Spatial contextual awareness

[1] It is also defined as the relationship between and synthesis of information garnered from the spatial environment, a cognitive agent, and a cartographic map.

This narrow definition omits the individual cognitive and computational functions involved in a complex geographic system.

[3] Augmented reality is an application which guides a user through present and into future context by displaying spatial contextual information in their visual system as they traverse through real space.

[4] Numerous examples of LBS user-level software packages (applications), exist which require the ability to leverage spatial contextual awareness.

These applications are in demand by the general public and are examples of how maps are being used by individuals to help better understand the world and make daily decisions.

[1] A three-level model of context awareness (Figure 1) includes the changeable nature of the environment by differentiating between the contributions of static, dynamic, and internal context:[8] Static content is driven by stored information while dynamic content is provided and updated by sensors.

Figure 2 shows Li's[8] components of context awareness and overlays them on multiple geographic reference systems.

It includes a set of concepts, practices and standards for spatial and geographic information and processing for applications accessible for use by the general public.

For that purpose, ubiquitous computing concepts employ sensors to collect data on the user's location as well as environmental parameters.

[2] Ubiquitous cartography is "the ability for users to create and use maps in any place and at any time to resolve geospatial problems".

LBS can include mobile commerce when taking the form of coupons or advertising directed at customers based on their current location.

Applications (user-level software packages) which require the use of spatial contextual awareness in LBS are confronted with a multitude of cartographic challenges and decisions.

[15] Other problems result from the large volume of potentially relevant contextual data as difficult choices need to be made on the most important content to display.