Araştırma Makalesi

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

Sayı: 85 30 Haziran 2024
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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.

Keywords

Etik Beyan

Dear Editor, I present to you our manuscript titled “Applying the kalman filter model to forecast shoreline positions: a case study in Şile, İstanbul”. I and the other author certify that this study has not been published in any journal, that it is not under consideration for publication elsewhere, and that its submission for publication in “Türk Coğrafya Dergisi” has been approved by all of the authors and the institution where the work was carried out. Any change in my address, telephone or fax will immediately be directed to the Editorial Office. We affirm that we have no financial affiliation (e.g., employment, direct payment, stock holdings, retainers, consultant ships, patent licensing arrangements, or honoraria) or involvement with any commercial organization with direct financial interest in the subject or materials discussed in this manuscript, nor have any such arrangements existed in the past three years. Any other potential conflict of interest is disclosed. I will be happy if you kindly accept our manuscript for editorial review. I look forward to hearing from you soon. Yours faithfully.

Kaynakça

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Ayrıntılar

Birincil Dil

İngilizce

Konular

Coğrafi Bilgi Sistemleri , Uzaktan Algılama

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

30 Haziran 2024

Gönderilme Tarihi

16 Nisan 2024

Kabul Tarihi

11 Haziran 2024

Yayımlandığı Sayı

Yıl 2024 Sayı: 85

Kaynak Göster

APA
Kılar, H., & Aydın, O. (2024). Applying the kalman filter model to forecast shoreline positions: A case study in Şile, İstanbul. Türk Coğrafya Dergisi, 85, 47-53. https://doi.org/10.17211/tcd.1469434

Cited By

Yayıncı: Türk Coğrafya Kurumu