ChatGPT as a mapping assistant: A novel method to enrich maps with generative AI and content derived from street-level photographs

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.25436/E2ZW27. This is version 2 of this Preprint.

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Authors

Levente Juhász , Peter Mooney, Hartwig H Hochmair, Boyuan Guan

Abstract

This paper explores the concept of leveraging generative AI as a mapping assistant for enhancing the efficiency of collaborative mapping. We present results of an experiment that combines multiple sources of volunteered geographic information (VGI) and large language models (LLMs). Three analysts described the content of crowdsourced Mapillary street-level photographs taken along roads in a small test area in Miami, Florida. GPT-3.5-turbo was instructed to suggest the most appropriate tagging for each road in OpenStreetMap (OSM). The study also explores the utilization of BLIP-2, a state-of-the-art multimodal pre-training method as an artificial analyst of street-level photographs in addition to human analysts. Results demonstrate two ways to effectively increase the accuracy of mapping suggestions without modifying the underlying AI models: by (1) providing a more detailed description of source photographs, and (2) combining prompt engineering with additional context (e.g. location and objects detected along a road). The first approach increases the suggestion accuracy by up to 29%, and the second one by up to 20%.

DOI

https://doi.org/10.31223/X5HQ1P

Subjects

Artificial Intelligence and Robotics, Computer Sciences, Geographic Information Sciences, Geography, Other Computer Sciences, Other Geography, Spatial Science

Keywords

ChatGPT, mapping, GIScience, mapillary, OpenStreetMap, street-level photos, computer vision, large language models, llm, volunteered geographic information, vgi

Dates

Published: 2023-06-06 14:13

Last Updated: 2023-09-01 03:15

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License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None.