Remote Sensing Alteration and Structure Analysis Based on Fractal Theory: A Case Study of Duobaoshan Area of Heilongjiang Province

doi:10.19657/j.geoscience.1000-8527.2022.019

Abstract

Abstract:

Mineralization-alteration information extraction and structural interpretation are of great significance for metallogenic prediction. Fractal theory can be used to reveal the fine structure of hidden information in complex terrain features, in the field of remote sensing geology, and the theories and new methods for remote sensing mineralization/alteration information extraction and quantitative analysis of geological/structural interpretations. This study mainly used Landsat-8 OLI images and related geological data to study the alteration and structural fractal characteristics of the Duobaoshan area in Heilongjiang Province, based on analysis theory. The interference removal+band ratio+principal component analysis+fractal threshold segmentation method was used to extract the alteration anomaly information. Dimension contour map of linear structure and alteration was obtained by box dimension method of fractal theory, and its spatial distribution and fractal characteristics were analyzed. The structural and alteration information were superimposed to compare with the high value area of structural and alteration fractal dimension, and with the metallogenic geological background. The results show that the high-value area of remote sensing alteration fractal dimension coincides with the alteration data-intensive area, and the structural fractal results are consistent with the spatial distribution of ore-forming structures. The superimposed information combines the advantages of the two, i.e., eliminates interference, narrows the exploration scope, and more effectively highlights the favorable ore-forming sites. Here, the fractal feature analysis method of remote sensing alteration anomaly and structural information superposition is first applied. This method can increase the utilization and accuracy of remote sensing information, and is also more consistent with the actual metallogenic geological background and exploration results. It can be used as a new theory and method for comprehensive prospecting prediction of remote sensing data, and provides theoretical basis and prospecting direction for future exploration work in the area.

Key words: fractal theory, remote sensing alteration, structural analysis, information extraction

CLC Number:

P627
P612

ZHAO Zhonghai, CHEN Jun, QIAO Kai, CUI Xiaomeng, LIANG Shanshan, LI Chenglu. Remote Sensing Alteration and Structure Analysis Based on Fractal Theory: A Case Study of Duobaoshan Area of Heilongjiang Province[J]. Geoscience, 2023, 37(01): 153-163.

Figures/Tables 12

Fig.1 Tectonic map (a) and geological sketch map (b) of the study area

Fig.2 Data processing flow chart

Table 1 Statistics of principal component analysis

特征向量	Band6/ Band7	Band6/ Band2	Band5/ Band4	Band4/ Band2
PC1	0.1866	0.8967	0.2707	0.2965
PC2	0.5703	-0.4283	0.3823	0.5875
PC3	-0.3402	0.0107	-0.5971	0.7265
PC4	-0.7241	-0.1113	0.6513	0.1978

Fig.3 lgN(r)-lgr for grey frequency

Fig.4 Iron staining alteration anomaly map in the study area based on fractal statistics (a), mirror Fe mineralization (b), and ferritization (c)

Fig.5 Contour map for fractal dimension values of FCA in the study area

Fig.6 Remote sensing fault interpretation map (a), structural azimuth statistical rose chart (b) and structural interpretive markers (c) of the study area

Fig.7 lgN(r)-lgr for fractal statistical results

Table 2 Comparison of fractal characteristics of the study area with other areas

区域	分维值	资料来源
黑龙江多宝山地区构造	1.7538	本次计算
广西大瑶山西北地区构造	1.6897	蒋超等^[17]
中国四川盆地中部断裂带	1.5300	Fan^[51]
中国上杭—云霄断裂带	1.3600	Lyu^[52]
西藏阿里住浪矿区线性构造	1.8412	张渊等^[53]
湘南九嶷山地区断裂	1.1155	雷天赐等^[18]
中国青藏高原地区断裂	1.2373	朱晓华^[54]
中国大陆断裂	1.2366	朱晓华^[54]
华南地区线性构造	1.3500	孔凡臣等^[55]
日本岛弧线性构造	<1.6000	Hirata^[56]

Fig.8 Contour map of the fault fractal dimension values in the study area

Fig.9 Schematic diagrams of fractal dimension scale division steps

Fig.10 Contour map for fractal dimension values of integrating alteration and structural information

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