  Large language models (LLMs) are advancing rapidly. Such models have
demonstrated strong capabilities in learning from large-scale (unstructured)
text data and answering user queries. Users do not need to be experts in
structured query languages to interact with systems built upon such models.
This provides great opportunities to reduce the barrier of information
retrieval for the general public. By introducing LLMs into spatial data
management, we envisage an LLM-based spatial database system to learn from both
structured and unstructured spatial data. Such a system will offer seamless
access to spatial knowledge for the users, thus benefiting individuals,
business, and government policy makers alike.
