基于ASTER数据的富钾岩石遥感信息提取研究

发布时间：2018-02-25 03:30

本文关键词： 遥感富钾岩石氧化物含量光谱　出处：《中国地质大学(北京)》2015年硕士论文　论文类型：学位论文

【摘要】：我国非水溶性的钾盐资源非常丰富,以钾长石和伊利石为主的各种富钾岩石的分布非常广泛,几乎遍布全国。如果可以将这部分潜在资源高效加以利用,则可以在一定程度上对水溶性钾盐资源的匮乏进行相应的弥补。针对我国钾矿资源不足的现况、促进钾盐(肥)矿产资源的可持续开发与利用,本次研究将采用先进的遥感技术对河南卢氏县和嵩县等地非水溶性钾矿资源开展遥感地质调查与评价。研究目的是获取工作区的客观基础数据,形成综合分析和资源潜力评价报告。为高效、快速而精准地获得东秦岭北缘富钾侵入岩带遥感勘查数据提供一定的技术支撑。遥感在岩石信息的提取方面的应用,主要是依靠波段合成及图像增强及岩石矿物光谱特征来实现的。近些年来,研究定量反演岩石中氧化物含量来分析岩石类型从而来识别岩性是遥感岩石学定量反演中的一个方向。根据岩石化学分析结果可知,通过岩石中氧化物含量来识别富钾岩石是一种行之有效的方法。为了能够准确地对富钾岩石资源进行圈定,本文选择河南嵩县、卢氏县地区的富钾岩体作为研究对象,通过ASD便携式光谱仪对研究区内37个岩石样本进行了测定,基于遥感岩石学的岩石识别理论,利用基于图像统计分析和基于岩石光谱特征来对研究区富钾岩石进行岩性识别,并通过分析对比验证两种识别方法的效果。然后,通过对研究区采样点光谱的数据变换,基于多元逐步回归分析,利用重采样光谱与岩石氧化物分析结果,得到氧化物含量反演模型,并利用ENVI图像处理软件,以ASTER遥感数据为数据源,对研究区氧化物含量进行反演;通过IDL语言将CIPW(标准矿物计算)算法实现,得到研究区岩石主要标准矿物石英、钠长石、正长石、钙长石的质量分数。最后在算数运算和比值运算的基础上,建立富钾岩石的提取规则,对研究区富钾岩体进行提取。综合定性与定量识别结果,对研究区富钾岩体提取方法进行综合分析与评价。实验结果表明,基于地面实测光谱,分析利用岩石光谱曲线与岩石化学分析结果,建立富钾岩石信息提取模型,具有快速识别与圈定富钾岩石资源的潜力,该方法具有一定的推广价值。
[Abstract]:Our country is rich in insoluble potash salt resources, and all kinds of potash rich rocks, mainly potash feldspar and Illite, are widely distributed all over the country. To a certain extent, we can make up for the scarcity of water-soluble potash resources. In view of the present situation of the shortage of potash mineral resources in China, we can promote the sustainable development and utilization of potash (fertilizer) mineral resources. This study will use advanced remote sensing technology to carry out remote sensing geological survey and evaluation of insoluble potassium ore resources in Lushi County and Songxian County of Henan Province. The purpose of the study is to obtain the objective basic data of the working area. Forming comprehensive analysis and evaluation report of resource potential. To provide certain technical support for obtaining high efficiency, fast and accurate remote sensing exploration data of K-rich intrusive rock belt in the northern margin of East Qinling Mountains, and the application of remote sensing in the extraction of rock information, It is mainly achieved by band synthesis, image enhancement and spectral characteristics of rock minerals. In recent years, Quantitative inversion of oxide content in rocks to analyze rock types and identify lithology is one of the directions in quantitative inversion of remote sensing petrology. It is an effective method to identify the potash rich rock by the oxide content in the rock. In order to accurately delineate the potassium rich rock resources, this paper chooses the potash rich rock mass in Songxian and Lushi County of Henan Province as the research object. 37 rock samples in the study area were measured by ASD portable spectrometer. Based on the rock recognition theory of remote sensing petrology, the lithology identification of the potash rich rocks in the study area was carried out based on the statistical analysis of images and the characteristics of rock spectrum. The effect of the two recognition methods is verified by analysis and comparison. Then, through the data transformation of the sampling point spectrum in the study area, based on the multivariate stepwise regression analysis, the resampling spectrum and the rock oxide analysis results are used. The oxide content inversion model is obtained, and the ENVI image processing software is used to retrieve the oxide content in the study area using ASTER remote sensing data as data source, and the standard mineral calculation algorithm is implemented by IDL language. The mass fraction of quartz, albite, orthoclase and calcium feldspar in the study area is obtained. Finally, on the basis of arithmetic operation and ratio operation, the extraction rules of K-rich rocks are established. The method of extracting the potash rich rock mass in the study area is analyzed and evaluated by synthesizing the qualitative and quantitative identification results. The experimental results show that, based on the measured spectra on the ground, Based on the spectral curve of rock and the result of petrochemical analysis, the information extraction model of K-rich rock is established, which has the potential of quickly identifying and delineating the resources of K-rich rock, and this method has certain popularizing value.
【学位授予单位】：中国地质大学(北京)
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P619.211;P627

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