Map-matching algorithms must perform an extremely challenging task if we consider the large number of possible road segments to match the position of the vehicle, the GNSS errors and the lack of completeness and accuracy of the digital maps [3].The concept of Enhanced Digital maps (EDmaps), also known as Enhanced Maps (Emaps), appeared with the purpose of creating better maps that could satisfy the needs of some vehicular applications with requirements of terms of map accuracy and completeness higher than those offered by standard maps [4]. Emaps are meant to be more complete and accurate than standard maps. To do so, Emaps may store more detailed data or some parameters that are not usual in standard maps based on polylines.Our Emap proposal aims at supporting positioning and map-matching in urban areas, for which it stores information in two different layers:A road layer, dedicated to describe urban road layouts that is flexible enough to model complicated shapes. When developing Emaps, most of the authors focus their efforts on the accuracy of the centerline of the lane and the estimate of the road curvature. However, in this work another relevant aspect of the map is covered: the accurate representation (in our case, at submeter accuracy) of the road borders in an urban environment, which is contrary to the most common approach of depicting the centerlines, the number of lanes and their widths. This allows further possibilities in map-matching algorithms that can benefit from a more complete description of the road, providing more precise allocations of the vehicles, that are not necessarily referred to the centerline.An elevation layer that contains locations and heights of the buildings along the road. This way, when a vehicle is on a given point of the road, it will be feasible to create a visibility map of the GNSS satellites, detecting whether a satellite is in Line-Of-Sight (LOS) or in Non-Line-Of-Sight (NLOS). When solving the calculation of the vehicle positioning, NLOS satellites can be then removed, avoiding the biases introduced by the multipath effects caused by faulty measurements coming from NLOS satellites. Due to the elevation information stored in the map, the model presented in this paper is named Elevation-Enhanced map, or simply EEmap.The rest of the paper goes as follows: Section 2 presents most relevant works published in this field. Section 3 introduces the EEmap concept and model. Next, Section 4 explains the creation process of the EEmap. Section 5 shows some relevant considerations in terms of accuracy and memory use. Finally, Section 6 concludes the paper.2.?Related exactly WorksDue to its benefits, the concept of enhanced road map has been exploited in former works of the authors in order to achieve lane-level positioning [5], lane-change detection [6] or position integrity [7]. This work follows this research line, adding new contributions to this field.