GeoSpatial Artificial Intelligence (GeoAI)

Over the last few years, Artificial Intelligence (AI) and particularly deep learning methods had a transformative impact in fields such as natural language processing or computer vision, significantly advancing the state-of-the-art in problems like parsing natural language, classifying unstructured data, or semantically segmenting images. These same techniques can also empower a next generation of Geographical Information Systems (GIS), providing the ability to combine spatial analysis with fast and near human-level perception, this way facilitating location-based discovery and analysis of relevant information. This is particularly important given the exponentially growing amount of online data, including different online sources of multimedia contents encoding spatial information.

Several recent studies have for instance shown that AI techniques can be used in a variety of geospatial applications, with examples in remote sensing for Earth observation (e.g., segmenting, classifying, downscaling, or fusing ground-level or aerial/satellite imagery), spatial data analysis (e.g., interpolation of geospatial data with generative adversarial networks), or geographical text analysis (e.g., address geo-coding or geo-referencing place references in documents), among many others (e.g., processing historical maps, gazetteer conflation, etc.). Together, these previous research efforts have given birth to a new and interdisciplinary area, often referred to as GeoAI (Geospatial Artificial Intelligence).

Many of the aforementioned applications can clearly highlight important challenges in AI for processing geospatial data, including small sample sizes to inform supervised learning, relative to the complexity of the problems, the lack of ground truth information, the high degree of noise and uncertainty, or the need for appropriately combining human-provided data (e.g., through crowd-sourcing) with automated approaches. Despite many successful applications, overcoming the aforementioned challenges requires additional developments, so that AI techniques can be more widely and easily applicable to a broader range of geospatial applications.

Topics of Interest

The EPIA’20 thematic track on geospatial artificial intelligence is thus concerned with interdisciplinary research related to different aspects of combining AI and Machine Learning (ML) with GIScience. Topics of interest include, but are not limited to:

  • Remote Sensing and Earth Observation
  • Geospatial Data Science
  • Spatial Analysis and Processing of Structured and Semi-Structured Information
  • Text Geoparsing and Handling Geographical Information Encoded in Textual Sources
  • Exploring Ground-Level Imagery for Proximate Sensing
  • Data Conflation and Quality Assurance
  • Reasoning with Geospatial Data and Knowledge Bases
  • Geospatial Information Retrieval of Multimedia Contents
  • Human-Centered Geospatial Artificial Intelligence
  • Location-Based Augmented Reality Applications
  • Combining Machine Learning and Crowdsourcing Efforts
  • Application Areas for Geospatial Artificial Intelligence (e.g., Precision Agriculture, Geospatial Health, etc.)
  • AI/ML Challenges and Geospatial Artificial Intelligence (e.g., Explainability, Causality, Efficiency, etc.)

Organizing Committee

  • Bruno Martins, Instituto Superior Técnico, University of Lisbon (General Organization Chair)
  • Carlos Damásio, Faculdade de Ciências e Tecnologia, New University of Lisbon (Program Committee Chair)
  • Jacinto Estima, Instituto Politécnico de Setúbal (Program Committee Chair)
  • João Moura Pires, Faculdade de Ciências e Tecnologia, New University of Lisbon (General Organization Chair)

Program Committee 

  • Ana Afonso, Faculdade de Ciências, University of Lisbon, Portugal
  • Ana Navarro, University of Lisbon, Portugal
  • Ana Teodoro, University of Porto, Portugal
  • Bruno Martins, Instituto Superior Técnico, University of Lisbon, Portugal
  • Carlos Damásio, Faculdade de Ciências e Tecnologia, New University of Lisbon, Portugal
  • Carsten Keßler, Aalborg University, Copenhagen, Sweden
  • Célia Gouveia, Instituto Português do Mar e da Atmosfera, Portugal
  • Christian Sallaberry, University of Pau, France
  • Cidália Fonte, University of Coimbra, Portugal
  • Devis Tuia, Wageningen University & Research, Netherlands
  • Diego Seco, University of Concepción, Chile
  • Dino Ienco, INRAE, Montpellier, France
  • Ekaterina Egorova, University of California at Santa Barbara, United States
  • Fernando Bação, NOVA IMS, New University of Lisbon, Portugal
  • Fernando Birra, Faculdade de Ciências e Tecnologia, New University of Lisbon, Portugal
  • Francisco Javier Lopez-Pellicer, Universidad Zaragoza, Spain
  • Francisco Javier Zarazaga-Soria, University of Zaragoza, Spain
  • Gil Gonçalves, University of Coimbra, Portugal
  • Isabel Trigo, Instituto Português do Mar e da Atmosfera, Portugal
  • Jacinto Estima, Instituto Politécnico de Setúbal, Portugal
  • Jérôme Gensel, University of Grenoble, France
  • João Catalão, Faculdade de Ciências, University of Lisbon, Portugal
  • João Moura Pires, Faculdade de Ciências e Tecnologia, New University of Lisbon, Portugal
  • João Valente, Wageningen University & Research, Netherlands
  • Karine Ferreira, Instituto Nacional de Pesquisas Espaciais, Brasil
  • Ludovic Moncla, INSA Lyon, France
  • Ludwig Krippahl, Faculdade de Ciências e Tecnologia, New University of Lisbon, Portugal
  • Marco Painho, NOVA IMS, New University of Lisbon, Portugal
  • Maribel Santos, University of Minho, Portugal
  • Mário Caetano, NOVA IMS, New University of Lisbon, Portugal
  • Marlène Villanova-Oliver, University of Grenoble, France
  • Mathieu Roche, University of Montpellier, France
  • Miguel Luaces, University of A Coruña, Spain
  • Nuno Datia, Instituto Superior de Engenharia de Lisboa, Portugal
  • Rafel Santos, Instituto Nacional de Pesquisas Espaciais, Brasil
  • Rainer Simon, AIT Austrian Institute of Technology, Austria
  • Roberto Henriques, NOVA IMS, New University of Lisbon, Portugal
  • Ross Purves, University of Zurich, Switzerland
  • Sébastien Lefèvre, University of Bretagne-Sud, Vannes, France
  • Sérgio Freire, European Joint Research Center, Belgium
  • Stefano De Sabbata, University of Leicester, United Kingdom
  • Steven Schockaert, Cardiff University, United Kingdom
  • Susana Nascimento, New University of Lisbon, Portugal
  • Thomas Corpetti, CNRS, Rennes, France
  • Yingjie Hu, Department of Geography, University at Buffalo, United States