Andrew Crooks

TL;DR: This paper addresses a framework to harvest ambient geospatial information, and resulting hybrid capabilities to analyze it to support situational awareness as it relates to human activities.

TL;DR: The experiments support the notion that people act as sensors to give us comparable results in a timely manner, and can complement other sources of data to enhance the authors' situational awareness and improve their understanding and response to such events.

TL;DR: The purpose of this paper is to catalogue these challenges and to illustrate them using three somewhat different agent-based models applied to city systems using a pedestrian model for emergency evacuation in central London, a hypothetical model of residential segregation model tuned to London data, and an agent- based residen- tial location model, for Greater London.

TL;DR: The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations, and explores the opportunity of linking a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM.