(1. 中南大學(xué) 有色金屬成礦預(yù)測(cè)教育部重點(diǎn)實(shí)驗(yàn)室，長沙 410083；
2. 中南大學(xué) 地球科學(xué)與信息物理學(xué)院，長沙 410083)
摘 要: 基于GIS技術(shù)，對(duì)銅陵天馬山及其外圍約100 km2區(qū)域進(jìn)行數(shù)字礦床空間信息找礦預(yù)測(cè)模型的研究。通過工作區(qū)信息統(tǒng)計(jì)單元的劃分、預(yù)測(cè)區(qū)地質(zhì)信息(包括構(gòu)造、地層、巖漿巖、地表礦化以及遙感混合蝕變信息等)變量的確定以及編碼和賦值，采用特征分析法確定空間網(wǎng)格單元成礦異常有利度模型，根據(jù)預(yù)測(cè)單元計(jì)算結(jié)果，結(jié)合地質(zhì)分析，圈定找礦靶區(qū)14處。
關(guān)鍵字: 找礦預(yù)測(cè)；信息統(tǒng)計(jì)；特征分析；天馬山及其外圍地區(qū)；銅陵
Tianmashan and its periphery area, Tongling
（1. Key Laboratory of Metallogenic Prediction of Nonferrous Metals, Ministry of Education,
Central South University, Changsha 410083, China;
2. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China）
Abstract:Based on geographic information system (GIS), the model of space information related with ore prediction in Tianmashan and its periphery area, Tongling of 100 km2 was studied. According to the division of information statistics units, the determination of geological information variables which consist of structure, strata, magmatic rocks, mineralization and remote sensing alteration information etc., along with coding and assignment, the method of signature analysis was adopted to ensure the mineralized anomalies favorability model of the space information grid units. Combined with geological analysis, 14 prospecting targets were delineated.
Key words: ore prediction; information statistics; signature analysis; Tianmashan and its periphery area; Tongling
