Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Space and distance have long been acknowledged by researchers as fundamental constraints which shape our world. As technological changes have transformed the very concept of distance, the relative location and connectivity of geospatial phenomena have remained stubbornly significant in how systems function. At the same time, however, technology has allowed us to begin to bring tools like simulation to bear on our understanding of how such systems work. While previous generations of scientists and practitioners were unable to gather spatial data or to incorporate it into models at any meaningful scale, new methodologies and data sources are becoming increasingly available to researchers, developers, users, and practitioners. This flowering of different approaches is occurring simultaneously across many fields, and at every point in the research process. Techniques for preparing spatial data for use in simulations, for measuring spatial processes within such simulations, or for using simulations to generate novel spatial data for further research have been developed by practitioners in dozens of distinct disciplines. These parallel lines of study hold great promise for researchers, and suggest the value of explicitly working across research boundaries to adopt and share techniques for the use and preparation of geospatial data in a simulation context.

Geographic information systems

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Geospatial simulation is a powerful tool for many disciplines to understand, explain, and predict overly complex natural and human-made systems. With the advances in computing and software technology, simulation is becoming a commonly accessible solution. The spatial information community has a huge potential to contribute and get benefited from the geospatial simulation as it provides many research avenues including creating methods for the ingestion of spatial data, studying domain-specific problems, and using simulation-generated spatial data. Especially, simulation-generated data provides many advantages over publicly available data sets that are too small to allow reliable inference, too noisy to find the signal of patterns or deliberately altered to preserve privacy.

Geodatabases.