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Sandy coastline fine extraction and correction method based on high resolution image
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Hang Yin1, Hongshuai Qi1, 2, *, Feng Cai1, 2, Chi Zhang3, Gen Liu1, Shaohua Zhao1, 2, Jiacheng Song1, 3, Guorun Zhao1, 3
Haiyang Xuebao | 2022, 44(4) : 143 - 152
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Haiyang Xuebao | 2022, 44(4): 143-152
Article
Sandy coastline fine extraction and correction method based on high resolution image
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Hang Yin1, Hongshuai Qi1, 2, *, Feng Cai1, 2, Chi Zhang3, Gen Liu1, Shaohua Zhao1, 2, Jiacheng Song1, 3, Guorun Zhao1, 3
Affiliations
  • 1. Laboratory of Ocean and Coast Geology, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China
  • 2. Fujian Provincial Key Laboratory of Marine Ecological Protection and Restoration, Xiamen 361005, China
  • 3. College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China
Published: 2022-04-15 doi: 10.12284/hyxb2022084
Outline
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The stable acquisition of large-scale and continuous coastline data through remote sensing is an important basis for the development of coastal zone research. Aiming at the problems of noise sensitivity and threshold instability in the traditional edge detection algorithm for high-resolution remote sensing images, the strected forests edge detection algorithm based on the structured random forest model is introduced to identify the sandy shoreline of the west coast of Haikou City, and proposed based on the Bruun-Dean balanced profile model, a new method of tide level correction is established to fit the profile model, and finally the fine coastline data is extracted. Based on the measured data, the precision evaluation and error analysis of the extraction results are carried out, and the prospects for method improvement and popularization and application are put forward. The research show that: (1) the result of the water edge line detected by the strected forests edge detection algorithm is clear and delicate, which is more accurate and efficient than the traditional edge detection operator methods such as Roberts operator, Canny operator, and LoG operator, and is suitable for the study of coastline extraction from high-resolution remote sensing images; (2) aiming at the tide level correction of the sandy coastline, the fitted profile model established based on the RTK measured data and the fitted profile model overcomes the large error of the traditional linear model and improves the accuracy and feasibility of the coastline correction; (3) based on actual measurement for the shoreline, the results are quantitatively analyzed using the section method, and it is verified that the positioning accuracy of the extracted shoreline is better than 2.5 m.

WorldView-2  /  coastline  /  edge detection  /  balanced profile mode  /  tide level correction  /  high resolution image
Hang Yin, Hongshuai Qi, Feng Cai, Chi Zhang, Gen Liu, Shaohua Zhao, Jiacheng Song, Guorun Zhao. Sandy coastline fine extraction and correction method based on high resolution image[J]. Haiyang Xuebao, 2022 , 44 (4) : 143 -152 . DOI: 10.12284/hyxb2022084
Year 2022 volume 44 Issue 4
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Article Info
doi: 10.12284/hyxb2022084
  • Receive Date:2021-07-19
  • Online Date:2026-02-01
  • Published:2022-04-15
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History
  • Received:2021-07-19
  • Revised:2021-08-27
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Affiliations
    1. Laboratory of Ocean and Coast Geology, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China
    2. Fujian Provincial Key Laboratory of Marine Ecological Protection and Restoration, Xiamen 361005, China
    3. College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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