Analytical Comparison of Methods for Calculating the Completeness of VGI

Spatial data, which is one of the main needs of human societies from business organizations to the general users today, cannot meet the needs of a wide range of users without changing the structure of conventional methods of data registration and updating on a metropolitan scale. Open Street Map, as one of the most successful implementations of the crowdsourcing approach to spatial data with the participation of the public users as the millions of scattered sensors in the environment, has provided a solution to achieve several goals such as improvement in rapid data collection and coverage of areas. Apart from the numerous benefits of volunteered geographic information, the reliance of this information solely on the participation and activity of users challenges the use of this data in various applications. However, this problem is exacerbated by the lack of the necessary frameworks for entering incorrect data, different levels of user knowledge, and different methods of data entry. Among the quality parameters, the completeness parameter, which provides the presence of one data set compared to another data set and shows the degree of importance of the features from the users' point of view, was discussed in the present study. It is also important to address this aspect of the quality of VGI in terms of its impact on the other quality parameters. In this study, after introducing the common approaches in evaluating this element of data quality and comparing the results of methods, the strengths and limitations of each method are also explained. In the general classification, the completeness parameter is examined by two region-based and the object-based approaches. After comparing results, the necessary pre-processing, and the analysis time of each method, the findings of this study demonstrate the high speed of evaluation of the region-based approach and the higher accuracy of object-based methods. Moreover, the mentioned advantage of region-based approach is achieved if there is no topological error in the VGI and there are correspondence relationships between the uses of both data sets. On the contrary, the object-based methods despite the high calculation due to the matching process; If they use the appropriate matching algorithm and guarantee the positional accuracy, they will provide more accurate results for the completeness parameter. Moreover, the object-based methods, with the possibility of calculating the omission and commission of the VGI data set compared to the official data set, provide a more accurate understanding of the completeness parameter. In the region-based approach, it is not possible to evaluate the completeness parameter separately due to the combination of these two sub-sectors. In the region-based approach, evaluation of the completeness parameter was implemented by parameters such as the ratio of the length of the two data sets, the ratio of the number of constituent points of features, and the ratio of the number of features. From the above three criteria, the length ratio of the two data sets was selected as a suitable evaluation criterion by less pre-processing analysis such as creating the graph structure in the number of features criteria and simplifying the lines in the constituent points of features. However, the length criterion in topologically erroneous datasets strongly affects the evaluation results. At the end, after introducing and using the vector matching algorithm based on determining the geometric similarity of the features, the completeness parameter was calculated as 66.2. High rate of two quantities of omission and commission information of the VGI data set compared to the official data set of 33.8 and 47.8 in the current study due to the weakness of the matching algorithm in the two data sets, it is expected that with the improvement of this algorithm, the amount of identified omission and commission information will be reduced.