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

Yun Zhang | Zendy; Xueming Li | Zendy; Jianli Zhang | Zendy; Derui Song | Zendy

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

Author(s) -

Yun Zhang,

Xueming Li,

Jianli Zhang,

Derui Song

Publication year - 2013

Publication title -

abstract and applied analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.228

H-Index - 56

eISSN - 1687-0409

pISSN - 1085-3375

DOI - 10.1155/2013/693194

Subject(s) - remote sensing , scale invariant feature transform , matching (statistics) , operator (biology) , mathematics , satellite , field (mathematics) , canny edge detector , image (mathematics) , artificial intelligence , enhanced data rates for gsm evolution , computer vision , edge detection , computer science , image processing , geography , statistics , biochemistry , chemistry , repressor , aerospace engineering , transcription factor , pure mathematics , engineering , gene

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

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