The session recording will be archived on the site until July 20th, 2025

This session was streamed but not recorded

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Description:

Almost 30 years ago, a book How Maps Work (MacEachren, 1995) generated lively discussion about the nexus between how geospatial information is represented cartographically and how people understand and use mapped representations to learn about the world, facilitate scientific analysis, and support decision making. Since that time, several advances in geospatial technologies have bolstered cartographic representation capabilities that are useful to scientists and scholars, but the methods can be difficult to access, interpret and utilize for other user communities.

This paper session focuses on two such advances, the development of multiscale mapping databases and the application of intelligent methods to capture, curate and integrate geospatial features across spatial and temporal scales and resolutions. Intelligent methods include but are not limited to knowledge-based or artificial intelligence (AI) techniques, such as rule-based systems, neural networks, genetic algorithms, and generative AI. Interest in these methods has been widespread, which raises important questions about how to tailor and evaluate the strategies and resulting multiscale data products for applications in social and physical science domains. What guidelines can be established to ensure strategies are operable, repeatable, and reliable? Can processing and outcomes be reported in ways that are understandable to user communities lacking specialized knowledge about multiscale mapping and data? Are we limited to metrics regarding efficient processing, data volume and accuracy, or can we advance the assessment to consider semantics about representing the world well with multiscale mapping? We invite demonstrations or proposals for implementing or assessing intelligent methods for geospatial data transformations across multiple spatial and/or temporal scales.

Non-Presenting Participants