Abstract

The coastal area is an intersection between mainland and ocean. The tourism potential in the coastal area of Bulak District in Surabaya is expanded. It is shown by the construction of Surabaya Bridge in 2015. This construction will affect land use change. Remote sensing technology is one of the acquisitions to monitor land use change. This research focuses on identifying the land use change in the coastal area in Bulak District, Surabaya, in 2014 and 2020, as well as to determine the accuracy of classification method applied for mapping the land use change in 2020. The application of 2014 acquisitions data was used as the bridge construction plan, while the application of 2020 acquisitions data was used as the premise for the land classification system in the previous year. There are two methods used to classify land use in coastal areas, that is pixel-based classification (maximum likelihood algorithm) and object-based classification (nearest neighbor algorithm). The research shows that there are 6 land use classes in study area: built-up land, rice fields, forests, shrubs, non-built-up land, and ocean. By applying these two methods, the result shows different area changes. The conversion of the highest mainland by applying a pixel-based classification was found in built-up land (+23.03 ha) and rice fields (-24.84 ha), while the area changes by applying object-based classification method were found in built-up land (+32.75 ha) and rice fields (-26.91 ha), respectively. The accuracy by applying the pixel and object-based method is 89% and 92%, respectively, from the percentage indicates good interpretation.

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