COASTLINE CHANGES DETECTION USING SENTINEL-1 SATELLITE IMAGERY IN SURABAYA, EAST JAVA, INDONESIA
Keywords:
coastline, sentinel-1 images, extracted parameter, threshold, overlayAbstract
One of the most important linear features on the earth’s surface is coastline. Coastal zone and its environmental management require the information about coastlines and their changes, which display a dynamic nature. The coastal area of Surabaya has the most dominant sedimentation. This is due to the presence of several large rivers flow in the area, which brings sediment to the estuary. In addition, the development of Suramadu bridge that across Madura strait, connecting Java and Madura islands, has opened an opportunity for the areas around the Suramadu Bridge to be the region of industry activities in East Java. It can give sizeable influence for the physical change that happens around the Suramadu Bridge in particular south coastal area of Bangkalan, Madura and north coastal area of Surabaya as the change of coastline and the wide change of land area caused by natural factor or human activities. Sentinel-1 is one of a Sentinels technology which is a polar-orbiting, all-weather, day-and-night radar imaging mission for land and ocean services at C-band. This image is not limited by weather conditions or darkness and effective to separate land and water objects. The availability of Sentinel-1 images that have high spatial resolution and high temporal frequency, facilitate the monitoring of coastline changes. The aim of this paper was to analyze the ability of Sentinel-1 imagery to delineate coastline and their changes. Detection of the coastline changes can be done by choosing the best extracted parameter from Sentinel-1 and by setting threshold for land and water separations. Furthermore, the results of processed images were overlayed based on multi temporal. From this research, it could be expected that sigma-nought from VH polarization is the best parameter for the land and water separations which threshold determination is according to the distribution values of sigma-nought. However, there are no big differences of coastline changes viewed by changes detection in some Sentinel-1 images since the monitoring was carried out every month.
References
Alesheikh, A. A., Ghorbanali, A., and Nouri, N., “Coastline Change Detection Using Remote Sensing,” Int. J. Environ. Sci. Tech., vol. 4, no. 1, pp. 61-66, 2007.
Handayani, H. H., Yuwono, Khomsin, and Taufik, M., “Study for Comparative Analysis of Changes in Shore Line Using Multi Stage Satellite Images (Case Study: Gresik and Bangkalan, Indonesia),”FIG Congress, Kuala Lumpur, Malaysia, 2014.
Liu, H. and Jezek, K. C., “A Complete High-Resolution Coastline of Antarctica Extracted from OrthorectifiedRadarsat SAR Imagery,” Photogrammetric Engineering & Remote Sensing, vol. 70, no. 5, pp. 605–616, May 2004.
Lopez-Caloca, A., Tapia-Silva, F.O., and Escalante-Ramirez, B., “Lake Chapala change detection using time series,” Remote Sens. Agric. Ecosyst.Hydrol., vol. 7104, pp. 1–11, 2008.
Matgen, P., Hostache, R., Schumann, G., Pfister, L., Hoffmann, L., and Savenije, H.H.G., “Towards an Automated SAR-based Flood Monitoring System: Lessons Learned from Two Case Studies,” Physics and Chemistry of the Earth, vol. 36, pp. 241–252, 2011.
Rohmah, M. N., “Study of Coastline Change in The Surabaya and Madura Coastal Area after The Development of Suramadu Bridge Using Multi Temporal Satellite Image,” Undergraduate Thesis, Sepuluh Nopember Institute of Technology, Indonesia, 2013.