Urban Land-Cover Classification Utilizing Sentinel 2 Data for Landscape Planning and Management in Vietnam

The Copernicus Sentinel 2 data could be essential for an effective land-cover classification for urban policymakers. While huge expenses and complicated post-processing issues are well-recognized by the city authorities, a convenient approach is hardly available to apply with other commercially available data sources. Freely available Sentinel 2 data, even with 10–60 m resolution, could be an essential addition for policymakers, especially for classifying urban landscapes. Here, the Geographic Object-based Image Analysis (GEOBIA) approach has been applied in the eCognition platform utilizing a Sentinel 2 image for the urban land-cover classification in Hue, Vietnam. Currently, four different classes, i.e., streets, buildings, vegetation, and water resources, have been applying the GEOBIA approach. Concerning the data availability and post-processing approach, this study could be a way out for urban policymakers due to the convenience and simplicity of the applied algorithms. So, this study will certainly assist city planners either in the case of developed or third-world developing ones, where it is much more necessary for efficient urban space management.