Public policy is the formal and informal guiding principles that are used by governments and other decision-making entities to guide our everyday lives. Geographic Information Science and Technology (GIS&T) has had an impact on the public policy process since GIS&T’s earliest beginnings in the 1960s. Advances in the development and availability of both geospatial technology and geospatial data paralleled a growing use of data-driven rational planning and decision-making models in policy making at all levels of government. Today more than ever, successful public policy depends on high-quality data and the technology that communicates its meaning effectively. Beyond the rational application of scientific or systematic methods, public policy is about values and how values affect, and are affected by, policies. This requires delivery of credible information in a transparent, understandable form not only to decision makers responsible for adopting policy, but also to various categories of stakeholders whose behavior will be impacted in some way by the policy’s implementation. GIS&T continues to play an important role in that endeavor, including making value conflicts more seeable and knowable. Included in the entry is a summary of the public policy process and its participants, followed by a brief overview of how GIST’s role in public policy has evolved over the last 50 years. The entry concludes by outlining a sample of real-world applications and presenting a discussion of related issues and future considerations.

The field of geospatial analytics and modeling has a long history coinciding with the physical and cultural evolution of humans. This history is analyzed relative to the four scientific paradigms: (1) empirical analysis through description, (2) theoretical explorations using models and generalizations, (3) simulating complex phenomena and (4) data exploration. Correlations among developments in general science and those of the geospatial sciences are explored. Trends identify areas ripe for growth and improvement in the fourth and current paradigm that has been spawned by the big data explosion, such as exposing the ‘black box’ of GeoAI training and generating big geospatial training datasets. Future research should focus on integrating both theory- and data-driven knowledge discovery.

Where should a retail business occur or locate within a region?  What would that trade area look like?  Should a retail expansion occur and how would that affect sales of other nearby existing locations?  Would a new retail location have the right demographic or socio-economic customer base to be profitable?  These are important questions for retailers to consider.  Within the evolving landscape of GIS, there is more geospatial data than ever before about the potential customer.  In retail, the application of maps and mapping technology is growing to include commercial real estate, logistics, and marketing to name a few.  There has been an increased momentum across commercial applications for geospatial technologies delivered in an easy to comprehend format for a variety of end users.  

As new information and communication technologies have altered so many aspects of our daily lives over the past decades, they have simultaneously stimulated a shift in the types of data that we collect, produce, and analyze. Together, this changing data landscape is often referred to as "big data." Big data is distinguished from "small data" not only by its high volume but also by the velocity, variety, exhaustivity, resolution, relationality, and flexibility of the datasets. This entry discusses the visualization of big spatial datasets. As many such datasets contain geographic attributes or are situated and produced within geographic space, cartography takes on a pivotal role in big data visualization. Visualization of big data is frequently and effectively used to communicate and present information, but it is in making sense of big data – generating new insights and knowledge – that visualization is becoming an indispensable tool, making cartography vital to understanding geographic big data. Although visualization of big data presents several challenges, human experts can use visualization in general, and cartography in particular, aided by interfaces and software designed for this purpose, to effectively explore and analyze big data.