The past decade has witnessed a significant increase in the quality and quantity of geospatial information from various sources. Consequently, the quest for knowledge from the massive geospatial information for scientific, commercial and decision-making activities has posed new challenges for the geospatial research community. While conventional spatial statistics methods remain their power and popularity in numerous studies, many new techniques and approaches have appeared in response to the newly available geospatial data, which is essentially massive, complex, incomplete and uncertain. A variety of analysis and modeling approaches have been brought into geospatial domain such as cellular automata, agent-based modeling, and qualitative and fuzzy reasoning. These techniques are efficient and effective in discovering hidden structures, patterns and associations within geospatial data. On the other hand, emerging visualization and interaction technologies provide a powerful tool for obtaining additional insights into geospatial information for spatial analysis and modeling process. There has been an increasing convergence of the analytical reasoning and visualization towards creation and discovery of geospatial knowledge for real world applications.