Geospatial reasoning underpins critical applications from city planning to emergency response, yet current large language models frequently struggle with accurate spatial computation, often resorting to unreliable web searches or superficial pattern recognition. Riyang Bao from Emory University, Cheng Yang and Zhexiang Tang from Rutgers University, alongside Dazhou Yu, Gengchen Mai and Liang Zhao, introduce Spatial-Agent, a novel framework grounded in established spatial information science. This research formalises geo-analytical question answering as a process of concept transformation, translating natural language into executable workflows called GeoFlow Graphs , essentially, a blueprint for spatial analysis. By rigorously extracting spatial concepts and composing…