Abstract and Applied Analysis
Volume 2013 (2013), Article ID 693194, 6 pages
http://dx.doi.org/10.1155/2013/693194
Research Article

A Study on Coastline Extraction and Its Trend Based on Remote Sensing Image Data Mining

Yun Zhang,1,2,3 Xueming Li,1 Jianli Zhang,2,3 and Derui Song2,3

1Liaoning Normal University, Dalian 116029, China
2National Marine Environmental Monitoring Center, Dalian 116023, China
3Key Laboratory of Sea Areas Management Technology, SOA, Dalian 116023, China

Received 31 January 2013; Accepted 21 March 2013

Academic Editor: Jianhong (Cecilia) Xia

Copyright © 2013 Yun Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In this paper, data mining theory is applied to carry out the field of the pretreatment of remote sensing images. These results show that it is an effective method for carrying out the pretreatment of low-precision remote sensing images by multisource image matching algorithm with SIFT operator, geometric correction on satellite images at scarce control points, and other techniques; the result of the coastline extracted by the edge detection method based on a chromatic aberration Canny operator has a height coincident with the actual measured result; we found that the coastline length of China is predicted to increase in the future by using the grey prediction method, with the total length reaching up to 19,471,983 m by 2015.