Applying the kalman filter model to forecast shoreline positions: A case study in Şile, İstanbul

Abstract

Coastal zones are remarkably productive and diverse environments on Earth, yet they are also highly vulnerable ecosystems. Therefore, examining both temporal and spatial variations in shorelines, as well as forecasting future shoreline position, is critical for ensuring the sustainability of coastal zones. In this study, historical shoreline change of the Şile (between western part of Şile port and eastern part of the Kumbaba Beach) was analyzed using End Point Rate (EPR), Net Shoreline Movement (NSM), and Linear Regression Rate (LRR) statistics of Digital Shoreline Change Analyses System (DSAS). Future shoreline forecasting was estimated using Kalman Filter method within DSAS tool. To analyze the historical shoreline changes in Şile, 18 shoreline data sets were generated from Google Earth Pro spanning the period from 2002 to 2021. The statistical result of the study indicates that the maximum shoreline progression of Şile between 2002 and 2021 was 41.3 m for NSM and 2.6 m/yr for LRR, while the maximum shoreline regression was -26.2 m for NSM and -1.3 m/yr for EPR. The projected future shoreline for Şile suggests that the most substantial shoreline advancement is anticipated to occur between 2031 and 2041, particularly in designated areas such as zone I, zone II, and zone III. Conversely, significant shoreline regression is forecasted to transpire in zone IV during the same periods. As a result, the shoreline of Şile has witnessed notable shoreline alterations throughout its history, and it is expected to continue experiencing significant changes in the future.