This study illustrates the application of a geometric average integration of aeromagnetic, radiometric and satellite imagery data over a region prone to Cu‐bearing mineralization at Chahargonbad area in Kerman province of Iran. Processing aeromagnetic, radiometric and Advanced Spaceborne Thermal Emission and Reflection Radiometer satellite data can provide exploratory insights about favourable zones in association with porphyry‐type ore occurrences, which can be synthesized through a combination of knowledge‐ and data‐driven approaches as a geometric average and be represented in a mineral prospectivity map. The existence of known deposits in a prospect region can facilitate the investigation of significant exploratory footprints extracted from airborne data by calculating each indicator layer's weight by plotting a prediction–area curve accompanied by a concentration–area fractal curve. Among various indicators, the most important ones are determined based on derived weights from the prediction–area plots to be synthesized in a single Cu favorability map. To fulfil this aim, indicator layers from airborne geophysics (magmatic bodies, magnetic lineaments and potassium radiometry) and remote‐sensing data (alterations such as argillic, phyllic, propylitic and iron oxide along with geological lineaments) were prepared and evaluated using the known porphyry Cu mineralization by the simultaneous plot of the concentration–area fractal model and the prediction–area curve to attain the ore prediction rate and the relevant occupied area of each map for weight assignment of indicators. The geometric average prospectivity model was applied to synthesize the leading indicators, and the result was compared with a multi‐class index overlay map. This study's significance lies in improvement of the performance of the mineral prospectivity/potential mapping after running a geometric average by a higher ore prediction rate of 79%, which has occupied 21% of the area as potential zones for further mining investigations.

中文翻译：

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整合机载地球物理学和卫星图像数据，用于斑岩铜矿系统中的勘探目标：伊朗查哈贡巴德区

这项研究说明了在伊朗克尔曼省的查哈贡巴德地区，在倾向于含铜矿化的地区，对航空，辐射和卫星影像数据进行几何平均积分的应用。处理航磁，辐射测量以及先进的星载热发射和反射辐射计卫星数据可以提供与斑岩型矿石发生有关的有利区域的探索性见解，可以通过结合知识和数据驱动方法将其综合为几何平均值并进行综合。在矿产远景图中表示。潜在地区中已知矿床的存在可以通过计算每个指标层的“密度”来促进对从机载数据中提取的重要勘探足迹的研究。通过绘制预测-面积曲线与浓度-面积分形曲线的关系来确定重量。在各种指标中，最重要的指标是根据从预测区域图得出的权重确定的，这些权重将在单个Cu有利性图中进行合成。为了实现这一目标，利用已知的斑岩，准备并评估了航空地球物理（岩体，磁性线和钾辐射）的指示层和遥感数据（如泥质，叶栅，次丙基和氧化铁等变化以及地质线）。通过浓度-面积分形模型和预测-面积曲线的同时绘图获得铜矿化作用，以获得矿石的预测速率和各图的权重分配的每个图的相关占用面积。应用几何平均预期模型合成前导指标，并将结果与​​多类索引覆盖图进行比较。这项研究的重要意义在于，在以几何平均数运行后，以79％的较高矿石预测率改善了矿产前景/潜力测绘的性能，该矿石预测面积已占该地区21％的面积作为进一步采矿研究的潜在区。