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Remote Sensing for Natural Resources    2023, Vol. 35 Issue (4) : 61-70     DOI: 10.6046/zrzyyg.2022250
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Application of GF-5 hyperspectral data in uranium deposit exploration
ZHANG Yuantao1,2(), PAN Wei1, YU Changfa1
1. National Key Laboratory of Remote Sensing Information and Image Analysis Technology, Beijing Research Institute of Uranium Geology, Beijing 100029, China
2. No.280 Institute of Nuclear Industry, Deyang 618300, China
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Abstract  

However, since GF-5 launch in 2018, few studies regarding the application of GF-5 AHSI data for uranium deposit exploration have been reported. In this study, with the Weijing area of Inner Mongolia as the study area, the spectral hourglass technology was applied to extract alteration anomalies of goethite and low-, medium-, and high-aluminum sericite from corresponding GF-5 AHSI data. Then, the principal component analysis (PCA) and the LINE module in PCI Geomatica software were employed for the automatic extraction of linear structures in the study area, with a linear structure density map created. Finally, a uranium mineralization potential map of the study area was generated by integrating all proof layers based on the ArcGIS software. The results indicate that the extraction of alteration information and linear structures, and the integration of multiple proof layers are feasible, and the obtained uranium mineralization potential map exhibits high reliability. One uranium deposit prediction zone was identified based on the study results and geological data. The study results will guide the subsequent uranium deposit exploration in the study area while providing a reference for the geological application of GF-5 AHSI data.
Keywords GF-5      hyperspectrum      alteration information      linear structure      weighted overlay      uranium deposit     
ZTFLH:  TP79  
Issue Date: 21 December 2023
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Yuantao ZHANG
Wei PAN
Changfa YU
Cite this article:   
Yuantao ZHANG,Wei PAN,Changfa YU. Application of GF-5 hyperspectral data in uranium deposit exploration[J]. Remote Sensing for Natural Resources, 2023, 35(4): 61-70.
URL:  
https://www.gtzyyg.com/EN/10.6046/zrzyyg.2022250     OR     https://www.gtzyyg.com/EN/Y2023/V35/I4/61
Fig.1  Sketch map of geology in research area (modified after the 2015 data from No.208 Geologic Party, CNNC)
波段 光谱范围/nm 光谱分
辨率/nm		 空间分
辨率/m		 波段数
可见光—近红外(VNIR) 390.324~1 029.18 5 30 150
短波红外(SWIR) 1 004.77~2 513.25 10 180
Tab.1  Main parameters of GF-5 AHSI image
Fig.2  Band 276 original image and fringe-restored image
Fig.3  Flow chart of research
Fig.4  Endmember spectrum from AHSI image and standard spectrum from USGS spectral library
参数 含义 单位 描述 采用值
RADI 滤波半径 像素 指定Canny边缘检测算子中用于梯度计算的高斯滤波器的半径大小 12
GTHR 边缘梯度阈值 无 边缘检测过程中,作为边缘的梯度最小值,该值越大,图像中边缘越少 50
LTHR 曲线长度阈值 像素 被视为线性构造的最小长度 25
FTHR 线拟合阈值 像素 线段拟合形成线性构造时允许的最大误差 3
ATHR 角度差阈值 像素 定义要连接的2条多段线之间不能超过的角度。当2线段之间夹角大于该值时,则不进行连接操作 20
DTHR 连接距离阈值 像素 指定2条线段之间进行连接处理的最大间距,当超过该值时,则不进行连接 1
Tab.2  Different parameters of the LINE module and their actual values
Fig.5  Distribution of alteration minerals
Fig.6  Distribution of linear structures
Fig.7  Rrose diagram of linear structures
图层 权重 数值 类别得分
线性构造密度 0.2 [0.000,0.723) 1
[0.723,0.815) 2
[0.815,0.906) 3
[0.906,1.000] 4
中铝绢云母蚀变 0.2 [0.000,0.395) 1
[0.395,0.419) 2
[0.419,0.444) 3
[0.444,1.000] 4
针铁矿蚀变异常 0.2 [0.000,0.728) 1
[0.728,0.738) 2
[0.738,0.748) 3
[0.748,1.000] 4
高铝绢云母蚀变 0.2 [0.000,0.733) 1
[0.733,0.772) 2
[0.772,0.811) 3
[0.811,1.000] 4
低铝绢云母蚀变 0.2 [0.000,0.513) 1
[0.513,0.545) 2
[0.545,0.577) 3
[0.577,1.000] 4
Tab.3  Weights of evidential layers and their respective classification
Fig.8  Classification results of evidential layers and mineral potential map of uranium
Fig.9  Field verification photos in Weijing area
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