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基于GIS空间分析进行多源信息成矿预测——以东天山土屋-延东铜矿床预测为例
引用本文:木合塔尔·扎日,郭瑞清,依玛木·塔伊尔.基于GIS空间分析进行多源信息成矿预测——以东天山土屋-延东铜矿床预测为例[J].新疆地质,2006,24(3):314-317.
作者姓名:木合塔尔·扎日  郭瑞清  依玛木·塔伊尔
作者单位:新疆大学资源与环境科学学院,新疆,乌鲁木齐,830046
基金项目:国家重点基础研究发展规划项目(2001CB409809),新疆大学博士启动基金,新疆维吾尔自治区重点学科(矿产普查与勘探)资助
摘    要:GIS空间分析在区域地质多源信息综合分析中,具有十分重要的作用.本文介绍了GIS空间分析的特征及应用于区域地质找矿的两种方法,即统计分析和叠加分析.参与多源信息成矿预测的信息图层,以东天山地区为例,选取找矿有利岩性、遥感断裂影响带(Buffer区)、地球化学异常、地质异常及已知矿(点)床的分布等6种控矿因素作为多源成矿预测的空间信息数据源.在此基础上,利用GIS的空间分析功能进行多源信息的综合分析,预测出3级成矿有利地区.

关 键 词:GIS  东天山  多源信息  空间分析  成矿预测
文章编号:1000-8845(2006)03-314-04
收稿时间:12 23 2005 12:00AM
修稿时间:03 9 2006 12:00AM

ORE-FORMING PREDICTION USING MULTIPLE-INFORMATION BASED GIS SPATIAL ANALYSIS——A CASE STUDY OF TUWU-YANDONG COPPER ORE-DEPOSIT IN EASTERN TIANSHAN
Muhtar ZARI,GUO Rui-qing,Yimamu TAYIR.ORE-FORMING PREDICTION USING MULTIPLE-INFORMATION BASED GIS SPATIAL ANALYSIS——A CASE STUDY OF TUWU-YANDONG COPPER ORE-DEPOSIT IN EASTERN TIANSHAN[J].Xinjiang Geology,2006,24(3):314-317.
Authors:Muhtar ZARI  GUO Rui-qing  Yimamu TAYIR
Institution:School of Resources and Environment Sciences, Xinjiang University, Urumqi, Xinjiang, 830046, China
Abstract:GIS spatial analysis plays an important role in regional ore-forming prediction using multi-informational synthetic analysis. The paper introduces the characteristics of GIS spatial analysis and two methods, statistical analysis and superimposed analysis, which are applied in mineral exploration. Integrating the information layer obtained by ore-forming prediction with the geological characteristics in the area of Eastern Tianshan, the author selected six key spatial data sources, which include favorable lithologic characters, remote sensed fracture influence belt, geochemistry abnormality, geological abnormality, and the distribution of known ore deposits. Based on the data sources, the author makes a synthetical analysis on the multiple information with the spatial analysis function of GIS and three ore-forming areas are predicted.
Keywords:GIS  the area of Eastern Tianshan  multiple-information  spatial analysis  ore-forming prediction
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