Abstract
In this paper we outline how to translate verbal subjective descriptions of spatial relations into metrically meaningful positional information, and extend this capability to spatiotemporal monitoring. Document collections, transcriptions, cables, and narratives routinely make reference to objects moving through space over time. Integrating such information derived from textual sources into a geosensor data system can enhance the overall spatiotemporal representation in changing and evolving situations, such as when tracking objects through space with limited image data. We focus on landmark identification, since it proves to be a more tractable problem than open-domain image recognition.