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Chat2Map: A ReAct-based Agent Framework for Automated Web Map Generation fromNatural Language Instructions

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This research aims to improve automated web map generation from natural language instructions using a specialized framework.
Implemented a prototype of Chat2Map using Tianditu as the reference API.
Evaluated the framework on 30 web map generation tasks, including directive-based and data-driven tasks.
Utilized an iterative generate-execute-diagnose-repair loop to enhance output quality.
Achieved 80% code executability for generated maps.
Attained a 70% task success rate on both directive-based and data-driven tasks.
Demonstrated that effective web map generation relies on model reasoning connected to domain knowledge.

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Randomized trial demonstrates 80% code executability in web map generation, indicating effective integration of geospatial data and tools.

Zhang et al. (2026) studied this question.

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Randomized trial demonstrates 80% code executability in web map generation, indicating effective integration of geospatial data and tools.