The Coastline Extraction for Fujian Province Based on Long Time Series of Remote Sensing Image

Liangzhao, Lin; Zengdi, Pan; Kang, Xiao; Na, Ye

doi:10.2991/rsete.2013.16

Cited by 2 publications

(1 citation statement)

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“…Firstly, Figure 10 displays the results of the extraction using the proposed method. Secondly, the Comparison of results using different methods is shown in Figure 11, where exhibits the result of the CNN method [30][31][32][33]. From Figure 11(a), it can be seen that the coastline has the breakpoints, disconnected situations, and the lowest accuracy.…”

Section: Resultsmentioning

confidence: 99%

Automatic Regionalized Coastline Extraction Method Based on High-Resolution Images

Lu,

Wang,

Liang

et al. 2024

IEEE Access

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To address the problems of low accuracy and the extracted coastlines with breakpoints in most existing coastline extraction methods, this paper proposes a regionalized coastline extraction method combined Simple Linear Iteration Clustering (SLIC), Bayes' theorem, and Metropolis-Hastings (M-H) algorithm for high-resolution images. First, the SLIC algorithm is utilized to segment the superpixels for the high-resolution images. Associated with each superpixel, there is a random label, and the label belongs to the land or the ocean. Under the assumptions that all pixels in the superpixel have the same label, that is, the label of the superpixel. On this basis, the Bayes' theorem and the M-H algorithm are combined to define the superpixel labeling optimization function. The optimal results of the function are obtained to achieve coastline extraction after numerous iterations, where the corresponding result of the labeling optimization function is calculated by altering the label of the superpixel in each iteration. Finally, the proposed method is tested on high-resolution images. In the superpixel segmentation, the qualitative results and quantitative evaluation metrics (Boundary Recall and Under segmentation Error) are used to determine the optimal size of superpixel for the image, and the optimal superpixel segmentation is obtained; On the optimal superpixel segmentation, the coastlines are extracted by the Bayes' theorem and the M-H algorithm; From the qualitative results, it can be seen that the proposed method only extract the coastlines, and the extracted coastlines have no breakpoints; According to quantitative evaluation metrics, its average Recall, Overall Accuracy and Kappa coefficient are 99.45%, 99.43% and 0.9882, respectively. Further, the effectiveness and feasibility of the proposed method are demonstrated. To verify the advantages of the proposed method on extracting the coastlines, four compared methods (including Canny operator, object-oriented, BP neural network methods, CNN methods) are tested on high-resolution images. Visually, the Canny operator method not only extracts the coastlines with breakpoints, but also extracts the boundaries of many land targets; the other two compared methods can also extract the boundaries of some land targets except for extracting complete coastlines. Two compared methods, which can extract complete coastlines, are evaluated quantitatively. For the objectoriented method, its average R is 71.24%, the average OA is 84.29%, and the average K is 0.7157; For the BP neural network method, its average R is 91.29%, the average OA is 93.04%, and the average K is 0.8707. For the CNN method, the average R, OA and K are 90.73%, 90.60% and 0.9023, respectively. Further, it can be verified that the proposed method can not only extract complete coastlines, but also has higher accuracy.

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Section: Resultsmentioning

confidence: 99%

Automatic Regionalized Coastline Extraction Method Based on High-Resolution Images

Lu,

Wang,

Liang

et al. 2024

IEEE Access

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Coastline extraction and land use change analysis using remote sensing (RS) and geographic information system (GIS) technology – A review of the literature

Yasir

Sheng

Huang

et al. 2020

Reviews on Environmental Health

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Coastlines mapping techniques or the coastline automated analyses have been sought after. In practice, various sorts of seacoasts, for example, biological, silty, arenaceous, artificial, and bedrock coasts, have their own attributes, which force various degrees of intricacy on coastline mapping. As an extraordinary kind of complex artificial coast, aquaculture coast is shaped by the farming of aquatic organisms on silt tidal flats. With the rapid growth of coastal aquaculture in recent years, aquaculture coasts have increased in some developing countries. It has been estimated that aquaculture coasts constitute about 30% of all coastlines in mainland China. In order to identify, monitor, model, and manage the vast expanse of coastal aquaculture, effective methods of extracting aquaculture coastlines from remotely sensed imagery are desired. Secondly, with the rapid economic development in coastal areas, the development of coastal zone resources is also increasing day by day, which benefits the development of island coastal zone. Using oneself has become an important link in the development of marine economy. Due to the limited coastal resources and low environmental carrying capacity, the overexploitation and utilization of coastal resources will lead to a series of problems, such as coastal erosion, coastal migration and accumulation, island area reduction, etc., Both man-made activities and natural factors will lead to coastline changes, which will lead to corresponding changes in coastal ecological environment, thus affecting the coordinated development of coastal economy and the survival of coastal residents. Therefore, efficient, accurate and timely acquisition of coastline information and research on the spatial-temporal changes of coastline are of great significance to the protection of the living environment of coastal residents, the effective development of island and coastal resources, the coordination of sustainable economic development in coastal areas and the mitigation of marine disasters. This paper presents a review of those papers reporting coastline extraction and land use and land cover (LULC) change analysis using remote sensing (RS) and geographic information system (GIS) technology.

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The Coastline Extraction for Fujian Province Based on Long Time Series of Remote Sensing Image

Cited by 2 publications

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Automatic Regionalized Coastline Extraction Method Based on High-Resolution Images

Automatic Regionalized Coastline Extraction Method Based on High-Resolution Images

Coastline extraction and land use change analysis using remote sensing (RS) and geographic information system (GIS) technology – A review of the literature

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