Performance study of imageries from MODIS, Landsat 8 and Sentinel-2 on measuring shoreline change at a regional scale

Abstract

In monitoring shoreline change, remote sensing data plays a pivotal role. Although different freely accessible satellite data are used in studies of shoreline change at various scales, it is imperative to identify their effectiveness at a regional scale. This study aims to determine how effectively MODIS, Landsat 8, and Sentinel-2 satellite images measure regional shoreline change. Digital Shoreline Analysis System (DSAS), an ArcGIS extension, was utilized to analyze the changes in the shoreline of Ganges deltaic coast in Bangladesh. The Shoreline Change Envelope (SCE) technique was applied to compare the shorelines extracted from MODIS, Landsat 8, and Sentinel-2 for the year 2016 with high-resolution Google Earth image. Next, using the End Point Rate (EPR) method, shoreline change rates between 2016 and 2019 were calculated separately from each satellite data. The study points out which satellite data was more accurate in delineating shoreline. Due to a higher spatial resolution, Sentinel-2 data were more effective than Landsat and MODIS data at a regional scale. In addition, MODIS, Landsat 8, and Sentinel-2 data indicate that the Ganges deltaic coast experiences landward movements of 54.65 m/yr, 12.56 m/yr, and 1.79 m/yr, respectively. Hence, it can be concluded that if the spectral resolution is coarse, shoreline change is overestimated. Therefore, in order to analyze or predict shoreline change (even at a regional scale), priority should be given to using images with fine spatial resolution. The spectral analysis of MODIS, Landsat and Sentinel showed a similar pattern of separability among the land cover classes observed along the Ganges deltaic coast. The separability is higher in NIR (Near Infrared) and SWIR (Short Wave Infrared) bands. This study will direct researchers in the selection of remote sensing data sources for shoreline change detection within a regional scale.