山西省中条山中北段遥感示矿信息提取与区块优选

刘知; 李彦星; 杨波; 刘小松; 张航

doi:10.19509/j.cnki.dzkq.tb20240617

山西省中条山中北段遥感示矿信息提取与区块优选

doi: 10.19509/j.cnki.dzkq.tb20240617

刘知^{1, 2, 3,},
李彦星^{1, 2, 3, 4, ,},
杨波¹,
刘小松^{1, 2, 3},
张航¹

1.
山西省煤炭地质物探测绘院有限公司，山西晋中 030600
2.
自然资源部矿业城市自然资源调查监测与保护重点实验室，山西晋中 030600
3.
地质灾害监测预警与防治山西省重点实验室，山西晋中 030600
4.
中国地质大学（北京）地球物理与信息技术学院，北京 100083

基金项目: 山西省地质勘查基金项目（2018-49；2019-27）

详细信息

作者简介:
刘知：E-mail：2454667759@qq.com

通讯作者:
E-mail：66369280@qq.com

中图分类号: P627
计量
- 文章访问数: 80
- PDF下载量: 23
- 被引次数: 0
出版历程
- 收稿日期: 2024-10-21
- 录用日期: 2024-12-23
- 修回日期: 2024-12-18
- 网络出版日期: 2025-12-18

Extraction of remote sensing ore-indicating information and block optimization in middle-northern segment of Zhongtiao Mountain, Shanxi Province

LIU Zhi^{1, 2, 3
,},
LI Yanxing^{1, 2, 3, 4
, ,},
YANG Bo¹,
LIU Xiaosong^{1, 2, 3},
ZHANG Hang¹

1.
Coal Geological Geophysical Exploration Surveying and Mapping Institute of Shanxi Province, Jinzhong Shanxi 030600, China
2.
Key Laboratory of Monitoring and Protection of Natural Resources in Mining Cities, Ministry of Natural Resources, Jinzhong Shanxi 030600, China
3.
Shanxi Key Laboratory of Geological Disaster Monitoring, Early Warning and Prevention, Jinzhong Shanxi 030600, China
4.
School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing 100083, China

More Information

Author Bio:
E-mail：2454667759@qq.com

Corresponding author: E-mail：66369280@qq.com

摘要

摘要:
区块优选是新一轮找矿突破战略行动一项重要工作，是响应自然资源部进一步提高找矿工作效率、发展新质生产力和提高矿产资源保障能力的重要举措。山西省中条山作为全国金、铜、铁等重要战略资源矿集区之一，矿产资源丰富，目前区内尚无大比例尺基于遥感卫星影像地质解译及找矿应用研究。以山西省中条山中北段为研究区，通过对Spot-6遥感影像进行控矿构造要素、控矿环形要素的人机交互解译，宏观上总结区域构造分布特征，基于Aster数据应用主成分分析法（PCA）初步提取蚀变矿化异常信息，以ASD光谱仪采集的野外典型岩矿光谱曲线作为训练样本，采用光谱角填图法（SAM）反演含矿地层分布，并利用结果用于筛选PCA提取信息，获取铁染、羟基、碳酸盐三大类矿化蚀变，分析蚀变异常与控矿要素（区域构造、赋矿地层、岩体分布等）的空间相关性。结果表明：①研究区线环构造发育，新增解译断裂84条，环形构造136条，解译结果可辅助修正前人地质调查成果的不足；②基于PCA法和岩矿光谱反演得到的矿化蚀变信息可有效指示矿化异常的位置，且研究区构造控矿作用明显；③结合野外实地验证和已有区域地质资料成果叠加分析得到综合异常等密度图，圈定出三大成矿优选区。研究成果为矿产资源潜力评价、找矿预测和深部找矿战略行动提供依据和指导。
- 遥感技术 /
- 蚀变信息 /
- 线环构造 /
- 找矿预测 /
- 中条山
Abstract: Objective
Ore block optimization of is an important task in the new round of strategic prospecting breakthrough actions, and a key initiative to respond to the Ministry of Natural Resources in further improving the efficiency of prospecting, developing new-quality productive forces, and enhancing the support capacity of mineral resources. As one of China's key national strategic resource concentration areas for gold, copper, iron, and other critical minerals, the Zhongtiao Mountain in Shanxi Province is abundant in mineral resources. However, to date, there is relatively limited research on the large-scale remote sensing geological interpretation and prospecting applications based on remote sensing satellite images in this region, which is of great significance for prospecting prediction.
Methods
The middle-northern segment of the Zhongtiao Mountain in Shanxi Province was selected as the study area. Based on human-computer interactive interpretation of ore-controlling structural and ore-controlling ring features from Spot-6 remote sensing images, the regional structural distribution of the study area was summarized from a macro perspective. Principal component analysis (PCA) was employed to preliminarily extract mineralization alteration anomaly information via Aster data. Additionally, with field spectral curves of typical rocks and minerals collected by an ASD spectrometer as training samples, the spectral angle mapping (SAM) method was applied to extract the distribution of ore-bearing strata. The distribution results were then used to screen the PCA extraction results to identify three major types of mineralization alterations, including iron staining, hydroxyl, and carbonate. The spatial correlation between alteration anomalies and ore-controlling factors (such as regional structures, ore-bearing strata, and rock mass distribution) was further analyzed.
Results
The results indicated that: (1) The linear and ring structures were well-developed in the study area, with 84 newly interpreted faults and 136 ring structures, which helped refine and supplement the shortcomings of previous geological survey findings. (2) The mineralization and alteration information obtained by PCA and rock-ore spectral inversion could effectively indicate mineralization anomalies, highlighting the important role of regional structures in ore formation. (3) A comprehensive anomaly isodensity map was obtained through combined analysis of field verification and existing regional geological data to delineate three optimal mineralization areas.
Conclusion
The research findings provide a basis and guidance for subsequent evaluation of mineral resource potential, prospecting prediction, and strategic actions of deep prospecting. The findings also promote the application of remote sensing-based geological prospecting in the Zhongtiao Mountain, and provide insights into future remote sensing-based geological prospecting efforts in other regions of Shanxi Province.
- remote sensing technology /
- alteration information /
- linear and ring structure /
- mineral prospecting prediction /
- Zhongtiao Mountain

HTML全文

图 1 研究区地质简图(a)和大地构造位置(b)

1. 第四系；2. 新近系；3. 古近系；4. 二叠系；5. 石炭系；6. 奥陶系；7. 寒武系；8. 长城系雄耳群；9. 长城系汝阳群；10. 长城系担山石群；11. 上中条亚群；12. 下中条亚群；13. 绛县群铜矿峪亚群；14. 绛县群横岭关亚群；15. 宋家山群；16. 燕山期；17. 晋宁期；18. 中条期；19. 绛县期；20. 宋家山期；21. 涑水期；22. 角砾岩；23. 断裂；24. 研究区范围；25. 三级构造单元；26. 四级构造单元；27. 隆起；28. 坳陷；29. 已知或推断的大断裂及编号；30. 构造单元分级编号；31. 地名；⑦. 涑渭大断裂；⑧. 中条北麓大断裂；⑨. 中条南东侧大断裂；⑩. 太行南麓大断裂；Ⅲ₆. 汾渭断陷；Ⅳ₂. 稷山台拱；Ⅳ₃. 涑渭断凹；Ⅳ₄. 黄河断凹；Ⅱ₃. 山西中台隆；Ⅱ₄. 嵩条断褶区；Ⅲ₁₀. 中黄陷断褶束；Ⅳ₈. 中条台穹；Ⅳ₉. 黄金山凹断褶束；Ⅳ₁₀. 洛阳台凹；Ⅱ₆. 秦岭轴缘坳陷；Ⅲ₁₆. 华露台拱

Figure 1. Simplified geological map (a) and tectonic location (b) of the study area

下载: 全尺寸图片幻灯片

图 2 不同融合方法结果对比图（以横岭关地区为例）

a. Brovey融合方法；b. PC融合方法；c. Gram-Schmidt融合方法；d. NNDiffuse融合方法

Figure 2. Comparison of results using different fusion methods

下载: 全尺寸图片幻灯片

图 3 典型岩石波谱图（a1～j1）及连续统（包络线）去除图（a2～j2）

a1，a2. 安山岩；b1，b2. 变辉长岩；c1，c2. 片岩；d1，d2. 大理岩；e1，e2. 白云岩；f1，f2. 片麻岩；g1，g2. 千枚岩；h1，h2. 花岗岩；i1，i2. 板岩；j1，j2. 石英岩

Figure 3. Typical rock spectra (a1-j1) and continuum removal spectra (a2-j2)

下载: 全尺寸图片幻灯片

图 4 蚀变矿物波谱与Aster波段对应关系

a. Al-OH；b. Mg-OH；c. Fe离子；d. CO₃²⁻。彩色柱状为Aster数据的各波段宽度

Figure 4. Correation between spectra of alteration minerals and Aster bands

下载: 全尺寸图片幻灯片

图 5 研究区线性构造遥感解译标志

a. 不同地貌单元；b. 断层三角面；c. 色调差异明显；d. 河流汇聚和局部直线；e. 同步错动水系；f. 直角河和同向转弯河系；g. 山脊（规律）错动；h. 正负地形突变；i. 断裂切割地层。淡绿色线为山脊走向或者河流走向；其余线型均为辅助线，起区分和指示作用，无实际含义；下同

Figure 5. Remote sensing interpretation signs for linear structures in the study area

下载: 全尺寸图片幻灯片

图 6 研究区主要断裂构造解译图(a)和环形构造解译图(b)

Figure 6. Interpretation maps of main fault structures (a) and ring structures (b) in the study area

下载: 全尺寸图片幻灯片

图 7 研究区环形构造遥感解译标志

a. 放射状环要素；b. 线环相切型构造；c. 地貌突变型环要素；d. 线环相交型构造；e. 双环相交型构造；f. 火山口型环要素；g. 火山锥型环要素；h. 色调差异明显的双环套合环要素

Figure 7. Remote sensing interpretation signs for ring structures in the study area

下载: 全尺寸图片幻灯片

图 8 基于光谱反演的蚀变岩性反演图

Figure 8. Alteration lithology inversion map based on inversion spectral data

下载: 全尺寸图片幻灯片

图 9 遥感异常分布与统计图

Figure 9. Remote sensing anomaly distribution and statistics map

下载: 全尺寸图片幻灯片

图 10 蚀变异常相关性分析

a. 蚀变异常面积与重叠区相应异常面积百分比雷达概率图；b. 蚀变异常面积与不同构造运动期岩体面积百分比玫瑰概率图；c. 蚀变异常面积与不同含矿地层面积百分比玫瑰概率图

Figure 10. Correlation analysis of alteration anomalies

下载: 全尺寸图片幻灯片

图 11 研究区构造野外查证照片

a，b. 地层错动；c. 断裂擦痕；d，e. 断层破碎带填充；f. 断层破碎带

Figure 11. Photos of field structural verification in the study area

下载: 全尺寸图片幻灯片

图 12 矿化蚀变野外验证结果

a. 褐铁矿化与绢英岩化；b. 黄铁矿化；c. 褐铁矿化与孔雀石化；d. 绿泥石化；e. 绿帘石化与碳酸盐化；f. 绿帘石化与硅化；g. 孔雀石化；h. 石英岩化与白云岩化；i. 碳酸盐化

Figure 12. Field verification results of mineralization and alteration

下载: 全尺寸图片幻灯片

图 13 综合异常等密度图

Figure 13. Comprehensive anomaly isodensity map

下载: 全尺寸图片幻灯片

表 1 研究区遥感数据基本情况

Table 1. Basic information of remote sensing data in the study area

数据种类	成像日期	面积/km²	空间分辨率
Spot-6数据	2015/12/16	3150	全色分辨率为1.5 m 多光谱分辨率为6 m
	2014/12/12
	2013/12/31
Aster数据	2005/03/23	3150	Band1～3分辨率为15 m Band4～9分辨率为30 m Band10～14分辨率为90 m
	2005/03/30
	2006/03/24

下载: 导出CSV

表 2 不同融合方法定量评价

Table 2. Quantitative evaluation of different fusion methods

融合方法	均值	标准差	信息熵	平均梯度
NNDiffuse	0.60863	0.04475	5.24934	0.02162
Gram-Schmidt	0.50261	0.00749	2.85081	0.00492
PC	0.51384	0.00478	2.26483	0.00285
Brovey	0.50100	0.00027	0.00122	0.00019
注：参数值为各波段参数的平均值

下载: 导出CSV

表 3 各类干扰地物去除方法

Table 3. Methods for removing various types of disturbing features

干扰因素	去除方法
植被	（Band3−Band2）/（Band3+Band2）或Band3/Band2
云	（b1 ge 云的最低亮度值）×0+（b1 lt 云的最低亮度值）×1
云	或者Band1高端切割
盐碱地	Band9/Band1或者Band1高端切割
水体	Band9/Band1或者（Band1−Band4）/（Band1+Band4）
阴影	（b1 ge 阴影中的高值）×1+（b1 lt 阴影中的低值）×0
阴影	或者Band9/Band1
冰雪	Band2或Band3高端切割
注：b1=Band6/Band1

下载: 导出CSV

表 4 4类蚀变的主成分变换特征向量矩阵

Table 4. PCA eigenvector matrices of four alteration types

蚀变类型	波段组合	主成分
蚀变类型	波段组合	PC1	PC2	PC3	PC4
铁离子基团（Fe³⁺&Fe²⁺）	Band1	0.265456	0.441699	−0.434136	−0.751158
	Band2	0.342133	0.514535	−0.354134	0.654396
	Band3	0.515148	0.328932	0.741541	−0.048923
	Band4	0.747815	−0.631286	−0.214641	0.005133
Al-OH基团	Band1	0.289626	0.572485	0.745240	−0.237267
	Band3	0.445364	0.648204	−0.554224	0.226745
	Band4	0.644482	−0.302524	−0.154528	−0.666426
	Band8	0.582397	−0.354568	0.350533	0.669486
Mg-OH基团	Band1	0.237826	0.515545	0.454256	0.684865
	Band4	0.434612	0.699602	−0.294525	−0.485568
	Band6	0.649462	−0.358542	−0.540554	0.395426
	Band7	0.542688	−0.344264	0.642136	−0.365452
CO₃^2-基团	Band1	−0.236845	0.565217	0.391453	0.605438
	Band3	−0.440441	0.646354	−0.134504	−0.645021
	Band4	−0.644187	−0.250453	−0.634035	0.342878
	Band5	−0.574503	−0.447450	0.651055	−0.203504

下载: 导出CSV

表 5 新发现矿化点信息统计

Table 5. Statistics of newly discovered mineralization occurrence information

编号	点位坐标/m	出露地层	容矿岩石	Cu	Zn	Pb	Ag	Au	所在区位	备注
编号	点位坐标/m	出露地层	容矿岩石	w_B/%			w_B/10⁻⁶		所在区位	备注
KH001	x=3913998 y=19555231	Ar₂t₃	石榴子石绢英片岩	0.5342	0.00254	0.00108	0.214	0.00123	省道335旁	铜矿化点
KH002	x=3908517 y=19553831	Pt₁b	绢英片岩	0.5245	0.00296	0.00157	0.111	0.0175	刘庄冶西南	铜矿化点
KH007	x=3919153 y=19566379	Pt₁b	碳质板岩夹白云石大理岩	2.0586	0.00307	0.00192	1.866	0.532	前海西南	金、铜矿化点
KH010	x=3909536 y=19574976	Ar₂j	石英岩、含碳绢英片岩	3.6783	0.00167	0.00219	0.718	0.878	篱笆沟南	金矿化点、铜矿化线索点
KH014	x=3876096 y=19533351	Pt₁b，Pt₁yj	碳质板岩、白云石大理岩	0.5345	0.00164	0.00123	0.215	0.024	柳仙洞西	铜矿化点
KH020	x=3884197 y=19551670	Pt₁yj，Chm	白云石大理岩、安山岩	0.0494	4.8988	7.9696	4.343	0.0264	上桃沟村	铅、锌矿化点，铜矿化线索点
KH027	x=3864443 y=19533227	Pt₁yj	白云石大理岩	0.6476	0.00161	0.0011	0.275	0.0331	西岭梁西北	铜矿化点
KH029	x=3865560 y=19533098	Pt₁yj	白云石大理岩	0.565	0.00143	0.000625	1.008	0.476	南白山东	铜矿化点
KH030	x=3865508 y=19532389	Pt₁yj	白云石大理岩	1.1206	0.00185	0.00329	3.246	0.0471	小场梁东	铜矿化点
注：Ar₂t_3. 横岭关亚群铜凹组三段；Pt₁b_. 中条群篦子沟组；Ar₂j_. 宋家山群绛道沟组；Pt₁yj_. 中条群余家山组；Chm_. 熊耳群马家河组

下载: 导出CSV

参考文献(57)

[1]	CRÓSTA A P, MOORE J M. Enhancement of landsat thematic mapper imagery for residual soil mapping in SW Minais Gerais State, Brazil: A prospecting case history in greenstone belt terrain[C]//Institute of Michigan. Proceedings of the Seventh Thematic Conference on Remote Sensing for Exploration Geology: Methods Integration Solutions. Calgary: Institute of Michigan, 1989: 1173-1187.
[2]	RAJESH H M. Mapping Proterozoic unconformity-related uranium deposits in the Rockhole area, northern Territory, Australia using landsat ETM+[J]. Ore Geology Reviews, 2008, 33(3/4): 382-396. doi: 10.1016/j.oregeorev.2007.02.003
[3]	NGCOFE L, MINNAAR H, CHEVALLIER L. A comparative study of hyperspectral versus multispectral images as an aid in geological mapping near Alexander Bay, northern Cape, South Africa[J]. South African Journal of Geology, 2010, 113(2): 141-154.
[4]	张亮, 那晓东, 刘知, 等. 基于国产GF-2卫星影像的遥感地质解译: 以阿吾拉勒地区为例[J]. 地质科技情报, 2018, 37(2): 233-240. ZHANG L, NA X D, LIU Z, et al. Remote sensing geological interpretation based on domestic GF-2 satellite imagery: A case study of the Awulale area[J]. Geological Science and Technology Information, 2018, 37(2): 233-240. (in Chinese with English abstract
[5]	JAIN R, SHARMA R U. Airborne hyperspectral data for mineral mapping in southeastern Rajasthan, India[J]. International Journal of Applied Earth Observation and Geoinformation, 2019, 81: 137-145. doi: 10.1016/j.jag.2019.05.007
[6]	KUMAR C, CHATTERJEE S, OOMMEN T, et al. Automated lithological mapping by integrating spectral enhancement techniques and machine learning algorithms using AVIRIS-NG hyperspectral data in Gold-bearing granite-greenstone rocks in Hutti, India[J]. International Journal of Applied Earth Observation and Geoinformation, 2020, 86: 102006. doi: 10.1016/j.jag.2019.102006
[7]	冯博, 段培新, 程旭, 等. 高分五号航天高光谱遥感技术在甘肃龙首山铀矿找矿中的应用[J]. 现代地质, 2022, 36(6): 1594-1604. FENG B, DUAN P X, CHENG X, et al. Application of GF-5 satellite hyperspectral data to uranium ore geological prospecting in Longshoushan area in Gansu Province[J]. Geoscience, 2022, 36(6): 1594-1604. (in Chinese with English abstract
[8]	徐大兴, 杨彪, 邵兆刚, 等. 哈达门沟金矿蚀变分带的高光谱分析及找矿意义[J]. 自然资源遥感, 2023, 35(1): 123-131. XU D X, YANG B, SHAO Z G, et al. A hyperspectral analysis of alteration zoning in the Hadamengou gold deposit and its significance for ore prospecting[J]. Remote Sensing for Natural Resources, 2023, 35(1): 123-131. (in Chinese with English abstract
[9]	YE B, TIAN S F, CHENG Q M, et al. Application of lithological mapping based on advanced hyperspectral imager (AHSI) imagery onboard Gaofen-5 (GF-5) satellite[J]. Remote Sensing, 2020, 12(23): 3990. doi: 10.3390/rs12233990
[10]	孙雨, 刘家军, 赵英俊, 等. 基于GF-5高光谱数据的蚀变矿物填图及地质应用: 以甘肃省瓜州县花牛山地区为例[J]. 中国地质, 2022, 49(2): 558-574. SUN Y, LIU J J, ZHAO Y J, et al. Alteration mineral mapping based on the GF-5 hyperspectral data and its geological application: An example of the Huaniushan area in Guazhou County of Gansu Province[J]. Geology in China, 2022, 49(2): 558-574. (in Chinese with English abstract
[11]	SHEIKHRAHIMI A, POUR A B, PRADHAN B, et al. Mapping hydrothermal alteration zones and lineaments associated with orogenic gold mineralization using ASTER data: A case study from the Sanandaj-Sirjan Zone, Iran[J]. Advances in Space Research, 2019, 63(10): 3315-3332. doi: 10.1016/j.asr.2019.01.035
[12]	徐燕飞, 陈永春, 李静, 等. 煤电基地CO₂和CH₄遥感监测及时空特征分析[J]. 煤田地质与勘探, 2024, 52(6): 79-90. XU Y F, CHEN Y C, LI J, et al. Remote sensing monitoring and spatiotemporal characteristics of CO₂ and CH₄ concentrations in coal-electricity production bases[J]. Coal Geology & Exploration, 2024, 52(6): 79-90. (in Chinese with English abstract
[13]	王晓云, 井国正, 李文君, 等. 基于多源遥感卫星数据的青海东昆仑沟里地区线性构造识别及找矿预测[J]. 地质科技通报, 2024, 43(1): 326-342. doi: 10.19509/j.cnki.dzkq.2022.0268 WANG X Y, JING G Z, LI W J, et al. Lineament mapping and deposit prospecting in the Gouli area, East Kunlun, Qinghai Province: Using multisource remote sensing data[J]. Bulletin of Geological Science and Technology, 2024, 43(1): 326-342. (in Chinese with English abstract doi: 10.19509/j.cnki.dzkq.2022.0268
[14]	陈富强. 伊宁至阿克苏铁路那拉提山越岭段关键性工程地质问题遥感解译与分析[J]. 地质科技通报, 2023, 42(2): 288-296. doi: 10.19509/j.cnki.dzkq.tb20210646 CHEN F Q. Remote sensing interpretation and analysis of key engineering geological problems in the Nalati Mountain crossing section of the Yining-Aksu Railway[J]. Bulletin of Geological Science and Technology, 2023, 42(2): 288-296. (in Chinese with English abstract doi: 10.19509/j.cnki.dzkq.tb20210646
[15]	LI X. A deep learning framework for the characterization of mineral in duced spectral signatures in high-dimensional reflectance data[J]. Remote Sensing, 2020, 12(8): 1274.
[16]	GALLWEY J, ROBIATI C, COGGAN J, et al. A Sentinel-2 based multispectral convolutional neural network for detecting artisanal small-scale mining in Ghana: Applying deep learning to shallow mining[J]. Remote Sensing of Environment, 2020, 248: 111970. doi: 10.1016/j.rse.2020.111970
[17]	SALATI S, VAN RUITENBEEK F, VAN DER MEER F, et al. Detection of alteration induced by onshore gas seeps from ASTER and WorldView-2 data[J]. Remote Sensing, 2014, 6(4): 3188-3209. doi: 10.3390/rs6043188
[18]	AMER R, EL MEZAYEN A, HASANEIN M. ASTER spectral analysis for alteration minerals associated with gold mineralization[J]. Ore Geology Reviews, 2016, 75: 239-251. doi: 10.1016/j.oregeorev.2015.12.008
[19]	侯占国, 赵增杰, 李嵩, 等. 山西省矿产资源潜力评价项目报告[R]. 太原: 山西省地质调查院, 2012. HOU Z G, ZHAO Z J, LI S, et al. Shanxi Province mineral resource potential assessment project report[R]. Taiyuan: Geological Survey of Shanxi Province, 2012. (in Chinese)
[20]	杨映春, 李云平, 曹有全. 基于Landsat 8和高分一号卫星数据的青海巴尔达吾地区铅、镍多金属矿化信息提取[J]. 矿产勘查, 2024, 15(10): 1824-1833. YANG Y C, LI Y P, CAO Y Q. Extraction of lead, nickel polymetallic mineralization information in Baldau, Qinghai based on Landsat 8 and GF-1 data[J]. Mineral Exploration, 2024, 15(10): 1824-1833. (in Chinese with English abstract
[21]	谢文扬, 刘磊, 赵英芬. 基于GF-1和Landsat 8影像的新疆东天山昌吉地区岩性识别[J]. 遥感技术与应用, 2023, 38(6): 1423-1432. doi: 10.11873/j.issn.1004-0323.2023.6.1423 XIE W Y, LIU L, ZHAO Y F. Lithology identification in Changji area, eastern Tianshan, Xinjiang using GF-1 and Landsat 8 data[J]. Remote Sensing Technology and Application, 2023, 38(6): 1423-1432. (in Chinese with English abstract doi: 10.11873/j.issn.1004-0323.2023.6.1423
[22]	陈玲, 贾佳, 王海庆. 高分遥感在自然资源调查中的应用综述[J]. 国土资源遥感, 2019, 31(1): 1-7. CHEN L, JIA J, WANG H Q. An overview of applying high resolution remote sensing to natural resources survey[J]. Remote Sensing for Land & Resources, 2019, 31(1): 1-7. (in Chinese with English abstract
[23]	魏长婧. 遥感技术在矿业领域的应用现状及发展趋势综述[J]. 北京测绘, 2022, 36(10): 1285-1292. doi: 10.19580/j.cnki.1007-3000.2022.10.001 WEI C J. Application status and development trend of the remote sensing technology in mining areas[J]. Beijing Surveying and Mapping, 2022, 36(10): 1285-1292. (in Chinese with English abstract doi: 10.19580/j.cnki.1007-3000.2022.10.001
[24]	孙军刚, 李洪英, 刘晓煌, 等. 中条山铜矿峪铜矿床蚀变及矿化特征研究[J]. 矿床地质, 2014, 33(6): 1306-1324. doi: 10.3969/j.issn.0258-7106.2014.06.010 SUN J G, LI H Y, LIU X H, et al. Alteration and mineralization characteristics of Tongkuangyu copper deposit in Zhongtiao Mountain, Shanxi Province[J]. Mineral Deposits, 2014, 33(6): 1306-1324. (in Chinese with English abstract doi: 10.3969/j.issn.0258-7106.2014.06.010
[25]	SEIFI A, ESMAEILY A, MOKHTARI Z. A new hybrid method for epithermal gold exploration using multi-sensor satellite data in Sistan and Baluchestan Province (Iran)[J]. Ore Geology Reviews, 2021, 138: 104357. doi: 10.1016/j.oregeorev.2021.104357
[26]	HUANG X, ZHANG L P. An SVM ensemble approach combining spectral, structural, and semantic features for the classification of high-resolution remotely sensed imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(1): 257-272. doi: 10.1109/TGRS.2012.2202912
[27]	AMER R, KUSKY T, GHULAM A. Lithological mapping in the central eastern desert of Egypt using ASTER data[J]. Journal of African Earth Sciences, 2010, 56(2/3): 75-82. doi: 10.1016/j.jafrearsci.2009.06.004
[28]	JIANG Y T. Research on road extraction of remote sensing image based on convolutional neural network[J]. EURASIP Journal on Image and Video Processing, 2019, 2019(1): 31. doi: 10.1186/s13640-019-0426-7
[29]	王生礼, 李志军. 遥感蚀变信息提取研究综述[J]. 地质与资源, 2023, 32(4): 462-470. WANG S L, LI Z J. A review of remote sensing alteration information extraction techniques[J]. Geology and Resources, 2023, 32(4): 462-470. (in Chinese with English abstract
[30]	白杨林, 吕凤军, 苏鸿博, 等. 高光谱遥感蚀变矿物信息提取研究综述[J]. 遥感信息, 2023, 38(1): 1-10. doi: 10.20091/j.cnki.1000-3177.2023.01.001 BAI Y L, LYU F J, SU H B, et al. Review of hyperspectral remote sensing altered mineral information extraction[J]. Remote Sensing Information, 2023, 38(1): 1-10. (in Chinese with English abstract doi: 10.20091/j.cnki.1000-3177.2023.01.001
[31]	王艺龙, 王然, 严子清, 等. 基于GF-2和ASTER数据青海德龙地区构造蚀变信息提取及找矿预测[J]. 自然资源遥感, 2024, 36(1): 217-226. doi: 10.6046/zrzyyg.2022444 WANG Y L, WANG R, YAN Z Q, et al. Tectonic alteration information extraction and prospecting prediction for the Delong area of Qinghai Province based on GF-2 and ASTER data[J]. Remote Sensing for Natural Resources, 2024, 36(1): 217-226. (in Chinese with English abstract doi: 10.6046/zrzyyg.2022444
[32]	韩燿徽, 王翠芝, 吴志杰, 等. 内蒙古赤峰柴胡栏子金矿田遥感地质解译和蚀变信息提取与找矿预测[J]. 现代地质, 2024, 38(4): 1076-1091. doi: 10.19657/j.geoscience.1000-8527.2023.112 HAN Y H, WANG C Z, WU Z J, et al. Remote sensing geological interpretation, alteration information extraction, and mineral prospecting prediction in the Chaihulanzi gold field, Chifeng, Inner Mongolia[J]. Geoscience, 2024, 38(4): 1076-1091. (in Chinese with English abstract doi: 10.19657/j.geoscience.1000-8527.2023.112
[33]	童勤龙, 叶发旺, 秦明宽, 等. WorldView-3遥感数据在巴音戈壁盆地本巴图地区铀矿勘查中的应用[J]. 地质论评, 2022, 68(6): 2349-2364. doi: 10.16509/j.georeview.2022.08.071 TONG Q L, YE F W, QIN M K, et al. Application of WorldView-3 remote sensing data to uranium exploration in Benbatu area, Bayingobi Basin[J]. Geological Review, 2022, 68(6): 2349-2364. (in Chinese with English abstract doi: 10.16509/j.georeview.2022.08.071
[34]	尹展, 张建国, 陈星霖, 等. 植被覆盖区老旧矿山边部遥感蚀变信息提取技术探讨[J]. 地质与资源, 2024, 33(2): 187-195. doi: 10.13686/j.cnki.dzyzy.2024.02.007 YIN Z, ZHANG J G, CHEN X L, et al. Alteration information extraction by remote sensing technology around old mines in vegetation-covered areas[J]. Geology and Resources, 2024, 33(2): 187-195. (in Chinese with English abstract doi: 10.13686/j.cnki.dzyzy.2024.02.007
[35]	赵佳琪, 董新丰, 李娜, 等. 基于高光谱数据的甘肃花西山金矿蚀变特征分析与找矿预测应用[J]. 地质与勘探, 2023, 59(1): 122-133. doi: 10.12134/j.dzykt.2023.01.010 ZHAO J Q, DONG X F, LI N, et al. Alteration characteristics and prospecting prediction of the Huaxishan gold deposit in Gansu Province based on hyperspectral data[J]. Geology and Exploration, 2023, 59(1): 122-133. (in Chinese with English abstract doi: 10.12134/j.dzykt.2023.01.010
[36]	祁昌炜, 董基恩, 程旭, 等. ZY-102D高光谱数据在柴北缘荒漠区蚀变矿物填图及找矿中的应用[J]. 自然资源遥感, 2024, 36(4): 31-42. QI C W, DONG J E, CHENG X, et al. Application of ZY-102D hyperspectral data to altered mineral mapping and ore prospecting in desert areas along the northern margin of the Qaidam Basin[J]. Remote Sensing for Natural Resources, 2024, 36(4): 31-42. (in Chinese with English abstract
[37]	张玉君, 曾朝铭, 姚佛军. 利用光谱角填图(SAM)优化多光谱遥感异常[J]. 矿物学报, 2015, 35(增刊1): 985. ZHANG Y J, ZENG Z M, YAO F J. Optimization of multispectral remote sensing anomaly by spectral angle mapping (SAM)[J]. Acta Mineralogica Sinica, 2015, 35(S1): 985. (in Chinese with English abstract
[38]	李嵩, 李海鹰. 遥感在矿产资源潜力评价中的综合应用研究: 以山西省为例[J]. 国土资源遥感, 2012, 24(1): 111-119. doi: 10.6046/gtzyyg.2012.01.20 LI S, LI H Y. A comprehensive study of applying remote sensing in the evaluation of mineral resource potential: A case study of the remote sensing application in Shanxi Province[J]. Remote Sensing for Land & Resources, 2012, 24(1): 111-119. (in Chinese with English abstract doi: 10.6046/gtzyyg.2012.01.20
[39]	薛克勤. 中条裂谷构造与成矿作用研究[D]. 北京: 中国地质大学(北京), 2006. XUE K Q. Study on the relation between structure and metallogenesis in the Zhongtiao rift[D]. Beijing: China University of Geosciences(Beijing), 2006. (in Chinese with English abstract
[40]	韩月池. 论中条山中部地区地质地层概况[J]. 华北自然资源, 2019(6): 68-69. HAN Y C. General situation of geological strata in the central area of Zhongtiaoshan Mountain[J]. Huabei Natural Resources, 2019(6): 68-69. (in Chinese with English abstract
[41]	真允庆, 杜继盛, 刘丽玲, 等. 中条裂谷与落家河铜矿床[M]. 武汉: 中国地质大学出版社, 1993. ZHEN Y Q, DU J S, LIU L L, et al. The Zhongtiao rift zone and the Luojiahe copper deposit[M]. Wuhan: China University of Geosciences Press, 1993. (in Chinese)
[42]	孙继源, 冀树楷, 真允庆. 中条裂谷铜矿床[M]. 北京: 地质出版社, 1995. SUN J Y, JI S K, ZHEN Y Q. The copper deposits in the Zhongtiao rift[M]. Beijing: Geological Publishing House, 1995. (in Chinese)
[43]	崔小军, 康顺福, 刘家军, 等. 中条裂谷的递进演化与王屋山地区铜矿成矿地质条件分析[J]. 地质找矿论丛, 2007, 22(1): 24-30. CUI X J, KANG S F, LIU J J, et al. Stepwise evolution of Zhongtiao rift and analysis on copper mineralization conditions in Wangwushan region[J]. Contributions to Geology and Mineral Resources Research, 2007, 22(1): 24-30. (in Chinese with English abstract
[44]	邓良, 程先富, 谢金红, 等. SPOT5影像数据不同融合方法的比较与评价[J]. 测绘与空间地理信息, 2012, 35(3): 19-23. doi: 10.3969/j.issn.1672-5867.2012.03.006 DENG L, CHENG X F, XIE J H, et al. Comparisons and evaluations between different fusion methods on SPOT 5 image data[J]. Geomatics & Spatial Information Technology, 2012, 35(3): 19-23. (in Chinese with English abstract doi: 10.3969/j.issn.1672-5867.2012.03.006
[45]	吕云峰. 一种手动野外反射光谱测量装置在地表测量中的应用[J]. 长春师范学院学报, 2012, 31(9): 86-89. doi: 10.3969/j.issn.1008-178X-B.2012.09.024 LYU Y F. The application of a manual system used to measure the reflectance spectrum of land surface in field[J]. Journal of Changchun Normal University, 2012, 31(9): 86-89. (in Chinese with English abstract doi: 10.3969/j.issn.1008-178X-B.2012.09.024
[46]	VAN DER MEER F. Spectral curve shape matching with a continuum removed CCSM algorithm[J]. International Journal of Remote Sensing, 2000, 21(16): 3179-3185. doi: 10.1080/01431160050145063
[47]	WANG W, WANG J, ZHOU K. et al. Analysis and research on mineral hyperspectral features[C]//Anon. Proceedings of 2015 International Symposium on Material, Energy and Environment Engineering. [S. l. ]: Atlantis Press, 2015: 9-12.
[48]	CLARK R N, ROUSH T L. Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications[J]. Journal of Geophysical Research: Solid Earth, 1984, 89(7): 6329-6340.
[49]	吴志春, 叶发旺, 郭福生, 等. 主成分分析技术在遥感蚀变信息提取中的应用研究综述[J]. 地球信息科学学报, 2018, 20(11): 1644-1656. doi: 10.12082/dqxxkx.2018.180195 WU Z C, YE F W, GUO F S, et al. A review on application of techniques of principle component analysis on extracting alteration information of remote sensing[J]. Journal of Geo-Information Science, 2018, 20(11): 1644-1656. (in Chinese with English abstract doi: 10.12082/dqxxkx.2018.180195
[50]	张玉君, 杨建民, 姚佛军. 用ASTER数据进行不同类型矿床蚀变异常提取研究[J]. 矿床地质, 2006, 25(增刊1): 507-510. doi: 10.16111/j.0258-7106.2006.s1.129 ZHANG Y J, YANG J M, YAO F J. The extraction of OHA from different types of deposits by using ASTER data[J]. Mineral Deposits, 2006, 25(S1): 507-510. (in Chinese with English abstract doi: 10.16111/j.0258-7106.2006.s1.129
[51]	张玉君, 杨建民, 陈薇. ETM⁺(TM)蚀变遥感异常提取方法研究与应用: 地质依据和波谱前提[J]. 国土资源遥感, 2002, 14(4): 30-36. doi: 10.3969/j.issn.1001-070X.2002.04.007 ZHANG Y J, YANG J M, CHEN W. A study of the method for extractioh of alteration anomalies from the ETM⁺(TM) data and its application: Geologic basis and spectral precondition[J]. Remote Sensing for Land & Resources, 2002, 14(4): 30-36. (in Chinese with English abstract doi: 10.3969/j.issn.1001-070X.2002.04.007
[52]	张夏青. 基于遥感地质解译和蚀变信息提取的找矿区预测: 以新疆东准噶尔地区为例[D]. 北京: 中国地质大学(北京), 2016. ZHANG X Q. Prediction of mining area based on remote sensing geological interpretation and alteration information extraction: Taking Xinjiang East Junggar area as an example[D]. Beijing: China University of Geosciences(Beijing), 2016. (in Chinese with English abstract
[53]	赵仕宝, 蔡进. 基于PCA方法的Aster遥感影像矿化蚀变信息提取应用研究[J]. 世界有色金属, 2020(10): 186-189. ZHAO S B, CAI J. Application research on mineralization and alteration information extraction of Aster remote sensing image based on PCA method[J]. World Nonferrous Metals, 2020(10): 186-189. (in Chinese with English abstract
[54]	柴东浩. 中条山铜矿地质概论[J]. 地质科技情报, 1982, 1(增刊1): 63-65. CHAI D H. Introduction to geology of Zhongtiaoshan copper mine[J]. Geological Science and Technology Information, 1982, 1(S1): 63-65. (in Chinese with English abstract
[55]	赵斌, 陈毓川, 王双猗, 等. 三岔沟金矿区钼矿成矿时代及中条山区找矿方向的研究[J]. 地质学报, 2009, 83(9): 1335-1343. ZHAO B, CHEN Y C, WANG S Y, et al. Ore-forming age of molybdenite deposit in the Sanchagou gold ore area and prospecting direction in the Zhongtiao Mountain region[J]. Acta Geologica Sinica, 2009, 83(9): 1335-1343. (in Chinese with English abstract
[56]	许伟, 杨德芳, 陈李昊, 等. 多源遥感影像融合处理提取格拉丹东雪山区域特征信息[J]. 地质科技通报, 2024, 43(2): 370-385. XU W, YANG D F, CHEN L H, et al. Fusion processing of multisource remote sensing images for extracting characteristic information from the Geladandong snow mountain area[J]. Bulletin of Geological Science and Technology, 2024, 43(2): 370-385. (in Chinese with English abstract
[57]	杨金中, 赵福岳, 杨日红, 等. 矿产资源遥感调查技术要求(1∶50 000): DD2011-05[S]. 北京: 中国地质调查局, 2011. YANG J Z, ZHAO F Y, YANG R H, et al. Technical Requirements for Mineral Resources Remote Sensing Survey (1∶ 50000 ): DD2011-05[S]. Beijing: China Geological Survey, 2011. (in Chinese)