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Satellite image enhancements, lineament identification and quantitative comparison with fracture data, central New York State.

机译:纽约州中部的卫星图像增强,线条识别和与裂缝数据的定量比较。

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摘要

This report quantitatively tests the correlation between lineaments selected from three enhancements of Landsat and ASTER images to fractures that were measured in the Finger Lakes Region of New York for the purpose of determining the optimal image enhancement. I enhanced satellite images using various algorithms to accentuate the visibility of lineaments. Enhancements included a principal component analysis of ASTER data and a combination of ASTER and Landsat bands that have the least correlation. Lineaments were selected and then I utilized the weights of evidence method to determine whether fractures and lineaments of the same trend are coincident.; Results from this study show that the Landsat and ASTER composite image is optimal for selecting lineaments that are related to strike parallel fractures, whereas the ASTER principal component analysis is optimal for selecting lineaments that are related to cross strike fractures in the study area. Use of a filter that constrained the lineaments to greater than 500m in length produced better correlation but was not necessary for selecting lineaments related to fractures. Of all the processing techniques considered, the Landsat and ASTER composite image with a lineament length filter has the most positive correlation.*; *This dissertation is a compound document (contains both a paper copy and a CD as part of the dissertation). The CD requires the following system requirements: Adobe Acrobat.
机译:本报告定量测试了从Landsat和ASTER图像的三种增强中选择的线条与在纽约手指湖地区测量的裂缝之间的相关性,以确定最佳图像增强。我使用各种算法增强了卫星图像,以突出线条的可见性。增强功能包括对ASTER数据的主成分分析以及相关性最小的ASTER和Landsat波段组合。选择线条,然后使用证据权重法确定同一趋势的裂缝和线条是否重合。这项研究的结果表明,Landsat和ASTER合成图像最适合于选择与走向平行裂缝有关的线型,而ASTER主成分分析最适合于选择与研究区域中与走向走向裂缝有关的线型。使用将线段约束到长度大于500m的过滤器可以产生更好的相关性,但是对于选择与裂缝相关的线段不是必需的。在考虑的所有处理技术中,带有线长过滤器的Landsat和ASTER合成图像具有最大的正相关性。 *本论文是复合文件(作为论文的一部分,包含纸质副本和CD)。该CD需要满足以下系统要求:Adobe Acrobat。

著录项

  • 作者

    Cruz, Cheri Ann.;

  • 作者单位

    State University of New York at Buffalo.;

  • 授予单位 State University of New York at Buffalo.;
  • 学科 Geology.; Remote Sensing.
  • 学位 M.S.
  • 年度 2005
  • 页码 138 p.
  • 总页数 138
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 地质学;遥感技术;
  • 关键词

  • 入库时间 2022-08-17 11:42:55

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