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.
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
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,
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.