摘要
以植被覆盖度较大的山东省兰陵县凤凰山铁矿区为例,选取覆盖该区的ASTER数据作为遥感数据源,首先进行了几何精纠正、大气校正和水体、阴影等干扰去除;然后在充分了解岩石波谱特征和ASTER数据波段特征的基础上选择了提取矿物蚀变信息的最优波段组合,采用主成分分析(Principal component analysis,PCA)法对研究区的铁染蚀变和羟基蚀变信息进行了提取,并对蚀变异常强度进行了标准化等级划分;最后通过分析蚀变信息与已知矿床的关系圈定了遥感异常区,并在矿化蚀变较强的地段选取8处铁染蚀变异常点和6处羟基蚀变异常点,通过布设踏勘路线进行了采样和验证。结果表明:从ASTER数据中提取的铁染和羟基蚀变信息的分布与实际情况吻合较好,其高值区分别对应着铁矿化和高岭土化强烈的地区,验证精度分别达到87.5%、83.3%。可见,在植被覆盖度较大的地区,ASTER数据的短波红外波段内仍包含丰富的矿物蚀变信息,可为地质找矿提供重要依据。
Owing to the growing demands for resources and less exploitable outcrop and shallow ore mines,it is urgent to look for new iron deposits around and below current iron deposits. As traditional prospecting methods are limited in doing this,remotely sensed mineralized alteration information is of great directive significance to geological prospecting work. But extracting alteration information in high vegetation covered areas is one of the difficulties in remotely sensed information extraction.The Fenghuangshan iron deposit is located in Lanling County of Shandong province with dense vegetation coverage,so,it is selected as the study area in this paper. Based on ASTER data,firstly,the ASTER data is geometrically corrected and atmospherically corrected,the water and other interference informations are removed; then,the optimal band combination of mineral alteration information extraction is selected,with references to the spectra of typical altered minerals in the USGS standard spectral database,the principal component analysis（ PCA） method is applied to extract the ferric contamination and hydroxyl alteration information,and they are enhanced and classified by thresholding; finally,the anomaly mineralization regions are delineated with references to both known deposits and related alterations,and 8 ferric contamination anomalies and 6 hydroxyl alteration anomalies are selected to validate. Due to high coverage of vegetation and soil and less exposed bedrock,and the agreement between remote sensing anomaly areas and mineralized alteration zones,Quaternary covered areas are investigated especially. The results show that,the extracted ferric contamination and hydroxyl alteration information are verified and the verification accuracy reaches 87. 5% and 83. 3% respectively,it proves that the ASTER data is of capacity to depict minerals＇ spectral characteristics in the short wave infrared ranges,which effectively facilitate geological prospecting in dense vegetation covered regions.
出处
《金属矿山》
CAS
北大核心
2016年第10期109-115,共7页
Metal Mine
基金
中国科学院"百人计划"项目(编号:Y34005101A
Y2ZZ03101B)
中国地质调查局工作项目(编号:12120113089200)
"十三五"国家科技支撑计划项目(编号:2015BAB05B05-02)
关键词
地质找矿
ASTER数据
遥感
铁矿化蚀变信息
主成分分析
Geological prospecting
ASTER data
Remote sensing
Iron mineralized alteration information
Principal component analysis
