Abstract
Abstract. The completeness of the number of Open- StreetMap (OSM) retail stores was estimated for two federal states of Germany at district level. An intrinsic measurement was applied that fits saturation models on the cumulative curve of the number of OSM retail stores over time. Even though the mean completeness of retail stores was estimated high in both states, the values within the states varied between 42 % and 100 %. The question therefore arises in which areas retail stores are well represented in OSM and whether economically weaker regions are possibly also digitally disadvantaged on the map. We investigated the influence of the urban-rural gradient as well as the influence of socioeconomic factors (gross domestic product, the unemployment rate, the proportion of academics) on the estimated completeness by means of a generalized linear model. Our results indicate that average big cities with low unemployment rate are better mapped with respect to retail stores.
Highlights
The ubiquity of smartphones has lead to a continuous availability of geodata
For five districts the data history showed a steady high increase in the number of OSM retail stores and did not indicate any slow down in growth rate while eight regions produced low quality saturation models due to complex temporal pattern. These issues occurred independent of influencing factors such as population density due to non continuous mapping activities and the respective regions had to be ignored for the generalized linear model (GLM)
This study was applied to the use for case of retail stores but the approach may be transferred to e.g. roads or land use data by substituting the store count with road network length or land use area
Summary
The ubiquity of smartphones has lead to a continuous availability of geodata. In day to day life, especially at less familiar locations, shops and restaurants are some of the most frequently searched points of interest (POI). Shop owners have great interest in being well represented in these POI collections for advertisement and visibility reasons. While big players such as Apple, Google and Microsoft dominate the market, the Volunteered Geographic Information project OpenStreetMap (OSM) provides an established non-commercial crowd sourced alternative. OSM contains an enormous amount of various geodata, that are continuous edited by the great number of more than 7.5 million volunteers (state of March 2021, OpenStreetMap contributors (2021)). The advantage of OSM over commercial providers of geodata is the free availability under the Open Data Commons Open Database License that allows an unrestricted use in many commercial or non-commercial applications. Due to the high growth rates of OSM in recent years, a high completeness can be assumed for other objects such as buildings or stores
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