Coastline extraction using remote sensing: a review

被引:55
作者
Sun, Weiwei [1 ]
Chen, Chao [2 ]
Liu, Weiwei [1 ]
Yang, Gang [1 ]
Meng, Xiangchao [3 ]
Wang, Lihua [1 ]
Ren, Kai [1 ]
机构
[1] Ningbo Univ, Dept Geog & Spatial Informat Tech, Ningbo, Zhejiang, Peoples R China
[2] Suzhou Univ Sci & Technol, Sch Geog Sci & Geomatics Engn, Suzhou, Jiangsu, Peoples R China
[3] Ningbo Univ, Fac Elect Engn & Comp Sci, Ningbo, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Coastline; remote sensing; image analysis; review; implementation; TASSELED CAP TRANSFORMATION; GRADIENT VECTOR FLOW; DEEP LEARNING-MODEL; SHORELINE CHANGES; COASTAL ZONE; SATELLITE IMAGES; INFORMATION EXTRACTION; EDGE-DETECTION; GIS TECHNIQUES; CLIMATE-CHANGE;
D O I
10.1080/15481603.2023.2243671
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Coastlines are important basic geographic elements and mapping their spatial and attribute changes can help monitor, model and manage coastal zones. Traditional studies focused on the accuracy of extraction methods and the evolution characteristics of coastlines. Thanks to the advances in remote sensing for earth observations, recent coastline extraction studies can reveal detailed ocean-land interaction changes. In this review, we aim to identify key milestones in coastline extraction using remote sensing by associating the emergence of major research topics with the occurrence of multiple application fields, multiple data sources, and multiple algorithms. Specifically, we define coastlines that can be applied to different application fields, summarize the characteristics of coastline products, and analyze the principles, advantages and disadvantages of methods. On this basis, we discussed the development direction and the challenges involved. This study provides practical insights that can be incorporated into the future development of coastline extraction approaches using remote sensing technologies.
引用
收藏
页数:26
相关论文
共 195 条
[71]   Remote Sensing of the Coastline Variation of the Guangdong-Hongkong-Macao Greater Bay Area in the Past Four Decades [J].
Hu, Ruirui ;
Yao, Lijun ;
Yu, Jing ;
Chen, Pimao ;
Wang, Dongliang .
JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2021, 9 (12)
[72]   Earth observations and geographic information science for sustainable development goals [J].
Im, Jungho .
GISCIENCE & REMOTE SENSING, 2020, 57 (05) :591-592
[73]   Advances in Remote Sensing-Based Disaster Monitoring and Assessment [J].
Im, Jungho ;
Park, Haemi ;
Takeuchi, Wataru .
REMOTE SENSING, 2019, 11 (18)
[74]   Assessment of shoreline changes over the Northern Tamil Nadu Coast, South India using WebGIS techniques [J].
Jayakumar, K. ;
Malarvannan, S. .
JOURNAL OF COASTAL CONSERVATION, 2016, 20 (06) :477-487
[75]   Rapid, robust, and automated mapping of tidal flats in China using time series Sentinel-2 images and Google Earth Engine [J].
Jia, Mingming ;
Wang, Zongming ;
Mao, Dehua ;
Ren, Chunying ;
Wang, Chao ;
Wang, Yeqiao .
REMOTE SENSING OF ENVIRONMENT, 2021, 255
[76]   A deep learning model using geostationary satellite data for forest fire detection with reduced detection latency [J].
Kang, Yoojin ;
Jang, Eunna ;
Im, Jungho ;
Kwon, Chungeun .
GISCIENCE & REMOTE SENSING, 2022, 59 (01) :2019-2035
[77]   Three Decades of Coastal Changes in Sindh, Pakistan (1989-2018): A Geospatial Assessment [J].
Kanwal, Shamsa ;
Ding, Xiaoli ;
Sajjad, Muhammad ;
Abbas, Sawaid .
REMOTE SENSING, 2020, 12 (01)
[78]   Spatio-temporal shoreline changes along the southern Black Sea coastal zone [J].
Karsli, Fevzi ;
Guneroglu, Abdulaziz ;
Dihkan, Mustafa .
JOURNAL OF APPLIED REMOTE SENSING, 2011, 5
[79]   SNAKES - ACTIVE CONTOUR MODELS [J].
KASS, M ;
WITKIN, A ;
TERZOPOULOS, D .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 1987, 1 (04) :321-331
[80]   Using GPS-surveyed intertidal zones to determine the validity of shorelines automatically mapped by Landsat water indices [J].
Kelly, Joshua T. ;
Gontz, Allen M. .
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2018, 65 :92-104