A quantitative analysis of multi-decadal shoreline changes along the East Coast of South Korea

被引:9
作者
Yum, Sang-Guk [1 ]
Park, Seunghee [2 ]
Lee, Jae-Joon [3 ]
Das Adhikari, Manik [1 ]
机构
[1] Gangneung Wonju Natl Univ, Dept Civil Engn, Kangnung 25457, Gangwon Do, South Korea
[2] Sungkyunkwan Univ, Sch Civil Architectural Engn & Landscape Architect, Suwon 2066, Gyeonggi Do, South Korea
[3] Sungkyunkwan Univ, Interdisciplinary Program Crisis Disaster & Risk M, Suwon 2066, Gyeonggi Do, South Korea
基金
新加坡国家研究基金会;
关键词
Coastal dynamics; Landsat imagery; Coastal erosion; accretion; Multi-decadal changes; East coast of South Korea; GEOSPATIAL TOOLS; LANDSAT IMAGERY; STORM SURGES; BEACH; STATISTICS; IMPACT; ACCURACY; CLIMATE; INDIA; PREDICTION;
D O I
10.1016/j.scitotenv.2023.162756
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
South Korea's east coast is facing several issues related to coastal erosion because of sea-level rise, typhoon-induced storm surges, and various coastal development projects. In recent decades, high storm waves have frequently appeared on the east coast, causing casualty, beach erosion, and coastal infrastructure damage, drawing significant public atten-tion. Thus, we analyzed the multi-decadal shoreline changes to understand the coastal dynamics and the forces respon-sible for the spatio-temporal changes along the 173 km coastline. The shorelines covering 38 years between 1984 and 2022 were derived from Landsat images and the change statistics, i.e., linear regression rate (LRR), endpoint rate (EPR), weighted linear regression (WLR), and net shoreline movement (NSM), were calculated at a 100 m alongshore intervals using Digital Shoreline Analysis System (DSAS), revealed several distinct behaviors of shoreline position. The long-period (1984-2022) assessment showed an average shoreline change rate (LRR) of 0.17 m/year with an esti-mated mean erosion and deposition rate of -0.57 and 2.07 m/year, respectively. The long-term surface gain and loss of the backshore region exhibited that the net surface gain of the east coast is 421.13 ha, and the net loss is 181.82 ha. The assessment of decadal shoreline changes showed a cyclic pattern of erosion (from 1984-1990 and 1999-2010) and accretion (from 1990-1999 and 2010-2022). Furthermore, a secondary level of investigation was conducted to address a wider variety of coastal behaviors by segmenting shoreline change rates based on coast types and average slopes along coastlines. It was observed that the frequent coastal deformation is associ-ated with a flatter beach compared to a steep one. This study found that the artificial structures constructed along the east coast have not completely solved or stopped the erosion issues but shifted it from one location to an-other. The analysis of local and regional shoreline changes had shown that typhoon-induced storm surges, high storm waves, and anthropogenic activities like encroachment and the development of artificial coastal structures were the primary drivers of coastline changes along the east coast. Finally, we proposed a decision -making classification scheme that can be used to determine the mechanism of decision for protective and preven-tive measures against further coastal deterioration.
引用
收藏
页数:22
相关论文
共 127 条
[1]   A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery [J].
Abdelhady, Hazem Usama ;
Troy, Cary David ;
Habib, Ayman ;
Manish, Raja .
REMOTE SENSING, 2022, 14 (03)
[2]  
Adhikari M.D., 2016, MODEL EARTH SYST ENV, P1
[3]   Atmospheric correction for short-wave spectral imagery based on MODTRAN4 [J].
Adler-Golden, SM ;
Matthew, MW ;
Bernstein, LS ;
Levine, RY ;
Berk, A ;
Richtsmeier, SC ;
Acharya, PK ;
Anderson, GP ;
Felde, G ;
Gardner, J ;
Hoke, M ;
Jeong, LS ;
Pukall, B ;
Ratkowski, A ;
Burke, HH .
IMAGING SPECTROMETRY V, 1999, 3753 :61-69
[4]   Coastline change detection using remote sensing [J].
Alesheikh, A. A. ;
Ghorbanali, A. ;
Nouri, N. .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, 2007, 4 (01) :61-66
[5]  
Amron A., 2018, E3S WEB CONF, V47, P06001, DOI DOI 10.1051/e3sconf/20184706001
[6]   Anthropogenic effects on shoreface and shoreline changes: Input from a multi-method analysis, Agadir Bay, Morocco [J].
Aouiche, Ismail ;
Daoudi, Lahcen ;
Anthony, Edward J. ;
Sedrati, Mouncef ;
Ziane, Elhassane ;
Harti, Abderrazak ;
Dussouillez, Philippe .
GEOMORPHOLOGY, 2016, 254 :16-31
[7]   The analysis of shoreline change dynamics and future predictions using automated spatial techniques: Case of El-Omayed on the Mediterranean coast of Egypt [J].
Awad, Mohamed ;
El-Sayed, Hossam M. .
OCEAN & COASTAL MANAGEMENT, 2021, 205
[8]   Detection and analysis of historical variations in the shoreline, using digital aerial photos, satellite images, and topographic surveys DGPS: case of the Bejaia bay (East Algeria) [J].
Ayadi, Katia ;
Boutiba, Makhlouf ;
Sabatier, Francois ;
Guettouche, Mohamed Said .
ARABIAN JOURNAL OF GEOSCIENCES, 2016, 9 (01) :1-12
[9]   Evaluation of decadal shoreline changes along the Parnaiba Delta (NE Brazil) using satellite images and statistical methods [J].
Bezerra Ferreira, Thiago Augusto ;
Aquino da Silva, Andre Giskard ;
Reyes Perez, Yoe Alain ;
Stattegger, Karl ;
Vital, Helenice .
OCEAN & COASTAL MANAGEMENT, 2021, 202
[10]   An analysis of the factors responsible for the shoreline retreat of the Chao Phraya Delta (Thailand) [J].
Bidorn, Butsawan ;
Sok, Kimhuy ;
Bidorn, Komkrit ;
Burnett, William C. .
SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 769