Automatic Coastline Detection Using Image
Enhancement and Segmentation Algorithms

Maraş, Erdem Emin; Caniberk, Mustafa; Maraş, Hadi Hakan

doi:10.15244/pjoes/64160

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…Some methods and technologies played vital roles in providing basic information to make decisions. For instance, remote sensing (RS) and geographical information systems (GIS) have been widely applied to monitor coastal environment change, such as ocean color (Kratzer et al, 2013) and shoreline (Maras et al, 2016). To improve the ability to acquire high-resolution data and high-precision classification, RS and GIS have been evolved in combination with some emerging technologies and methods, such as intelligent remote sensing satellite system (Zhang et al,…”

Section: Methods and Technologymentioning

confidence: 99%

Research on integrated coastal zone management from past to the future: a bibliometric analysis

Jiang,

Yang,

Wang

et al. 2023

Front. Mar. Sci.

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Integrated coastal zone management (ICZM) has been regarded as an effective tool for achieving sustainable development of coastal ecosystems and reducing potential human health risks, but questions remain regarding its research status and future directions. Therefore, a bibliometric analysis was conducted using screened 6151 publications collected from Web of Science Core Collection databases. An exponential increase trend of publications revealed the continuous and strong research interests for ICZM worldwide. The most high-yield country, institution, category, and journal were USA, NOAA, Environmental Sciences, and Ocean & Coastal Management, respectively. Regarding the number of publications, academic influence, and international collaboration, the developed countries occupied the predominant positions. Co-word analysis reveals eight important topics: challenge, service, management and planning, method and technology, development, process, area, and system. Relevant future directions of the ICZM field were proposed based on the Sustainable Development Goals of the United Nations. This review addresses the question of what focal topics in the ICZM field and what should be focused on in future works by objective and quantitative methods. Our results provide valuable insights into the evolution of the ICZM field and the sustainable development of the coastal areas.

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Section: Methods and Technologymentioning

confidence: 99%

Research on integrated coastal zone management from past to the future: a bibliometric analysis

Jiang,

Yang,

Wang

et al. 2023

Front. Mar. Sci.

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“…That makes the model-driven methods hardly transferable to other landscapes or satellites. Finally, they may have a large computation time (Maraş, Canıberk, and Maraş 2016).…”

Section: Model-driven Approachmentioning

confidence: 99%

Coastline extraction from ALOS-2 satellite SAR images

Hurtík

Vajgl

2021

Remote Sensing Letters

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The continuous monitoring of a shore plays an essential role in designing strategies for shore protection against erosion. To avoid the effect of clouds and sunlight, satellite-based imagery with synthetic aperture radar is used to provide the required data. In contrast to standard model-driven methods, we present a deeplearning-based approach to detect coastlines in such data. We split the process into data preprocessing, model training, inference, ensembling, and postprocessing and describe the best techniques for each of the parts. To deal with a small training dataset, we propose a novel multi-sample mosaicing augmentation that helps the deep neural network models to reduce overfitting during training. Our solution has been validated against the real Global Positioning System location of coastlines during a worldwide competition organized by Signate and Japan Aerospace Exploration Agency, where it was runner-up among 109 teams from the whole world.

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“…Chessboard Segmentation Algorithm. According to [9][10][11], there are three strategies that can be implemented to speed up the image registration progress. The first strategy is to decrease the dimension of the key points' descriptors.…”

Section: Csa and Ransacmentioning

confidence: 99%

Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks

Wang

et al. 2018

International Journal of Aerospace Engineering

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In order to satisfy the real-time requirement of spacecraft autonomous navigation using natural landmarks, a novel algorithm called CSA-SURF (chessboard segmentation algorithm and speeded up robust features) is proposed to improve the speed without loss of repeatability performance of image registration progress. It is a combination of chessboard segmentation algorithm and SURF. Here, SURF is used to extract the features from satellite images because of its scale-and rotation-invariant properties and low computational cost. CSA is based on image segmentation technology, aiming to find representative blocks, which will be allocated to different tasks to speed up the image registration progress. To illustrate the advantages of the proposed algorithm, PCA-SURF, which is the combination of principle component analysis and SURF, is also analyzed in this paper for comparison. Furthermore, random sample consensus (RANSAC) algorithm is applied to eliminate the false matches for further accuracy improvement. The simulation results show that the proposed strategy obtains good results, especially in scaling and rotation variation. Besides, CSA-SURF decreased 50% of the time in extraction and 90% of the time in matching without losing the repeatability performance by comparing with SURF algorithm. The proposed method has been demonstrated as an alternative way for image registration of spacecraft autonomous navigation using natural landmarks.

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Automatic Coastline Detection Using Image Enhancement and Segmentation Algorithms

Cited by 5 publications

References 10 publications

Research on integrated coastal zone management from past to the future: a bibliometric analysis

Research on integrated coastal zone management from past to the future: a bibliometric analysis

Coastline extraction from ALOS-2 satellite SAR images

Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks

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