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WANG Changying,ZHANG Jie,SONG Pingjian. 2014. An intelligent coastline interpretation of several types of seacoasts from TM/ETM+ images based on rules. Acta Oceanologica Sinica, 33(7):89-96
An intelligent coastline interpretation of several types of seacoasts from TM/ETM+ images based on rules
基于规则的多种类型海岸线TM/ETM+影像智能检测方法
Received:June 18, 2012  Revised:September 27, 2013
DOI:10.1007/s13131-014-0482-x
Key words:coastline interpretation  TM/ETM+  data mining  rule
中文关键词:  海岸线解译,TM/ETM+,数据挖掘,规则
基金项目:The Science and Technology Development Plan Projects of Shandong Province of China under contract No. 2011YD15005;the National Natural Science Foundation of China under contact Nos 91130035 and 40906094.
Author NameAffiliationE-mail
WANG Changying College of Information Engineering, Qingdao University, Qingdao 266071, China wcing80@126.com 
ZHANG Jie Key Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China  
SONG Pingjian Key Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China  
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Abstract:
      A coastline is defined as the average spring tide line. Different types of seacoast, such as sandy, silty, and biological coast, have different indicators of interpretation. It is very difficult to develop a universal method for interpreting all shorelines. Therefore, the sandy, the silty, and the biological coast are regarded as research objects, and with data mining technology, found the rules of interpretation of those three types of coastlines. Then, an intelligent coastline interpretation method based on rules was proposed. Firstly, the rules for extracting the waterline in Landsat TM/ETM+ (Thematic Mapper/Enhanced Thematic Mapper Plus) imagery were discovered. Then, through analyzing the features of sandy, silty and biological coast, the indicators of interpreting different types of shoreline were determined. According to the indicators, the waterline could be corrected to the real coastline. In order to verify the validity of the proposed algorithms, three Landsat TM/ETM imageries were selected for case studies. The experimental results showed that the proposed methods could interpret the coastlines of sandy, silty, and biological coasts with high precision and without human intervention, which exceeded three pixels.
中文摘要:
      我国海岸线定义为平均大潮高潮线所处的位置。不同的海岸类型,其海岸线解译标志也不同,那么海岸线位置的确定方法也不同,因此,很难找到一种适用于所有海岸类型的海岸线提取方法。本文以砂质、淤泥质和生物海岸为研究对象,利用数据挖掘技术,找到各种海岸类型的海岸线解译规则,进而提出一种基于知识的海岸线智能提取方法。首先,采用数据挖掘技术中的关联规则算法,挖掘出Landsat TM/ETM+遥感影像水边线检测规则,实现基于规则的水边线检测;然后,针对砂质海岸、淤泥质海岸和生物海岸等海岸类型的特征,分析不同海岸类型的岸线解译标志,将提取出的水边线修正为真正的海岸线。以三景Landsat TM/ETM 影像为数据源,对提出的岸线提取方法进行精度验证。结果表明,本文方法提取出的岸线与真正的岸线非常接近,精度优于3个像元。
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