Call for abstracts
Geospatial Artificial Intelligence (GeoAI) draws from across disciplinary domains in that it situates itself in data science, environmental science and geography. It incorporates multi-modal geospatial data to inform use cases in policy such as environmental degradation and disaster management.
This session aims to explore these and other cross-disciplinary interstices among big data, large language models, Geographic Information Systems (GIS) and cartography. GIS education, which combines spatial analysis and cartographic design, represents a unique context in which Generative Artificial Intelligence tools can make a significant impact.
GIS education encompasses a variety of pedagogical approaches aimed at building both technical proficiency and spatial thinking (Duarte et al. 2022). Traditional methods are often complemented by laboratory-based learning, where students engage in hands-on exercises with GIS software like ArcGIS or QGIS, developing skills in spatial data manipulation, analysis, and visualization (Rickles and Ellul, 2015).
Contemporary approaches have integrated emerging technologies and pedagogies. For example, experiential learning incorporates fieldwork, enabling students to gather spatial data using GPS devices or drones. Additionally, the rise of WebGIS platforms and open data has democratized GIS education, making geospatial tools and datasets accessible to broader audiences (Ruibo, 2019).
This session is inspired by Muehlenhaus’s cartographically-focussed Generative Pre-training Transformer (GPT). It is envisaged that papers will represent a diversity of methodological stances: qualitative studies and preliminary explorations are particularly encouraged.
Possible topics include (but are not limited to):
Descriptions and case studies of GeoAI and / or large language models to GIS and cartography / cartographic education;
Examples of how geographical epistemologies have shaped and / or been shaped by the application of (what might loosely be termed as) AI agents / AI tools;
Methodological approaches to such investigations; and
Defining and designing for the nurturing of literacies of GeoAI and the ethical implications of the use of IoT and Data Science in such investigations.
Enquiries to Kenneth Y T Lim (voyager@mac.com / kenneth.lim@nie.edu.sg) are welcome.