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首页> 外文学位 >Using Landsat TM Imagery to Monitor Vegetation Change Following Flow Restoration to the Lower Owens River, California.
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Using Landsat TM Imagery to Monitor Vegetation Change Following Flow Restoration to the Lower Owens River, California.

机译：使用Landsat TM影像监测加利福尼亚州欧文斯河下游的流量恢复后的植被变化。

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摘要

Rehabilitating river corridors to restore valuable riparian habitat consumes significant resources from both governments and private companies. Given these considerable expenditures, it is important to monitor the progress of such projects. This study evaluated the utility of using Landsat Thematic Mapper remotely-sensed data from 2002 and 2009 to monitor vegetation change induced by instream flow restoration to the Lower Owens River in central California. This study compared the results of an unsupervised classification with an NDVI threshold classification to appraise the resources required and effectiveness of each analysis method. The results were inspected by creating standard remote sensing accuracy error matrices and by correlating landscape pattern metrics with bird indicator species. Both sets of classified maps show a noticeable increase in riparian vegetation in the study area following flow restoration in 2006, indicating an improvement of the quality of bird habitat. The study concluded that analyzing vegetation change using the unsupervised classification technique required more effort, expert knowledge, and supplementary data than using the NDVI threshold method. If these prerequisites are met, the output from the unsupervised classification process produces a more precise map of land cover change than the NDVI threshold method. However, if an analyst is lacking either resources or ground verification data, the NDVI threshold technique is capable of providing a generalized, but still valid evaluation of vegetation change. This conclusion is supported by higher correlations between indicator bird species under the unsupervised classification method than were found with the NDVI threshold method.
机译：修复河流走廊以恢复宝贵的河岸生境会消耗政府和私人公司的大量资源。考虑到这些巨大的支出，监视此类项目的进度非常重要。这项研究评估了使用2002年至2009年的Landsat Thematic Mapper遥感数据监测加利福尼亚中部下欧文斯河的河道内流量恢复引起的植被变化的实用性。这项研究将无监督分类的结果与NDVI阈值分类进行了比较，以评估每种分析方法所需的资源和有效性。通过创建标准的遥感精度误差矩阵并将景观格局指标与鸟类指示剂物种相关联来检查结果。两组分类地图均显示，在2006年流量恢复之后，研究区域的河岸植被显着增加，表明鸟类栖息地的质量得到了改善。研究得出的结论是，与使用NDVI阈值方法相比，使用无监督分类技术分析植被变化需要更多的精力，专业知识和补充数据。如果满足了这些先决条件，则无监督分类过程的输出将比NDVI阈值方法产生更精确的土地覆盖变化图。但是，如果分析人员缺少资源或地面验证数据，则NDVI阈值技术能够提供对植被变化的一般化但仍然有效的评估。与无NDVI阈值方法相比，在无监督分类方法下指示鸟种类之间的相关性更高，支持了该结论。

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  • 作者

    Bross, Lesley Crandell.;

  • 作者单位

    Portland State University.;

  • 授予单位 Portland State University.;
  • 学科 Remote sensing.;Geographic information science and geodesy.
  • 学位 M.S.
  • 年度 2015
  • 页码 126 p.
  • 总页数 126
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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