A Study on Coastline Extraction and Its Trend Based on Remote Sensing Image Data Mining
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, geo...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2013/693194 |
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| Summary: | 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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| ISSN: | 1085-3375 1687-0409 |