Automated Coastline Extraction Using the Very High Resolution WorldView (WV) Satellite Imagery and Developed Coastline Extraction Tool (CET)

Domazetović, Fran; Šiljeg, Ante; Marić, Ivan; Faričić, Josip; Vassilakis, Emmanuel; Panđa, Lovre

doi:10.3390/app11209482

Cited by 14 publications

(8 citation statements)

References 61 publications

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“…Total Number of Pixels   (10) The OA provides a holistic measure of the correct classification across all classes and is calculated as the ratio of the sum of true positives for all classes to the total number of pixels.…”

Section: Tp Oamentioning

confidence: 99%

“…Currently, various countries generally define the instantaneous water level as the coastline. Within the realm of remote sensing interpretation, it is commonly believed that the coastline is the boundary line between the land and the ocean in the remote sensing image, It is an important basis for delineating the extent of the coastline zone [9,10]. A growing number of researchers are proposing numerous related methods to extract coastlines.…”

Section: Introductionmentioning

confidence: 99%

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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: Tp Oamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automatic Regionalized Coastline Extraction Method Based on High-Resolution Images

Lu,

Wang,

Liang

et al. 2024

IEEE Access

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“…Satellite images, especially those from the last century, have low resolution up to 80 m, while recent ones have much better, even high, resolution. Moreover, recent investigations [46] obtained the resolution of 0.5 m from automated extraction of coastlines (WorldView satellite). According to the listed data, remote sensing techniques have proven to be time-saving and useful methods for various beach surveys.…”

Section: Investigations Of Beach Morphologymentioning

confidence: 99%

Assessment of Remote Sensing Techniques Applicability for Beach Morphology Mapping: A Case Study of Hvar Island, Central Adriatic, Croatia

Mićunović

Faivre

Gašparović

2021

JMSE

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This study investigates the quality and accuracy of remote sensing data in beach surveys based on three different data sources covering a 10-year period (2011–2021). Orthophotos from State Geodetic Administration Geoportal and satellite imagery from Google Earth were compared with orthophotos generated from UAV using ArcGIS Pro and Drone2Map. The beach area and length of 20 beaches on the island of Hvar were measured using each data source from different years. The average deviation for beach area (−2.3 to 5.6%) and length (−1 to 2.7%) was determined (without outliers). This study confirms that linear feature measurement is more accurate than polygon-based measurement. Hence, smaller beach areas were associated with higher errors. Furthermore, it was observed that morphological complexity of the beach may also affect the measurement accuracy. This work showed that different remote sensing sources could be used for relatively accurate beach surveys, as there is no statistically significant difference between the calculated errors. However, special care should always be addressed to the definition of errors.

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“…In the building industry, IRT has also been used for object detection on a building [12] and for archaeological purposes [13]. IRT is also widely used in other industries, such as energetics [14], agriculture [15], security [16], zoology [17], seed [18] and plant [19] monitoring, and environmental protection [20]. There is also extensive use of IRT in the medical industry.…”

Section: Introductionmentioning

confidence: 99%

Photogrammetric Co-Processing of Thermal Infrared Images and RGB Images

Dlesk

Vach²,

Pavelka³

2022

Sensors

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In some applications of thermography, spatial orientation of the thermal infrared information can be desirable. By the photogrammetric processing of thermal infrared (TIR) images, it is possible to create 2D and 3D results augmented by thermal infrared information. On the augmented 2D and 3D results, it is possible to locate thermal occurrences in the coordinate system and to determine their scale, length, area or volume. However, photogrammetric processing of TIR images is difficult due to negative factors which are caused by the natural character of TIR images. Among the negative factors are the lower resolution of TIR images compared to RGB images and lack of visible features on the TIR images. To eliminate these negative factors, two methods of photogrammetric co-processing of TIR and RGB images were designed. Both methods require a fixed system of TIR and RGB cameras and for each TIR image a corresponding RGB image must be captured. One of the methods was termed sharpening and the result of this method is mainly an augmented orthophoto, and an augmented texture of the 3D model. The second method was termed reprojection and the result of this method is a point cloud augmented by thermal infrared information. The details of the designed methods, as well as the experiments related to the methods, are presented in this article.

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Automated Coastline Extraction Using the Very High Resolution WorldView (WV) Satellite Imagery and Developed Coastline Extraction Tool (CET)

Cited by 14 publications

References 61 publications

Automatic Regionalized Coastline Extraction Method Based on High-Resolution Images

Automatic Regionalized Coastline Extraction Method Based on High-Resolution Images

Assessment of Remote Sensing Techniques Applicability for Beach Morphology Mapping: A Case Study of Hvar Island, Central Adriatic, Croatia

Photogrammetric Co-Processing of Thermal Infrared Images and RGB Images

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