遥感与地理信息系统在加纳东部Birim北部地区金矿潜力制图中的应用——GIS与遥感的金矿潜力制图

Clement Kwang, E. M. O. Jnr., A. Duker
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引用次数: 4

摘要

遥感和地理信息系统(地理信息系统)在矿物勘探方面发挥了积极作用,帮助在世界大部分地区,如西班牙、新斯科舍(加拿大)和埃及查明或发现新的金矿。不同的作者利用遥感和地理信息系统勘探矿藏。加纳东部地区的Birim北区是一个金矿化地区,但没有覆盖全区的黄金潜力图。这项研究工作的目的是通过利用遥感和地理信息系统技术,制作一张覆盖整个Birim北区的黄金潜力地图。对Birim North的Landsat Enhanced Thematic Mapper (ETM+)影像进行了5 ~ 7波段黏土矿物比和主成分分析。对结果进行进一步处理,得到Birim北区蚀变图,该蚀变图代表了与金矿化有关的蚀变岩。利用边缘检测方向滤波对同一区域的航磁图像进行增强,然后在屏幕上手工数字化,生成Birim北区的线形图。这些遥感结果与土壤地球化学数据和地球物理数据等其他地理空间数据集集成到GIS环境中。将证据弧权法作为空间数据集成模型应用于潜在金区预测。总共使用了250个已知金矿,其中180个作为训练样本,70个用于验证。研究结果表明,土壤地球化学资料、地球物理资料和地貌特征是预测新金矿的最佳指标。变化是最不具预测力的。金矿潜力图将研究区内497平方公里中的158平方公里(即32%)划定为金矿有利赋存区。黄金潜力图的成功率为88%(即预测有利金矿带中训练矿床或点的百分比),预测率为83%(即预测有利金矿带中验证矿床或点的百分比)。许多采矿社区和Newmont Ghana Gold有限矿区被发现与相对较高的后验概率相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Remote Sensing and Geographic Information Systems for Gold Potential Mapping in Birim North District of Eastern Region of Ghana -Gold Potential Mapping Using GIS and Remote Sensing
Remote Sensing and Geographic Information System (GIS) have played an active role in mineral exploration by helping in the identification or discovery of new gold deposits in most part of the world such as Spain, Nova Scotia (Canada) and Egypt. Different authors have used Remote Sensing and GIS in exploring minerals deposits. Birim North District of the Eastern Region of Ghana is one of the gold-mineralized districts but there is no gold potential map covering the whole district. This research work was aimed at producing a gold potential map covering the whole of Birim North District through the use of Remote Sensing and GIS technique. The Landsat Enhanced Thematic Mapper (ETM+) image of the Birim North was processed by applying the clay-mineral ratio (Band 5 to Band 7) and the principal component analysis. The result was further processed to obtain the alteration map of Birim North District which represented the altered rocks associated with goldmineralization. The Aeromagnetic image of the same area was enhanced by using the Edge Detection Directional Filter and later digitized manually on-screen to produce the lineament map of Birim North District. These results obtained from the Remote Sensing processes were integrated into GIS environment with other geospatial datasets such as the soil geochemical data and geophysical data. The Arcweight of evidence was used as the spatial data integration model in the prediction of the potential gold areas. A total of 250 known gold deposits was used, 180 were used as training samples and 70 were used for the validation. The results obtained from the research work indicated that the best predictors of the new gold deposits were the soil geochemical data, geophysical data and the lineament. The alteration was the least predictor. The gold potential map demarcates 158 km2 (i.e., 32%) of the total of 497 km2 as favourable for the occurences of the gold deposits within the study area. The gold potential map also has a success rate of 88% (i.e, the percentage of the training deposits or points in the predicted favourable gold deposits zones) and a prediction rate of 83% (i.e, the percentage of the validation deposits or points in the predicted favourable gold deposits areas). Many of the mining communities and Newmont Ghana Gold limited mine area were found in the areas associated with relative higher posterior probabilities.
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