Land use change monitoring is one of the main concerns of managers and urban planners due to human activities and unbalanced physical development in urban areas. In this paper, a combination of remote sensing data and volunteered geographic information was used to assess the quality of volunteered geographic information on land use and land cover changes monitoring. For this purpose, the ORBVIEW-3 satellite imagery for 2005, the IRS satellite for 2008, 2010, and 2015 and the Google Earth imagery from 2011 to 2019 have been used as the reference database. One of the issues discussed in the field of validating volunteered geographic information in monitoring land-use changes is related to the quality of this information. Various indices have been proposed for evaluating the quality of VGI parameters in the field of validation of land use changes monitoring, includes data completeness, spatial accuracy, and shape accuracy. This paper aimed to evaluate the quality of volunteered geographic information designed for land use changes monitoring and compare the results with satellite images as reference data. In other words, this study seeks to compare the results of volunteered geographic information and satellite imagery to show the accuracy of VGI . Actually, the use of local knowledge of individuals in the urban planning process and the importance of timely information for better management and decision-making in the face of urban progresses such as urban sprawl has led to attention and understanding the importance of VGI in land use change. To validate the VGI, first satellite images were obtained and clustered using unsupervised learning. The use of satellite imagery due to the repeatability with wide and multi-source view of an area increases the credibility and confidence of VGI quality validation.
The VGI collection has been carried out over a web-based GIS which provided a facility for users to register personal information, parcel land use and draw polygons per relevant land use. Finally, volunteered geographic information quality was evaluated. In the first step of validation process, data completeness was assessed. According to the results, the value of VGI completeness has been changed during assessment period, as  by moving away from the present, the accuracy has been also reduced, so that in 2018, 72.7 percent of the volunteered data were completely overlapping with the reference data, but in 2007 this compatibility decreased to 25 percent. In the next step, the spatial accuracy of the data was calculated. The central distance method was used for evaluating this parameter. The results of the distances between the polygons centers of the volunteer data and the polygons centers of the reference data show that the maximum and minimum distance are 14.37 m and 0.09 m, respectively. In the last stage, the shape accuracy of the volunteered data was examined. Due to the standard deviation of 0.61, it can be concluded that the two databases differ significantly.