In this context, the methods based on lines have a wide field of application. This large amount of GI continually added and updated requires new mechanisms to control their quality feasibly and rapidly. Obviously, the positional quality of this data must also be controlled because users require a level of quality similar to that demanded for data produced by institutions. Consequently, we must consider that a large amount of VGI data are composed of lines. As an example, VGI includes routes and tracks surveyed and shared by users on applications such as OpenStreetMap, Wikiloc, etc. Goodchild (2007) suggested the term Volunteered Geographical Information (VGI) to include those data produced by citizens in this context. Thus, users are producing, sharing and consuming geospatial data continuously. Nowadays, this evolution supposes a change of paradigm because GI is no longer solely generated by traditional producers. In addition the global distribution of mobile devices, which has greatly eased positioning measurement, and consequently the development of location-based services, has obviously contributed to this expansion. As a consequence, the demand of GI has expanded to those user segments who were not used to these type of products in the past. An example of this increase of availability on the Internet is the development and establishment of Spatial Data Infrastructures, which allow users to access GI easily. This tendency has been based mainly on the growing concern of producers and users for the quality of products and services and the increase of the availability of the geographic information (GI) on the Internet, which implies a greater demand of data quality on the part of producers and users. The quality requirement of spatial databases has undergone a great development during the last few decades. This premise has been analysed during recent years by several authors. Definitely, the use of linear elements can be considered for assessing the positional accuracy of spatial databases. Lines are acquired much more comfortably and quickly Ruiz-Lendínez et al. Nowadays the acquisition of lines from a more accurate source has achieved a great improvement thanks to the evolution of the acquisition devices and to the development of kinematic measuring techniques. Maybe this selection was caused by the best definition of these elements, both in the database and in reality, and the ease of determination of the coordinates using classical surveying, including static observations performed using Global Navigation Satellite System (GNSS). Despite the fact that lines are commonly well-distributed and well-defined on a map, producers and institutions have traditionally used points to check the positional accuracy. Lines contain a great deal of geometrical information defined by a large quantity of vertexes ( Mozas & Ariza, 2011). Secondly, the analysis of these elements can improve the results of the assessment because of their own spatial characteristics. In fact, lines suppose the large group in a spatial database ( Cuenin, 1972) and they usually have a good spatial distribution over any area ( Mozas-Calvache & Ariza-López, 2014). Firstly, there are more types of elements in a spatial database such as lines or polygons. However, there are several aspects to be considered related to the positional accuracy of spatial databases. In general, the coordinates of these points are compared to those obtained from more accurate sources using several metrics (e.g. There are several methods and standards published by several authors and institutions during the last decades which use a sample of well-distributed points ( USBB, 1947 ASCE, 1983 ASPRS, 1990 FGDC, 1998) to determine the positional accuracy of cartographic products. The use of lines supposes an important alternative to the traditional controls based on points both independently or in a complementary way. A line can be defined by a set of ordered vertexes that are connected by segments. This study is focused on positional accuracy and more specifically on its assessment based on linear elements. Other components include attribute accuracy, temporal accuracy, logical consistency and completeness ( ISO, 2013). Positional accuracy is one of the main components of quality related to spatial databases (Mozas-Calvache & Ariza-López, 2011). This article summarizes the main methods and applications developed, until this moment, for assessing and/or controlling the positional accuracy of spatial databases based on lines.
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