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首页> 外文期刊>Advances in space research >Mapping Regolith and Gossan for Mineral Exploration in the Eastern Kumaon Himalaya, India using hyperion data and object oriented image classification
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Mapping Regolith and Gossan for Mineral Exploration in the Eastern Kumaon Himalaya, India using hyperion data and object oriented image classification

机译:使用超离子数据和面向对象的图像分类,绘制Regolith和Gossan在印度东部喜马拉雅山的矿产勘探图

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Crystalline in the Kumaon Himalaya, India near Askot area is a prominent site of the base metal mineralization and gossanised surface. This area is hosted by the sulphides and sulphates of Cu, Pb, Zn and Au and Ag mineralization with the altered rocks like sericite chlorite schist, gneiss etc. Due to the deep weathering this area is also a good illustration site of the gossanised outcrop. Regolith mapping through the multispectral remotely sensed data using different parametric and nonparametric classification algorithm has been used for many years. In recent years, object oriented classification for classification of object rather than pixel has gained a good success within the geospatial community. On the other hand, space borne hyperspectral remote sensing has gained a great success in identification of the minerals from space. The narrow contiguous bands of this hyperspectral remote sensing data can provide more information of the chemical content of the different minerals. In this study EO1 (Earth Observation) Hyperion hyperspectral sensor data has been evaluated for regolith and gossan mapping using the object oriented image classification technique. The efficacy of the hyperion data is evaluated in and around the Askot base metal mineral deposits for hydrothermal alteration and base metal minerals. Three sites were selected by regolith mapping using object oriented image classification method and were evaluated by the aid of hyperspectral data for alteration minerals. During the field verification it was found that the mineralization within these sites was associated with the dolomite, gneiss and schists. Strong hydrothermal activity and shearing were dominated at these sites. Minerals like carbonates, sulphates and sulphides of copper, lead, zinc and silver, magnetite along with the altered minerals like, mica, chlorite, talc etc. were found at the target sites. eCognition™ and ENVI~® software's were used for the object based classification and for the hyperspectral data processing, respectively. It was concluded from this study that object oriented classification is a suitable classification algorithm for regolith and gossan mapping as it uses the spatial, spectral and textural information of the remote sensing dataset. Target areas suggested by the object oriented classification method were examined by the hyperspectral data analysis. Results of the hyperspectral analysis were in good confirmation of the minerals found in the field as well as in the lab. Though the signal to noise ratio of the scene was low but still hyperion data was able to highlight the mineralogy of the Askot and nearby areas. It was also concluded by this study that the spectral analysis was very helpful for identification of the gossan and limonite over the conventional petrography analysis.
机译:印度库玛恩·喜马拉雅山附近阿库特地区的晶体是贱金属矿化和散乱的表面的重要部位。该地区是由铜,铅,锌,金和银的硫化物和硫酸盐矿化而成的,还有蚀变的岩石,如绢云母绿泥石片岩,片麻岩等。由于风化较深,该地区也是散布成片的好地方。使用不同的参数和非参数分类算法通过多光谱遥感数据进行Regolith映射已经使用了很多年。近年来,在地理空间界中,用于对象分类而不是像素分类的面向对象分类取得了很好的成功。另一方面,星载高光谱遥感在鉴定来自太空的矿物方面取得了巨大的成功。该高光谱遥感数据的狭窄连续带可以提供有关不同矿物化学成分的更多信息。在这项研究中,已经使用面向对象的图像分类技术对EO1(地球观测)Hyperion高光谱传感器数据进行了重石和戈桑映射的评估。在水热蚀变和基础金属矿物的Askot基础金属矿物矿床中及其周围评估高离子数据的有效性。使用面向对象的图像分类方法通过重石测绘选择了三个地点,并借助高光谱数据对蚀变矿物进行了评估。在现场核查期间,发现这些地点的矿化与白云岩,片麻岩和片岩有关。在这些地点,强烈的热液活动和剪切作用占主导地位。在目标地点发现了矿物质,如铜,铅,锌和银的碳酸盐,硫酸盐和硫化物,磁铁矿以及改变后的矿物质,如云母,亚氯酸盐,滑石等。 eCognition™和ENVI®软件分别用于基于对象的分类和高光谱数据处理。从这项研究得出的结论是,面向对象的分类是一种适用于regolith和gossan映射的分类算法,因为它使用了遥感数据集的空间,光谱和纹理信息。通过高光谱数据分析检查了面向对象分类方法建议的目标区域。高光谱分析的结果很好地证实了现场和实验室中发现的矿物。尽管场景的信噪比很低,但是高离子数据仍然能够突出Askot和附近地区的矿物学。这项研究还得出结论,与常规的岩相学分析相比,光谱分析对识别棉布和褐铁矿非常有帮助。

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