Shoreline Change Detection Using DSAS: Case Study in PT IWIP Mining Industrial Area, North Maluku Province, Indonesia

Graphical Abstract Highlight Research DSAS based on geographic information systems has the ability to extract important information on the dynamics of shoreline changes, both accretion and abrasion. The dynamics of shoreline change in the short period of time 2018-2023 in the IWIP industrial area shows a very dynamic change process dominated by accretion. The conversion of beach into land was more prevalent than the process of shoreline retreat in the study area. The abrasion rate in this study area was categorized as moderate, while the accretion rate was categorized as very high due to construction activities. Abstract The development of industrial estate infrastructure in coastal areas causes significant changes in coastal morphology. Despite extensive infrastructure development in coastal zones, limited empirical data exists on the shoreline dynamics of newly established industrial estates, particularly in Eastern Indonesia, thus highlighting the urgency of this study. This study investigates coastal morphology changes in the PT Indonesia Weda Bay Industrial Park (IWIP) industrial area over five years using Landsat 8 OLI level 2A satellite imagery and geospatial analysis. Shoreline extraction was performed using the Normalized Difference Water Index (NDWI) algorithm and analyzed with the Digital Shoreline Analysis System (DSAS) applying the Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR) methods. The findings show that from 2018 to 2023, the shoreline in the PT IWIP area predominantly experienced accretion. The highest rate of shoreline accretion occurred in industrial zone, with a maximum of 147.58 m/year and an average of 36.56 m/year, while residential zones in the eastern and western regions experienced moderate abrasion, with a maximum of 12.32 m/year and an average of 4.11 m/year. Categorization followed standard DSAS criteria, where shoreline changes between 10–30 m/year were considered moderate, and changes above 30 m/year were classified as very high. Measurement accuracy was validated using high-resolution Google Earth imagery and Landsat metadata, ensuring positional accuracy within ±30 meters. These results highlight the rapid and spatially varied shoreline changes driven by industrial activities, emphasizing the importance of remote sensing in monitoring and managing coastal development impacts