Shoreline change detection using multitemporal remote sensing images

Abstract

In this study we used multitemporal remote sensing data, including DMC aerial images and SPOT-5 satellite images, to detect shoreline change of I-Lan coastal zone. We chose wet-dry line, vegetation line and water line as proxies for shoreline position, and then classified the images into different classes by means of supervised image classification. Based on the classification results obtained from images acquired on different dates, shoreline changes was assessed. The study shows that using DMC images can detect shoreline efficiently; however, its high spatial resolution causes serious salt and pepper effect. On the other hand, using SPOT-5 satellite images can only get little information of shoreline due to its limited spatial resolution.