摘要
桂西南是中国重要的锰矿聚集带,近地表分布的沉积型锰矿通过遥感的方法能较好地获取异常,然而由于桂西南地区植被覆盖度较高,地形地貌特征明显,因此依据传统遥感的铁染和羟基异常提取的效果并不理想。在充分分析区域地质资料的基础上,结合桂西南沉积型锰矿的成因与特殊地形地貌特征之间的关系,通过将植被指数与已知锰矿区进行偏相关分析,探索锰矿分布与植被指数之间的敏感关联,建立锰矿的遥感胁迫植被指数异常综合模型。将该模型与遥感构造解译得到的地质构造信息相结合,在高分二号(GF-2)遥感影像上对靖西县周边进行初步预测并圈定了新的锰矿靶区。预测验证的结果表明,遥感胁迫植被指数异常综合模型与锰矿地质构造能够更好地叠合。
Southwest Guangxi is an important manganese ore accumulation zone in China.The near-surface sedimentary manganese deposits can obtain anomalies well by using remote sensing method.However,due to the high vegetation coverage and topographic and landform features in southwest Guangxi,Iron dye and abnormal extraction of hydroxyl is not ideal.Based on the full analysis of the regional geological data and the relationship between the genesis of the sedimentary manganese ore in southwest Guangxi and the special topography,this paper explores the correlation between the distribution of manganese ore and the vegetation index through the partial correlation analysis between the vegetation index and the known manganese ore area between the sensitive relationship between the establishment of manganese ore remote sensing co-vegetation index anomaly model.The model was combined with the remote sensing structure interpretation to obtain the geological structure information.The high-grade second(GF-2)remote sensing imagery was used to predict the periphery of Jingxi County and delineated a new target zone of manganese ore.The results of the prediction and verification show that the remote sensing RSI model can be better superposed with the manganese ore geological structure.
作者
陈三明
殷显阳
赵袁磊
黄远林
刘智颖
涂媛
韦龙
邵润泽
CHEN Sanming;YIN Xianyang;ZHAO Yuanlei;HUANG Yuanlin;LIU Zhiying;TU Yuan;WEI Long;SHAO Runze(School of Earth Sciences,Guilin University of Technology,Guilin 541006,Guangxi,China;College of Resources and Environment,Qinzhou University,Qinzhou 535000,Guangxi,China;China Chemical Geology and Mine Bureau Research Institute of Geological,Zhuozhou 072750,Hebei,China)
出处
《矿产与地质》
2017年第6期1126-1132,共7页
Mineral Resources and Geology
基金
国家自然科学基金项目(41372339)
大陆构造与动力学国家重点实验室开放基金项目(K201402)共同资助
关键词
锰矿
胁迫植被指数
高分遥感
偏回归分析
找矿预测
manganese ore
stress vegetation index
high-resolution remote sensing
partial regression analysis
ore-prospecting prediction
