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ISSDQ 2023- Artificial Intelligence and Uncertainty Modeling in Spatial Analysis

 

Spatial data quality concerns with the reliability, confidence and trustworthiness of spatial data and their fitness for use. In the new era of spatial big data, IoT, smart city, ubiquitous spatial information systems and volunteered data produced using space-borne, areal and geo-sensors as well as human sensors in the phases of collection, fusion and leveraging artificial intelligence for spatial information extraction, and modeling, the issue of spatial data quality and uncertainty assessment requires more attention than ever before. Spatial data quality and uncertainty assessment/modeling are integrated components of spatial information systems main functionalities in measuring, mapping, managing, modeling and monitoring. The 12th International Symposium on Spatial Data Quality (ISSDQ 2023) will be part of the ISPRS Geospatial Week 2023, hosted by the Arab Academy for Science, Technology, and Maritime Transport, in parallel with a number of related geospatial workshops. The event will be held as a two-day single-track symposium of keynote and oral presentations as well as poster sessions and a panel discussion in the context of the ISPRS Geospatial Week.

CHAIRES

Mahmoud Reza Delavar

University of Tehran, Iran (WG IV/2)

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Alfred Stein

University of Twente, The Netherlands (WG IV/2)

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John W.Z. Shi

The Hong Kong Polytechnic University,Hong Kong, China (WG IV/2)

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Themes of event:
  • Spatial data quality in space and time,
  • Leveraging artificial intelligence in spatial data analysis and quality assessment,
  • Collaborative spatial data quality
  • Uncertainty modeling, assessment and propagation in spatial analyses
  • Error assessment and propagation in digital terrain modeling
  • Intelligent methodologies to integrate and assess spatial data and spatial analysis
  • Smart spatial data infrastructures, land administration systems, cadastral surveying and mapping, BIM and their quality assessment
  • Interoperability issues in spatial data analysis
  • Challenges in assessing big spatial data in spatial information science
  • Spatial and spatio-temporal statistics methods and their uncertainty assessment
  • Challenges in assessment of UBGI/UBGIS, GSN, autonomous driving, smart city, multidimensional GIS, UAV, marine GIS, disaster management, and real time spatial data collections, collation and processing
  • Harmonization of spatial information models and standards
  • Matching the spatial data quality of combining multiple datasets
  • Increasing spatial data quality through fusion
  • Deep learning spatial data quality assessment
  • Spatial data quality assessment of transferability
  • Spatial data quality visualization
  • Web GIS data quality
  • Sensor-based data quality
  • Intelligent GIS

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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 vande 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, Warsaw University, Poland
  • Yongze Song, Curtin University, Australia
  • Mojgan Jadidi, York University, Canada
  • Hossein Chavoshi, University of Life Science, Norway
  • Robert G. Pontious, Clark University, US
  • Alexis Comber, Leeds University, UK
  • Bahareh Kalantar, Riken, Japan
  • Nicholas Hamm, Nottingham University China Campus, China
  • Firoozeh Karimi, North Carolina A & T, US
  • 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

Special Issue dedicated to the workshop:
After the workshop, authors of selected papers will be invited to submit extended versions of their papers to the ISPRS IJGI and Geospatial information Science (GSIS) journals. The papers being accepted after the peer-review process of the journal will appear in a special issue of the journals dedicated to this symposium.