http://www.iaeme.com/IJCIET/index.asp 85 editor@iaeme.com International Journal of Civil Engineering and Technology (IJCIET) Volume 11, Issue 3, March 2020, pp. 85-96, Article ID: IJCIET_11_03_009 Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=11&IType=3 Journal Impact Factor (2020): 11.3296 (Calculated by GISI) www.jifactor.com ISSN Print: 0976-6308 and ISSN Online: 0976-6316 © IAEME Publication MARINA SHORELINE CHANGE DETECTION USING REMOTE SENSING AND GIS S. Thangaperumal Assistant Professor, Department of Civil Engineering, St.Joseph’s College of Engineering, Chennai, Tamilnadu, India Cyril Magimai Antoz A Department of Civil Engineering, St.Joseph’s College of Engineering, Chennai, Tamilnadu, India Shivaharan R Department of Civil Engineering, St.Joseph’s College of Engineering, Chennai, Tamilnadu, India ABSTRACT Marina is considered as the world’s second largest urban beach. It has a stretch of 13 Km including a 6 Km promenade. It has been studied in order to understand shoreline changes and erosion/accretion pattern that have been taken place due to the natural processes and anthropogenic activities. The shoreline is one of the rapidly changing coastal landforms. Shorelines are the key element in coastal GIS and provide the most information on coastal landform dynamics. Therefore, accurate detection and frequent monitoring of shorelines are very essential to understand the coastal processes and dynamics of various coastal features. Multi temporal landsat (7 ETM+) satellite images from 2009 to 2019 were used to extract shorelines. The data is processed and analyzed by (Digital Shoreline Analysis System) DSAS an extension tool of ArcGIS. The rate of the shoreline change are calculated by 3 statistical analysis such as (End Point Rate) EPR, (Net Shoreline Movement) NSM and (Linear Regression Rate) LRR. The study had been conducted in summer and winter season and the results obtained are shown in graphs. The result obtained clearly shows Accretion is higher in summer and erosion is higher in winter. Keywords: Erosion, Accretion, Shoreline, Change Detection, Remote Sensing, ArcGIS, Digital Shoreline Analysis System, End Point Rate, Linear Regression Rate, Net Shoreline Movement. Cite this Article: S Thangaperumal, Cyril Magimai Antoz A and Shivaharan R, Marina Shoreline Change Detection Using Remote Sensing and GIS. International Journal of Civil Engineering and Technology, 11(3), 2020, pp. 85-96. http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=11&IType=3