Abstract
Climate change and natural disasters are especially dangerous to coastal landscapes. Natural and man-made hazards like erosion sedimentation, rising sea levels, and tidal flooding are wreaking havoc on coastal areas. The mapping and detection of coastlines are critical for safe navigation, environmental conservation, and long-term coastal development. The model is composed of a method for extracting coastline from sentinel-2-l2a satellite images obtained from the sentinelhub website. The model uses the Gaussian blur module to reduce noise. Using k-means clustering, the image is then segmented as land and water. An edge detection algorithm identifies the boundary between land and water. One of many edge detection algorithms, Canny edge detector, applies a multi-level algorithm to detect edges in images. Percentage change is calculated by comparing window to window of edge detected images.
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References
Panwar P, Gopal G, Kumar R (2016) Image Segmentation using K-means clustering and thresholding. Image 3(05):1787–1793
Yasir M, Hui S, Binghu H, Rahman SU (2020) Coastline extraction and land use change analysis using remote sensing (RS) and geographic information system (GIS) technology—a review of the literature. Rev Environ Health 35(4):453–460
Modava M, Akbarizadeh G (2017) Coastline extraction from SAR images using spatial fuzzy clustering and the active contour method. Int J Remote Sens 38(2):355–370
Saeed AM, Fatima AM (2016) Coastline extraction using satellite imagery and image processing techniques. Red 600:720
Bouchahma M, Yan W, Ouessar M (2012) Island coastline change detection based on image processing and remote sensing. Comput Inf Sci 5(3):27
Zhang T, Yang X, Hu S, Su F (2003) Extraction of coastline in aquaculture coast from multispectral remote sensing images: object-based region growing integrating edge detection. Remote Sens 5(9):4470–4487
Paravolidakis V, Ragia L, Moirogiorgou K, Zervakis ME (2018) Automatic coastline extraction using edge detection and optimization procedures. Geosciences 8(11):407
Karantzalos KG, Argialas D, Georgopoulos A (2002) Towards automatic detection of coastlines from satellite imagery. In: 2002 Proceedings of 14th ınternational conference on digital signal processing, DSP 2002 (Cat. No. 02TH8628), vol 2. IEEE, pp 897–900
Dellepiane S, De Laurentiis R, Giordano F (2004) Coastline extraction from SAR images and a method for the evaluation of the coastline precision. Pattern Recogn Lett 25(13):1461–1470
Pham VH, Lee BR (2015) An image segmentation approach for fruit defect detection using k-means clustering and graph-based algorithm. Viet J Comput Sci 21:25–33
Biswas R, Sil J (2012) An improved canny edge detection algorithm based on type-2 fuzzy sets. Proc Technol 4:820–824
Deng C-X, Wang G-B, Yang X-R (2013) Image edge detection algorithm based on improved canny operator. In: 2013 International conference on wavelet analysis and pattern recognition. IEEE, pp 168–172
Ebby DP, Jeena Jacob I (2021) Rain Streaks Removal in digital images by dictionary based sparsity process with MCA estimation. J Innov Image Process 3(3):174–189
Karuppusamy P (2021) Building detection using two-layered novel convolutional neural networks. J Soft Comput Paradigm (JSCP) 3(01):29–37
Shakya S (2021) Unmanned aerial vehicle with thermal imaging for automating water status in Vineyard. J Electr Eng Autom 3(2):79–91
James Deva Koresh H, Chacko S (2020) Hybrid speckle reduction filter for corneal OCT images. In: International conference on ımage processing and capsule networks. Springer, Cham, pp 87–99
Sathesh A, Eisa Babikir Adam E (2021) Hybrid parallel ımage processing algorithm for binary ımages with ımage thinning technique. J Artif Intell 3(03):243–258
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Sasank Dattu, T., Bhargav Reddy, D., Charan Teja, M., Sailaja, K.L., Ramesh Kumar, P. (2023). Coastline Change Detection Using K-means Clustering and Canny Edge Detector on Satellite Images. In: Smys, S., Lafata, P., Palanisamy, R., Kamel, K.A. (eds) Computer Networks and Inventive Communication Technologies. Lecture Notes on Data Engineering and Communications Technologies, vol 141. Springer, Singapore. https://doi.org/10.1007/978-981-19-3035-5_47
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DOI: https://doi.org/10.1007/978-981-19-3035-5_47
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