Identification of Rare Metal Dikes by Multi-Platform Synchronous Thermal Infrared Remote Sensing in Hutoushan Area
-
摘要: 华北陆块北缘稀有金属矿床岩脉的遥感识别调查具有重要现实需求和理论研究意义.针对岩脉识别技术难点和研究区特殊的地质背景，提出来一种“天-空-地”同步热红外遥感铌钽多金属矿床岩脉识别算法，以辅助成矿岩脉识别.算法以Landsat-8卫星数据和同步采集的无人机热红外数据为主要数据源，解算修正地表比辐射率.结合天河石化钠长花岗岩的发射特征，利用阈值分割法划定13处岩脉发育区并开展野外踏勘查证.结果表明：提出的岩脉识别算法的准确性和可靠性较高，“天-空-地”同步热红外遥感可用于虎头山地区稀有金属岩脉识别.本研究为区域后续铌钽矿勘察工作提供了指导，同时也为可为稀有金属矿床的遥感探测识别提供有益参考.Abstract: Remote sensing identification of rare metal deposit dikes in the north margin of North China block has important practical needs and theoretical significance. In view of the technical difficulties of vein recognition and the special geological background of the study area, it proposes a "Space-Sky- Ground" synchronous thermal infrared remote sensing algorithm for Nb-Ta polymetallic deposit vein recognition to assist the identification of metallogenic veins. The algorithm uses landsat-8 satellite data and UAV thermal infrared data collected synchronously as the main data source to calculate and correct the surface specific emissivity. Combined with the emission characteristics of Tianhe Petrochemical albite granite and threshold segmentation method, 13 dike development areas were delimited and verified in the field. The results show that the accuracy and reliability of the proposed algorithm are high, and the "Space-Sky-Ground" synchronous thermal infrared remote sensing can be used to identify rare metal dikes in Hutoushan area. This study has provided guidance for the exploration of niobium-tantalum deposits in the study area, and will also provide a useful reference for the remote sensing detection and identification of rare metal deposits.
-
表 1 Landsat-8载荷信息
Table 1. Landsat-8 satellite payload information
传感器 波段 名称 波长范围(μm) 空间分辨率(m) OLI Band 1 COASTAL 0.43~0.45 30 Band 2 Blue 0.45~0.51 Band 3 Green 0.53~0.59 Band 4 Red 0.64~0.67 Band 5 NIR 0.85~0.88 Band 6 SWIR1 1.57~1.65 Band 7 SWIR2 2.11~2.29 Band 8 PAN 0.50~0.68 15 Band 9 Cirrus 1.36~1.38 30 TIRS Band 10 TIR1 10.60~11.19 100 Band 11 TIR2 11.50~12.51 
下载: 导出CSV
表 2 无人机热红外数据技术指标
Table 2. UAV thermal infrared data technical indicators
参数 技术指标 飞行时间 2023年10月20日11:00至11:25 飞行高度 150~200 m 空间分辨率 ＜0.5 m 波段设置 单波段(8~14 μm) 测量面积 1.2 km2 帧频 30 fps 噪声等校温差(NETD) ≤50 mK @ f/1.0 测温范围 -40 ℃至150 ℃(高增益模式)
-40 ℃至550 ℃(低增益模式)
下载: 导出CSV
-
Benson, T. R., Coble, M. A., Rytuba, J. J., et al., 2017. Lithium Enrichment in Intracontinental Rhyolite Magmas Leads to Li Deposits in Caldera Basins. Nature Communications, 8(1): 270. https://doi.org/10.1038/s41467-017-00234-y Chakhmouradian, A. R., Smith, M. P., Kynicky, J., 2015. From "Strategic" Tungsten to "Green" Neodymium: A Century of Critical Metals at a Glance. Ore Geology Reviews, 64: 455-458. https://doi.org/10.1016/j.oregeorev.2014.06.008 Chakraborty, T., Lee, X. H., Ermida, S., et al., 2021. On the Land Emissivity Assumption and Landsat-Derived Surface Urban Heat Islands: A Global Analysis. Remote Sensing of Environment, 265: 112682. https://doi.org/10.1016/j.rse.2021.112682 Chao, J. Q., Zhao, Z. F., Lai, Z. B., et al., 2023. Detecting Geothermal Anomalies Using Landsat 8 Thermal Infrared Remote Sensing Data in the Ruili Basin, Southwest China. Environmental Science and Pollution Research International, 30(11): 32065-32082. https://doi.org/10.1007/s11356-022-24417-3 Dai, J. J., Wang, D. H., Wang, H. Y., 2019. A Review of the Three Type Rare Mineral Resources Survey in China Using Remote Sensing. Acta Geologica Sinica, 93(6): 1270-1278(in Chinese with English abstract). doi: 10.3969/j.issn.0001-5717.2019.06.008 Dai, J. J., Zhao, L. X., Jiang, Q., et al., 2020. Review of Thermal-Infrared Spectroscopy Applied in Geological Ore Exploration. Acta Geologica Sinica, 94(8): 2520-2533(in Chinese with English abstract). doi: 10.3969/j.issn.0001-5717.2020.08.026 Duan, J. B., Peng, P., Yang, Z., et al., 2019. Prediction of Polymetallic Metallogenic Favorable Area Based on ASTER Data. Remote Sensing for Land & Resources, 31(3): 193-200(in Chinese with English abstract). Dyar, M. D., Gunter, M. E., Tasa, D., 2007. Mineralogy and Optical Mineralogy. Mineralogical Society of America Chantilly, VA. E, A. Q., 2018. Ore Characteristics and Ore Controlling Factors of Rare Metal Deposits of Typical Granite Type in the Middle of the Inner Mongolia Autonomous Region. Nonferrous Metals Science and Engineering, 9(2): 62-69(in Chinese with English abstract). Fan, Y. H., Wang, H., Yang, X. K., et al., 2018. Application of High-Resolution Remote Sensing Technology to the Prospecting for Rare Metal Mineralization Belt. Remote Sensing for Land & Resources, 30(1): 128-134(in Chinese with English abstract). Galve, J. M., Sánchez, J. M., García-Santos, V., et al., 2022. Assessment of Land Surface Temperature Estimates from Landsat 8-TIRS in a High-Contrast Semiarid Agroecosystem. Algorithms Intercomparison. Remote Sensing, 14(8): 1843. https://doi.org/10.3390/rs14081843 Gao, Y., Sun, Y., Zhao, Z., et al., 2017. 40Ar-39Ar Dating of Muscovite from the Zhaojinggou Nb-Ta Polymetallic Deposit in Wuchuan County of Inner Mongolia and Its Geological Implications. Rock and Mineral Analysis, 36(5): 551-558(in Chinese with English abstract). Gao, Y. B., Bagas, L., Li, K., et al., 2020. Newly Discovered Triassic Lithium Deposits in the Dahongliutan Area, Northwest China: A Case Study for the Detection of Lithium-Bearing Pegmatite Deposits in Rugged Terrains Using Remote-Sensing Data and Images. Frontiers in Earth Science, 8: 591966. https://doi.org/10.3389/feart.2020.591966 Gao, Y. N., Zhang, W. C., 2008. Comparison Test and Research Progress of Topographic Correction on Remotely Sensed Data. Geographical Research, 27(2): 467-477, 484(in Chinese with English abstract). doi: 10.3321/j.issn:1000-0585.2008.02.024 He, J. L., Zhao, W., Li, A. N., et al., 2019. The Impact of the Terrain Effect on Land Surface Temperature Variation Based on Landsat-8 Observations in Mountainous Areas. International Journal of Remote Sensing, 40(5-6): 1808-1827. https://doi.org/10.1080/01431161.2018.1466082 Jiménez-Muñoz, J. C., Sobrino, J. A., Skoković, D., et al., 2014. Land Surface Temperature Retrieval Methods from Landsat-8 Thermal Infrared Sensor Data. IEEE Geoscience and Remote Sensing Letters, 11(10): 1840-1843. https://doi.org/10.1109/LGRS.2014.2312032 Kuenzer, C., Dech, S., 2013. Thermal Infrared Remote Sensing: Sensors, Methods, Applications. Springer, Amsterdam, Netherlands. Li, L. G., Wang, L. X., Zhu, Y. X., et al., 2023. Metallogenic Age and Process of Rare Metal-Bearing Pegmatites from the Northern Margin of Mufushan Complex, South China. Earth Science, 48(9): 3221-3244(in Chinese with English abstract). Liu, D. C., Tian, F., Qiu, J. T., et al., 2017. Application of Hyperspectral Remote Sensing in Solid Ore Exploration in the Liuyuan-Fangshankou Area. Acta Geologica Sinica, 91(12): 2781-2795(in Chinese with English abstract). doi: 10.3969/j.issn.0001-5717.2017.12.014 Liu, D. F., Chen, S. B., Chen, L., et al., 2015. Silicification Information Extraction Based on the Content of SiO2 from ASTER TIR Data. Earth Science, 40(8): 1396-1402(in Chinese with English abstract). Lou, D. B., Wang, D. H., Li, W. Y., et al., 2022. Progress of Prospecting Prediction Research for Granitic Pegmatite-Type Lithium Deposits at Home and Abroad. Mineral Deposits, 41(5): 975-988(in Chinese with English abstract). Lü, Z. H., Liu, K., Zhang, H., et al., 2023. The Potential Medium- and Large-Scale Be Ore Deposit in Altai, Xinjiang: A Case Study of Pegmatites from Chonghur. Acta Petrologica Sinica, 39(11): 3319-3333(in Chinese with English abstract). doi: 10.18654/1000-0569/2023.11.07 Mao, J. W., Song, S. W., Liu, M., et al., 2022. REE Deposits: Basic Characteristics and Global Metallogeny. Acta Geologica Sinica, 96(11): 3675-3697(in Chinese with English abstract). doi: 10.3969/j.issn.0001-5717.2022.11.001 Maurer, T., 2013. How to Pan-Sharpen Images Using the Gram-Schmidt Pan-Sharpen Method: A Recipe. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-1/W1: 239-244. https://doi.org/10.5194/isprsarchives-xl-1-w1-239-2013 Mwaniki, M. W., Moeller, M. S., Schellmann, G., 2015. A Comparison of Landsat 8 (OLI) and Landsat 7 (ETM+) in Mapping Geology and Visualising Lineaments: A Case Study of Central Region Kenya. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-7/W3: 897-903. https://doi.org/10.5194/isprsarchives-xl-7-w3-897-2015 Neinavaz, E., Skidmore, A. K., Darvishzadeh, R., 2020. Effects of Prediction Accuracy of the Proportion of Vegetation Cover on Land Surface Emissivity and Temperature Using the NDVI Threshold Method. International Journal of Applied Earth Observation and Geoinformation, 85: 101984. https://doi.org/10.1016/j.jag.2019.101984 Qin, Z. H., Zhang, M. H., Arnon, K., et al., 2001. Mono-Window Algorithm for Retrieving Land Surface Temperature from Landsat TM6 Data. Acta Geographica Sinica, 56(4): 456-466(in Chinese with English abstract). Sekertekin, A., Bonafoni, S., 2020. Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation. Remote Sensing, 12(2): 294. https://doi.org/10.3390/rs12020294 Shaw, R. A., Goodenough, K. M., Roberts, N. M. W., et al., 2016. Petrogenesis of Rare-Metal Pegmatites in High-Grade Metamorphic Terranes: A Case Study from the Lewisian Gneiss Complex of North-West Scotland. Precambrian Research, 281: 338-362. https://doi.org/10.1016/j.precamres.2016.06.008 Tardy, B., Rivalland, V., Huc, M., et al., 2016. A Software Tool for Atmospheric Correction and Surface Temperature Estimation of Landsat Infrared Thermal Data. Remote Sensing, 8(9): 696. https://doi.org/10.3390/rs8090696 Wang, D. H., Wang, R. J., Sun, Y., et al., 2016. A Review of Achievements in the Three-Type Rare Mineral Resources (Rare Resources, Rare Earth and Rarely Scattered Resources) Survey in China. Acta Geoscientica Sinica, 37(5): 569-580(in Chinese with English abstract). Wang, H., Qin, X. W., Fan, Y. H., et al., 2018. The Application of High Resolution Remote Sensing Technology to Ore-Prospecting in Dahongliutan-Fulugou Area of West Kunlun Mountains. Geology in China, 45(6): 1289-1301(in Chinese with English abstract). Wang, L., Cheng, Y., Lamb, D., et al., 2020. The Application of Rapid Handheld FTIR Petroleum Hydrocarbon-Contaminant Measurement with Transport Models for Site Assessment: A Case Study. Geoderma, 361: 114017. https://doi.org/10.1016/j.geoderma.2019.114017 Wulder, M. A., Loveland, T. R., Roy, D. P., et al., 2019. Current Status of Landsat Program, Science, and Applications. Remote Sensing of Environment, 225: 127-147. https://doi.org/10.1016/j.rse.2019.02.015 Xu, X. W., Li, H., Shi, F. P., et al., 2019. Metallogenic Characteristics and Prospecting of Granitic Pegmatite-Type Rare Metal Deposits in the Tugeman Area, Middle Part of Altyn Tagh. Acta Petrologica Sinica, 35(11): 3303-3316(in Chinese with English abstract). doi: 10.18654/1000-0569/2019.11.03 Zhang, C., Li, Z. D., Li, X. G., et al., 2019. Zircon U-Pb Dating and Hf Isotopic and Geochemical Characteristics for K-Feldspar Granite in Zhaojinggou, Inner Mongolia. Acta Petrologica et Mineralogica, 38(3): 303-317(in Chinese with English abstract). doi: 10.3969/j.issn.1000-6524.2019.03.002 代晶晶, 王登红, 王海宇, 2019. 我国三稀矿产资源遥感调查综述. 地质学报, 93(6): 1270-1278. doi: 10.3969/j.issn.0001-5717.2019.06.008 代晶晶, 赵龙贤, 姜琪, 等, 2020. 热红外高光谱技术在地质找矿中的应用综述. 地质学报, 94(8): 2520-2533. doi: 10.3969/j.issn.0001-5717.2020.08.026 段俊斌, 彭鹏, 杨智, 等, 2019. 基于ASTER数据的多金属成矿有利区预测. 国土资源遥感, 31(3): 193-200. https://www.cnki.com.cn/Article/CJFDTOTAL-GTYG201903024.htm 鄂阿强, 2018. 内蒙古中部典型花岗岩型稀有金属矿床特征和控矿因素. 有色金属科学与工程, 9(2): 62-69. https://www.cnki.com.cn/Article/CJFDTOTAL-JXYS201802011.htm 范玉海, 王辉, 杨兴科, 等, 2018. 基于高分辨率遥感数据的稀有金属矿化带勘查. 国土资源遥感, 30(1): 128-134. https://www.cnki.com.cn/Article/CJFDTOTAL-GTYG201801018.htm 高永年, 张万昌, 2008. 遥感影像地形校正研究进展及其比较实验. 地理研究, 27(2): 467-477, 484. doi: 10.3321/j.issn:1000-0585.2008.02.024 高允, 孙艳, 赵芝, 等, 2017. 内蒙古武川县赵井沟铌钽多金属矿床白云母40Ar-39Ar同位素年龄及地质意义. 岩矿测试, 36(5): 551-558. https://www.cnki.com.cn/Article/CJFDTOTAL-YKCS201705014.htm 李乐广, 王连训, 朱煜翔, 等, 2023. 华南幕阜山北缘含稀有金属伟晶岩成矿时代及成矿过程. 地球科学, 48(9): 3221-3244. doi: 10.3799/dqkx.2022.141 刘道飞, 陈圣波, 陈磊, 等, 2015. 以SiO2含量为辅助因子的ASTER热红外遥感硅化信息提取. 地球科学, 40(8): 1396-1402. doi: 10.3799/dqkx.2015.124 刘德长, 田丰, 邱骏挺, 等, 2017. 柳园-方山口地区航空高光谱遥感固体矿产探测及找矿效果. 地质学报, 91(12): 2781-2795. doi: 10.3969/j.issn.0001-5717.2017.12.014 娄德波, 王登红, 李婉悦, 等, 2022. 国内外花岗伟晶岩型锂矿找矿预测研究进展. 矿床地质, 41(5): 975-988. https://www.cnki.com.cn/Article/CJFDTOTAL-KCDZ202205007.htm 吕正航, 刘堃, 张辉, 等, 2023. 新疆阿尔泰潜在的中大型铍矿床: 以冲乎尔伟晶岩为例. 岩石学报, 39(11): 3319-3333. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXB202311007.htm 毛景文, 宋世伟, 刘敏, 等, 2022. 稀土矿床: 基本特点与全球分布规律. 地质学报, 96(11): 3675-3697. doi: 10.3969/j.issn.0001-5717.2022.11.001 覃志豪, Zhang, M. H., Arnon, K., 等, 2001. 用陆地卫星TM6数据演算地表温度的单窗算法. 地理学报, 56(4): 456-466. https://www.cnki.com.cn/Article/CJFDTOTAL-DLXB200104008.htm 王登红, 王瑞江, 孙艳, 等, 2016. 我国三稀(稀有稀土稀散)矿产资源调查研究成果综述. 地球学报, 37(5): 569-580. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXB201605006.htm 王辉, 秦绪文, 范玉海, 等, 2018. 高分遥感技术在西昆仑大红柳滩—俘虏沟地区地质找矿中的应用. 中国地质, 45(6): 1289-1301. https://www.cnki.com.cn/Article/CJFDTOTAL-DIZI201806018.htm 徐兴旺, 李杭, 石福品, 等, 2019. 阿尔金中段吐格曼地区花岗伟晶岩型稀有金属成矿特征与找矿预测. 岩石学报, 35(11): 3303-3316. doi: 10.18654/1000-0569/2019.11.03 张超, 李志丹, 李效广, 等, 2019. 内蒙古赵井沟钾长花岗岩锆石U-Pb定年、Hf同位素和岩石地球化学特征. 岩石矿物学杂志, 38(3): 303-317. doi: 10.3969/j.issn.1000-6524.2019.03.002 -
点击查看大图
图(7) / 表(2)
计量
- 文章访问数: 476
- HTML全文浏览量: 112
- PDF下载量: 48
- 被引次数: 0
