Coastline extraction from high-resolution image based on decision tree and density clustering algorithms
WANG Chang-ying1, WANG Zhi-rui1, CHU Jia-lan2,3, ZHAO Jian-hua2
1. Data Science and Software Engineering College Qingdao University, Qingdao 266071, China;
2. National Marine Environmental Monitoring Center, Dalian 116023, China;
3. Key Laborary of Sea Field Managent Technology, State Oceanic Administration, Dalian 116023, China
Abstract：When extracting coastline from high resolution images,the coastline often extends landward far away due to the influence of the rivers or ditches.In view of this problem,this paper regards coastline as the boundary of seawater (including tidal flat) and land (including rivers and ditches),and then extracts it from images.Firstly,C4.5 decision tree classification method is used to discovery the classification rules for distinguishing the coastal land uses or marine uses; secondly,the discoveried rules are used to classify the coastal land uses or marine uses; after that,postprocessing is conducted based on the classification results by using density clustering method.For a pixel,the principle of postprocessing is to correct the pixel's class according to statistic the number of heterogeneous pixels within a pre-setting radius arround the pixel.If the number of heterogeneous pixels arround exceeds a preset threshold,the current pixel's class will be corrected to the class of the heterogeneous pixels.To validate the proposed method,Resources three satellite image on October 20,2013 near Tianjin is acquired.The experiment result shows that the proposed method can eliminate the influence of rivers and ditches.The average accuracy is better than 2 pixels,which meets the requirements of the standard of linear information error in the technical regulation of marine remote sensing,except for the region,in which some individual objects are more complex.
WANG Chang-ying,WANG Zhi-rui,CHU Jia-lan et al. Coastline extraction from high-resolution image based on decision tree and density clustering algorithms[J]. Marine Environmental Science, 2017, 36(4): 590-595.
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