白岗岩型铀矿关键要素识别遥感应用——以纳米比亚欢乐谷地区为例

Remote Sensing Application in the Identification of Key Elements of Alaskite-type Uranium Deposits:A Case Study of Gaudeanmus Area in Namibia

文章以ASTER和Quickbird遥感数据为数据源,以阈值分割、类别集群算法、相邻图斑合并、光谱角填图及目视解译等方法,以白岗岩型铀成矿要素提取为目的,开展了欢乐谷地区白岗岩型铀成矿相关的地层、岩体和构造的识别工作。最终精确识别了大理岩岩层、含矿白岗岩体、断裂构造,准确识别出多处地质图上未标出的与铀矿化密切相关的罗辛组大理岩,为铀成矿新区突破提供了重要依据。由此得出,采用高空间分辨率可见光-近红外波段与中等分辨率热红外波段的组合遥感数据,遥感技术能够精确提取白岗岩型铀矿成矿要素,为该类型铀矿勘查提供必要的技术支撑。

In this paper,ASTER and Quickbird data were used with the methods of threshold segmentation,category clustering algorithm,adjacent pattern merging,spectral angle mapping and visual interpretation to extract the mineralization elements of alaskite type uranium.The strata,rock masses and structures related to the alaskite-type uranium mineralization were identified in the Gaudeanmus area.In the end,the marble strata,ore-bearing granite rock bodies,and faulted structures were accurately identified,and many marbles of the Rossing Formation closely related to uranium mineralization which were not marked on the geological map were accurately circumscribed,which provides an important basis for the breakthrough in prospecting for new uranium mineralization areas.It is concluded that remote sensing technology can accurately extract the mineralization elements of alaskite rock-type uranium deposits,and provide necessary technical support for the exploration of this type of uranium deposits by combining the remote sensing data of high spatial resolution visible-near infrared band and medium-resolution thermal infrared band.