EXTRACTION OF ALTERED MINERAL INFORMATION BASED ON MULTI-SOURCE REMOTE SENSING DATA: A CASE STUDY OF JIAMA COPPER POLYMETALLIC DEPOSIT
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摘要: 以甲玛矿区的ETM+(TM)数据和Aster数据为数据源, 采用波段代数运算法和主成分分析法提取两种数据中的蚀变矿物信息, 然后将蚀变信息结果融合得到研究区矿物蚀变分布图。ETM+(TM)数据适合提取羟基、铁染、碳酸盐等基团(离子)信息, 为遥感找矿提供基础的技术支撑。Aster数据可以识别出更细化的蚀变矿物, 如方解石、褐铁矿、绿泥石、白云母和高岭石等。通过与研究区地质资料及前人勘探结果比对分析, 遥感矿物蚀变信息结果有效、可靠。Abstract: This paper extracted the altered minerals in Jiama copper polymetallic deposit by two methods: bands algebraic operation and principal component analysis with ETM+(TM) data and Aster data and got the distribution map of altered minerals by fusing alteration information.ETM+(TM) data is suitable to recognize hydroxyl group, iron and carbonate and can offer basic remote sensing technology. Aster data can extract more minerals, such as dolomite, limonite, chlorite, muscovite and kaolinite. By comparing with the geological data and actual exploration results, the extraction results of mineral alteration are effective and reliable.
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图 1 甲玛矿区建造构造图[11]
1—第四系;2—楚木龙组;3—林布宗组;4—多底沟组;5—硅帽;6—花岗斑岩;7—花岗闪长斑岩;8—二长花岗斑岩;9—石英闪长玢岩;10—辉绿玢岩;11—矽卡岩;12—矿体;13—地层界线;14—角岩蚀变界线;15—正断层;16—逆断层;17—斜歪倒转背斜;18—斜歪倒转向斜
Figure 1. The Jiama mine construction structural map
表 1 Landsat-7 ETM+(TM)参数
Table 1. The parameter of Landsat-7 ETM+(TM) data
通道 波长/μm 波段 地面分辨率/m 应用 1 0.45~0.52 蓝 30 海色、植被、土壤识别 2 0.52~0.60 绿 30 植被绿色反射 3 0.63~0.69 红 30 叶绿素吸收、植被识别 4 0.76~0.90 近红外 30 生物量、水面识别 5 1.55~1.75 短波红外 30 植被湿度、雪、云识别 6 10.4~12.5 热红外 60 热制图、植被热胁迫 7 2.09~2.35 短波红外 30 水热制图 8 0.45~0.52 全色波段 15 制图 表 2 Aster数据参数
Table 2. The parameters of Aster
光学子系统 波段 波长/μm 空间分辨率/m 辐射分辨率 可见光近红外(VNIR) Band 1 0.52~0.60 15 NE Δρ≤0.5% Band 2 0.63~0.69 Band 3 0.76~0.86 Band 3N 0.76~0.86 短波红外(SWIR) Band4 1.600~1.700 30 NE Δρ≤0.5% Band5 2.145~2.185 NE Δρ≤1.3% Band6 2.185~2.225 NE Δρ≤1.3% Band7 2.235~2.285 NE Δρ≤1.3% Band8 2.295~2.365 NE Δρ≤1.0% Band9 2.360~2.430 NE Δρ≤1.3% 热红外(TIR) Band 10 8.125~8.475 90 NE ΔT≤0.3 K Band 11 8.475~8.825 Band 12 8.925~9.275 Band 13 10.25~10.95 Band 14 10.95~11.65 表 3 羟基-铁染-碳酸盐在ETM+(TM)数据中的波谱特征
Table 3. Spectral characteristics of mineral on Landsat ETM+(TM) data
基团离子 Band 1 Band 2 Band 3 Band 4 Band 5 Band6 Band 7 羟基 反射 吸收 反射 吸收 铁染 吸收 反射 吸收 反射 碳酸盐 反射 吸收 表 4 羟基、铁染、碳酸盐主成分分析特征向量
Table 4. Eigenvector of principal component analysis(PCA)
蚀变矿物 波段 主成分分析特征向量载荷因子贡献值 PC1 PC2 PC3 PC4 羟基 B1 0.462660 0.707850 -0.172077 0.505256 B4 0.602425 0.078441 0.664456 -0.435235 B5 0.636666 -0.482005 -0.591928 -0.109310 B7 0.132990 -0.510359 0.422503 0.737115 信息量 91.51% 7.98% 0.36% 0.15% 铁染 B1 0.416080 0.670401 0.575621 -0.214709 B3 0.495513 0.255463 -0.380474 0.737865 B4 0.529017 -0.045025 -0.565401 -0.631217 B5 0.549076 -0.695179 0.451909 0.104975 信息量 94.52% 5.14% 0.31% 0.03% 碳酸盐 B1 0.484244 0.602072 -0.201978 0.601849 B3 0.577498 0.241061 0.592879 -0.506834 B5 0.644576 -0.567005 -0.498904 -0.118838 B7 0.128552 -0.507844 0.598994 0.605620 信息量 90.51% 9.01% 0.35% 0.13% 表 5 羟基-铁染-碳酸盐在Aster数据中的波谱特征
Table 5. Spectral characteristics of hydroxyl group, iron and carbonate based on Aster data
蚀变矿物 Band 1 Band 2 Band 3 Band 4 Band 5 Band 6 Band 7 Band 8 Band 9 白云石 反射 反射 反射 微弱吸收 反射 吸收 反射 黄钾铁矾 反射 吸收 反射 反射 褐铁矿 反射 吸收 反射 吸收 钙铁榴石 吸收 反射 反射 吸收 绿泥石 吸收 反射 吸收 反射 吸收 白云母 微弱吸收 反射 吸收 反射 高岭石 反射 吸收 反射 表 6 几种蚀变矿物提取采用方法及对应Aster波段选择
Table 6. Bands selection based on Aster data
蚀变矿物 波段代数运算法 主成分分析法 白云石 (B6+B9)×0.5/B8 B1,B3,B4,(B5+B8)/2 绿泥石 (B5+B9)/(B7+B8) B1,B3,B4,B8 高岭石 B1,B3,B4,B6 白云母 B5/B6 B1,B4,B6,B7 褐铁矿 B2/B1 B1,B2,B3,B4 黄钾铁矾 B1,B4,B7,B8 钙铁榴石 B1,B3,B4,(B8+ B9)/2 -
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