Our chair will be represented at ACM SIGSPATIAL GIS in Hamburg

Our professorship is thrilled to announce its active participation in the 31st International Conference on Advances in Geographic Information Systems (SIGSPATIAL ‘23), taking place in Hamburg, Germany. We are co-organizing the conference, are co-chairing multiple workshops, and we are presenting quite a few research results from colleagues of the chair and our collaborators.

Research Papers

We are excited to present the following scientific papers:

  1. Rethink Geographical Generalizability with Unsupervised Self-Attention Model Ensemble: A Case Study of OpenStreetMap Missing Building Detection in Africa (full paper) Authors: Hao Li, Jiapan Wang, Johann Maximilian Zollner, Gengchen Mai, Ni Lao, Martin Werner

  2. Bavaria Buildings - A Novel Dataset for Building Footprint Extraction, Instance Segmentation, and Data Quality Estimation (Data and Resources Paper) Authors: Martin Werner, Hao Li, Johann Maximilian Zollner, Balthasar Teuscher, Fabian Deuser

  3. Exploring GeoAI Methods for Supraglacial Lake Mapping on Greenland Ice Sheet (GIS cup) Authors: Xuanshu Luo, Paul Walther, Wejdene Mansour, Balthasar Teuscher, Johann Maximilian Zollner, Hao Li, Martin Werner

  4. Signal Separation in Global, Temporal Gravity Data (GeoAI workshop paper) Authors: Betty Heller-Kaikov, Roland Pail and Martin Werner

  5. Towards GeoAI as a Containerized Microservice (SRC paper) Authors: Jiapan Wang


We are delighted to co-host two workshops:

  1. 11th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial 2023) Workshop Co-Chairs from our group: Martin Werner Description: Join us to explore the challenges and opportunities of processing and analyzing big geospatial data, fostering collaboration and knowledge exchange.

  2. 2nd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data Workshop Co-Chairs from our group: Hao Li, Martin Werner Description: Engage with experts in the efficient searching and mining of large geospatial data collections, contributing to the development of cutting-edge solutions.

For further information about our participation and research reach out to us on the conference. We look forward to sharing insights, learning, and contributing to the vibrant academic community at SIGSPATIAL ‘23. For detailed information on all our published papers refer to the publications page.

© 2020 M. Werner