SUPQA: LLM-based Geo-Visualization for Subjective Urban Performance Question-Answering
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
As urbanization accelerates, urban performance has become a growing concern, impacting every aspect of residents' lives. However, urban performance exploration is a tedious and highly subjective process for users. Users need to manually collect and integrate various information, or spend a large amount of time and effort due to the steep learning curves of existing specialized tools. To address these challenges, we introduce SUPQA, a novel approach for urban performance exploration using natural language as input and interactive geographic visualizations as output. Our approach leverages Large Language Models (LLMs) to effectively interpret user intents and quantify various urban performance measures. We integrate progressive navigation and multi-geographic scale analysis in our visualization system, explaining the reasoning process and streamlining users' decision-making workflow. Two usage scenarios and evaluations demonstrate the effectiveness of SUPQA in helping residents and planners acquire desired information more efficiently and enhancing the quality of decision-making.
Description
CCS Concepts: Human-centered computing → Visualization systems and tools; Interaction design process and methods; Geographic visualization
@article{10.1111:cgf.70106,
journal = {Computer Graphics Forum},
title = {{SUPQA: LLM-based Geo-Visualization for Subjective Urban Performance Question-Answering}},
author = {Huang, Haiwen and Chen, Juntong and Wang, Changbo and Li, Chenhui},
year = {2025},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.70106}
}