Car navigation has become one of the most widely used examples of Location-Based Services (LBSs). However current car navigation systems are not fully suitable for the navigational needs of pedestrians mainly because walkers are not as restricted as car drivers. Pedestrians can easily go into a building or underground to get to their destination where GPS signals are unavailable. Seamless indoor and outdoor navigation is one of the most important features which should be handled in a pedestrian navigation application. Another aspect of pedestrian navigation which is not applicable to car navigation are alternatives to turn-by-turn navigational instruction delivery. In contrast with drivers, pedestrians have a higher degree of freedom in their movements. They are not constrained by road networks (for example vehicle lanes, turn restrictions, one-way streets) and can walk in places where vehicles are not allowed to move, such as squares, parks, grasslands or pedestrian malls, which can be traversed freely in any direction. As current turn-by-turn navigational instructions to be given to vehicle drivers are mostly based on graph-based or street network-based algorithms, this way of navigating is not fully suitable for pedestrians as they do not only move on streets. In both of these challenges for useful pedestrian navigation systems, seamless indoor/outdoor positioning and non-turn-by-turn navigational instructions, other information such as the use of landmarks can be helpful. It is possible to calculate the position of a user based on proximity to known landmarks. Their relative position can be sensed using wireless systems, ultrasound, dead-reckoning and inertial sensors as well as conventional GPS. Landmark extraction can be performed manually or semi-automatically using conventional cartographic data-capture techniques or using technologies such as aerial image processing or laser scanning. Since landmarks can be detected and labelled both indoors and outdoors, it is possible to use them with users’ locations seamlessly. Several researchers in the field of spatial cognition assert that navigating humans rely on three forms of spatial knowledge: landmark, route and survey knowledge (Siegel, 1975), (Werner, 1997). Exploring an unfamiliar environment, pedestrians first notice outstanding objects or structures at fixed locations. These unique objects or places are easy to recognize and can be kept in memory without difficulty (Millonig, 2005). The importance of landmarks for pedestrian navigation and wayfinding instructions has been demonstrated (Michon, 2001), (Tom, 2003), (Lovelace, 1999), (Raubal, 2002). If landmark data is stored in a spatial database, it is possible to provide users with navigational instructions landmark-by-landmark rather than turn-by-turn. A landmark-based navigation service would provide users with navigational instructions of the form “turn right when see Tower A”, and “go straight on passing by Statue B. whenever they approach each landmark. One of the most important advantages of landmark-based navigation is that it makes the pedestrian sure that they are on the correct route, since they can see the very landmark which was used as a part of navigational instruction. Also this approach is more compatible for tourists and visitors. It is possible to add some attribute data or images of landmarks while navigating, so they will see more while visiting an area in addition to being directed. In order to implement our model, the campus of National University of Maynooth was considered. Buildings and important features, such as sports pitches and library were stored in a spatial database as outdoor landmarks. In addition, indoor landmarks such as main entrances and geo-tagged wall features (notice-boards etc.) were stored as indoor landmarks. All the landmarks were modelled with polygonal shapes, four pictures were captured and also attributes such as the name in English, name in Irish, land use and description were collected and stored in a spatial database. After locating the user, navigational instructions are provided using a description and pictures of the nearest landmark on the pre-calculated route. To select a picture of each landmark, the direction of user movement is used to find the most similar to the view the user has.