Roghayeh Adabi; Rahim Ali Abbaspour; Alireza Chehreghan
Abstract
Extended AbstractIntroductionIn recent years, data has become the life-giving force of developing innovations in smart cities all around the world. The up-to-date, availability, and freeness of this data are the deciding factors in their frequent use in smart city projects. Today, different sources of ...
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Extended AbstractIntroductionIn recent years, data has become the life-giving force of developing innovations in smart cities all around the world. The up-to-date, availability, and freeness of this data are the deciding factors in their frequent use in smart city projects. Today, different sources of information on city-related issues are available. They are crucial for driving towards “Smart Cities”. Among these sources is the Open Street Map (OSM) project, which is a free and open-source information repository used in many urban and non-urban-related applications. At present, OSM is used for a wide range of applications, for example, navigation, location-based services, construction of 3D city models, and traffic simulation. In the meantime, building blocks are among the OSM data that plays a key role in urban-related studies. These studies include constructing 3D building models, modeling urban energy systems, and land-use management in smart cities. Regarding the importance of completeness in the quality of spatial data, this study will assess the historical course of building blocks data completeness in OSM. Materials and methodsThe 20 districts of the Tehran metropolis have been selected as the study area. This city, with an area of 730 square kilometers and a population of around 8 million people covers the center of Tehran. The main purpose of this study is to present an analysis of the completeness of building block data in the OSM for the Tehran metropolis in 10 years (between 2011 and 2020). To reach this aim, an object-based approach based on object matching was used to assess the completeness parameter. Results and DiscussionThe findings of this study demonstrate that during the recent two years, OSM building block data in Tehran increased in terms of the number of features and the completeness of geometric information considerably. The number of data increased from 300 features in 2011 to 40.138 features in 2020, as well as the number of features edited and added to the OSM dataset increased from 38 and 194 in 2011 to 28680 and 10705 in the end of 2020, respectively. The completeness of OSM building block data in Tehran has increased from 0.18% in 2011 to 2.7% in 2020. Moreover, the evaluation of the completeness of OSM data in different regions of Tehran shows that the completeness of all regions of Tehran was less than 1% from 2011 to 2014, and in the last two years, for 12 of 20 regions of Tehran, the completeness is still less than 1%, but for the other eight regions (i.e., the regions no. 1, 2, 4, 5, 11, 15, and 20), which are mostly located in the northern part of Tehran, the completeness has increased. However, the data have many weaknesses in terms of the attribute information completeness. ConclusionThis study has provided a clear view of OSM building block status in Tehran. In addition, it has provided a better view of OSM data in different regions of Tehran. The insights gained from this study can lead toward creating the awareness required to use of these data in various fields of application. It can also assist local and national managers and related organizations to support active regions and encourage inactive regions. This paper represents a potential starting point for many possible future research directions in smart cities, especially in Tehran. Smart cities can conduct similar studies to understand the state of OSM data in their regions, make plans based on the findings, and manage their space more efficiently. To conduct future research, we evaluate the factors affecting the growth and development of OSM data and the efficiency of the OSM data in some smart city applications.
