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Application of fractal dimension-change point method to the extraction of remote sensing alteration anomaly |
| HAN Haihui1, 2, WANG Yilin1, YANG Min1, REN Guangli1, YANG Junlu1, LI Jianqiang1, GAO Ting1 |
1. Xi’an Center of China Geological Survey, Xi’an 710054, China;
2. School of Geological and Surveying, Chang’an University, Xi’an 710054, China |
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Abstract At present, the extracting method for remote sensing alteration anomalies from principal component image relies mainly on the data’s normal distribution, without considering the nonlinear characteristics of geological anomaly. To tackle this problem, the authors have proposed the fractal dimension-change point method(FDCPM)in this paper. By calculating the self-similarity and mutability of alteration anomalies with fractal dimension-change point model, the critical threshold of an alteration anomaly was acquired quantitatively. The realization theory and access mechanism of the method were elaborated by an experiment with ASTER data in Fangshankou,Beishan,and the results of the proposed method and traditional method (de-interfered anomalous principal component thresholding technique,DIAPCTT) were compared with each other. The results show that the FDCPM has a relatively high extracting precision than the DIAPCTT for three alteration minerals in the experiment. In this experiment, the accuracy of three alteration minerals could reach over 83%. Moreover, the distribution of remote sensing alteration anomalies agrees well with a large amount of evidence from the geochemical anomaly and the heavy sand anomaly. What’s more, the known polymetallic ore spots and mineralized spots fall in the zone of remote sensing alteration anomaly or at its edge. All the results mentioned above show that the FDCPM is one of the effective distinguishing methods for the geological background and the remote sensing alteration anomaly in the future.
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| Keywords
SPOT6
rule
building extraction
KNN
SVM
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Issue Date: 15 August 2017
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2017,
Vol. 29
