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2 2022

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Monitoring spatial and temporal scales of shoreline changes in Lahou-Kpanda (Southern Ivory Coast) using landsat data series (TM, ETM+ and OLI)

Zonkouan Badjo Ruth Virginia, Bachri Imane, Beda Abaze Henri Joël, N’Guessan Kpangba Aristide Meniansou

Geomatics and Environmental Engineering

2022

Vol. 16, no. 1

145--158

Shoreline changes are crucial for assessing human-ecosystem interactions in coastal environments. They are a valuable tool for determining the environmental costs of socioeconomic growth along coasts. In this research, we present an assessment of shoreline changes along the eastern coast of Lahou-Kpanda of the Ivory Coast during the period from 1980 to 2020 by applying Digital Shoreline Analysis System method using Landsat Data Series. The measurement of the shoreline dynamics of the Lahou-Kpanda coastline is mainly described in three parts: the west straight cordon, the dynamics at the mouth and the east straight cordon. The findings show a drastic reduction in natural shorelines. The greatest transition occurred along the mouth segment of the coast, where the average erosive velocity approaches 90 meters each year and the average distance has decreased by around 2 kilometers. The Ivory Coast lost more than 40% of its biological shorelines between 1980 and 2020, according to this report, a worrying development because these are regions that were once biologically abundant and highly rich. In general, human operations on the Ivory Coast’s shorelines have never had such an impact. The effects of these changes on habitats, as well as the vulnerability of new shoreline investments to increased human activity and sea-level rise, must be measured.

Assessing the multi-decadal shoreline dynamics along the Purba Medinipur Balasore coastal stretch, India by integrating remote sensing and statistical methods SK

Hossain Ariful, Mondal Ismail, Thakur Sandeep, Linh Nguyen Thi Thuy, Anh Duong Tran

Acta Geophysica

2022

Vol. 70, no 4

1701--1715

Monitoring decadal shoreline change is essential to understand the influence of coastal processes on the coastline. The shoreline is constantly shaped by natural and anthropogenic factors, and so, it is critical to understand decadal trends. The prediction of future shoreline positions is a must for effective long-term coastal zone management. This study was conducted along a 90-km-stretch of the coastline from the mouth of the Haldi River (Purba Medinipur) in the Northeast to the Subarnarekha estuary (Balasore) in the Southwest. The primary objectives of the study were to analyze the decadal shoreline migration using the End Point Rate (EPR) method and then predict future shoreline change prediction using the Kalman Filter method. Shoreline positions were digitized after extracting the shorelines using Principal Component Analysis (PCA) from Multi-temporal (1990, 2000, 2010, and 2020) and Multisensor (Landsat TM, ETM+, and OLI) satellite data. A total of 887 transects were cast to compute change statistics of the time series shoreline. It was observed that the average shoreline change rate was −8.41 m/year in the periods of 1990–2000 and 2000–2010, and −8.80 m/year from 2010 to 2020. Accretion along this coastal stretch is caused by the growth of morphological features such as sand bars, beaches, and dunes. We also found that erosion occurred from 1990 to 2000 along the coastline of Bhograi, Ramnagar-I, Ramnagar-II, a few parts of Contai-I, Khejuri-I, and the Nandigram-I coastal block. Accretion mostly occurred due to Land reclamation in the Northern portion of Bhograi, Contai-1 blocks and Nandigram- I block from 2000 to 2010 and 2010 to2020. Root mean square error (RMSE) and Regression Coefficient values were computed for the future shoreline prediction of 2031 and 2041. The calculated RMSE value of±4.7 m and value of 0.97 shows a good relationship between the actual and predicted coastline of 2020. This study concludes that the coastline of Purba Medinipur-Balasore experienced severe erosion and needs management action and also proves the efficiency of the Digital Shoreline Analysis System (DSAS) tool for decadal analysis and prediction of shoreline change. The findings of this study may help the coastal planners, environmentalists, and coastal managers in preparing both short-term and long-term coastal zone management plans.