The influence of urban stractures, vegetation cover, and utilized data in urban impervious surface mapping from multi-source data

Given the significant impact of expanding impervious surfaces on the urban environment, obtaining accurate and up-to-date information about impervious surfaces (IS) is important in urban planning and sustainable management. Remote sensing data, especially aerial photos, have a high potential to provide the mentioned information and have been successfully used in recent years. Despite the widespread use of these data in urban impervious surfaces (UIS) mapping, the reliability and accuracy of the final map still need further investigation. Therefore, in this study, using a detailed and precise classification scheme, drone, and Sentinel satellite data, the impact of three parameters including utilized data, urban structure, and vegetation canopy on the output maps accuracy was evaluated. The results showed that all three factors are of great importance and may cause significant uncertainty in the output maps. Vegetation cover can lead to up to 10% underestimate in the IS. Additionally, changes in urban structure in different areas and changes in the utilized data can also result in a 20% change in the overall accuracy. Results from this work can be used to provide a proper understanding of the reliability of remote sensing products and depict directions for future methodological development