...
首页> 外文期刊>Journal of the Indian Society of Remote Sensing >Application of Fractal Modelling for Cu Mineralisation Reconnaissance by ASTER Multispectral and Stream Sediment Data in Khoshname Area, NW Iran
【24h】

Application of Fractal Modelling for Cu Mineralisation Reconnaissance by ASTER Multispectral and Stream Sediment Data in Khoshname Area, NW Iran

机译:分形建模在ASTER多光谱和河流沉积物数据在铜矿化勘察中的应用

获取原文
获取原文并翻译 | 示例
           

摘要

This study identifies the major Cu anomalous zones including iron oxide, argillic and phyllic alterations and lithology as the most important extractable layers from the satellite images in Khoshname area located in the western part of Tarom - Hashtjin belt as a main metallogenic belt in the NW of Iran by utilization of concentration-area (C-A) fractal model based on 216 collected stream sediment and remote sensing data. The C-A fractal model for ASTER image log-log plots indicate three Cu geochemical populations for alterations which means that the high intensity for iron oxides, argillic and phyllic commences with 199, 177 and 158, respectively, in terms of pixels' values. With respect to the C-A log-log plot based on the stream sediment data, there are three Cu populations which indicate that Cu background and high intensive anomalies are < 38 ppm and > 56 ppm, respectively. The locations of high intensive Cu anomalies are situated in the SW parts of the area. To certify this, a correlation between remote sensing and geochemical data has been conducted to validate the C-A fractal model for Cu anomalies associated with alteration zones.
机译:这项研究从位于塔罗姆(Tarom)西部的Khoshname地区的卫星图像中识别出了主要的铜异常区,包括氧化铁,阿古拉性和叶性蚀变以及岩性,这是最重要的可提取层-哈什金带是西北部的主要成矿带。伊朗利用基于216个收集的河流沉积物和遥感数据的集中区(CA)分形模型。用于ASTER图像对数对数图的C-A分形模型指示了三个Cu地球化学种群的变化,这意味着就像素值而言,铁的高强度分别从199、177和158开始。关于基于河流沉积物数据的C-A对数-对数图,有3个Cu种群,表明Cu背景和高强度异常分别<38 ppm和> 56 ppm。高强度铜异常的位置位于该地区的西南部。为了证明这一点,已进行了遥感和地球化学数据之间的相关性,以验证与蚀变带相关的铜异常的C-A分形模型。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号