key Society, SASA, S2A3, SAMS, ICCSSA (registered as a Chartered Statistician from 2019 - 2023). She is a SACNASP council member for the period 2021 to 2025, is a Registered Professional Natural Scientist with SACNASP, and has a National Research Foundation Y2 rating in recognition of her research.

scientific Committee

  • Bryan C. Pijanowski, University of Purdue, US.
  • Christophe Claramunt, Naval Academy Research Institute, France
  • Giles Foody, Nottingham University, UK
  • Qiming Zhou, Baptist University, Hong Kong
  • Mir Abolfazl Mostafavi, Laval University, Canada
  • Nico Van de Weghe, Ghent University, Belgium
  • Alfred Stein, Twente University, The Netherlands
  • John W.Z. Shi, The Hong Kong Polytechnic University, Hong Kong, China
  • Gerhard Navratil, TU Wien, Austria
  • Jamal Jokar Arsanjani, Aalborg University, Denmark
  • Ana-Maria Raimond, IGN, France
  • Jan Blachowski, Wroclaw University of Science and Technology
  • Yongze Song, Curtin University, Australia
  • Mojgan Jadidi, York University, Canada
  • Hossein Chavoshi, Norwegian University of Life Science, Norway
  • RobertPontius Jr, Clark University, US
  • Alexis Comber, Leeds University, UK
  • Bahareh Kalantar, Riken, Japan
  • Nicholas Hamm, Nottingham University China Campus, China
  • Mingshu Wang, Glasgow University, UK
  • Umit Isikdag, Istanbul Technical University, Turkey
  • Inger Fabris-Rotelli, University of Pretoria, South Africa
  • Mei-Po Kwan, Chinese University of Hong Kong, Hong Kong
  • Cidalia Fonte, University of Coimbra, Portugal
  • Bin Jiang, University of Galve, Sweden
  • Mahmoud Reza Delavar, University of Tehran, Iran

ABOUT GSW

The ISPRS Geospatial Week (GSW) is a combination of workshops organised by about 30 ISPRS Working Groups active in areas of interest of ISPRS.

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