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首页> 外文学位 >Characterizing fire-related spatial patterns in fire-prone ecosystems using optical and microwave remote sensing (Arizona).
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Characterizing fire-related spatial patterns in fire-prone ecosystems using optical and microwave remote sensing (Arizona).

机译：使用光学和微波遥感（亚利桑那州）在易火生态系统中表征与火有关的空间格局。

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摘要

The use of active and passive remote sensing systems for relating forest spatial patterns to fire history was tested over one of the Arizona Sky Islands. Using Landsat Thematic Mapper (TM), Shuttle Imaging Radar (SIR-C), and data fusion I examined the relationship between landscape metrics and a range of fire history characteristics. Each data type (TM, SIR-C, and fused) was processed in the following manner: each band, channel, or derived feature was simplified to a thematic layer and landscape statistics were calculated for plots with known fire history. These landscape metrics were then correlated with fire history characteristics, including number of fire-free years in a given time period, mean fire-free interval, and time since fire. Results from all three case studies showed significant relationships between fire history and forest spatial patterns. Data fusion performed as well or better than Landsat TM alone, and better than SIR-C alone. These comparisons were based on number and strength of significant correlations each method achieved. The landscape metric that was most consistent and obtained the greatest number of significant correlations was Shannon's Diversity Index. Results also agreed with field-based research that has linked higher fire frequency to increased landscape diversity and patchiness. An additional finding was that the fused data seem to detect fire-related spatial patterns over a range of scales.
机译：在亚利桑那州的一个天空群岛上测试了使用主动和被动遥感系统将森林空间格局与火灾历史联系起来的情况。通过使用Landsat Thematic Mapper（TM），穿梭成像雷达（SIR-C）和数据融合，我检查了景观指标与一系列火灾历史特征之间的关系。每种数据类型（TM，SIR-C和融合）的处理方式如下：将每个波段，通道或派生的特征简化为一个主题层，并为具有已知火灾历史的地块计算景观统计数据。然后将这些景观指标与火灾历史特征相关联，包括给定时间段内无火年的数量，平均无火间隔和火灾发生后的时间。这三个案例研究的结果都表明，火灾历史与森林空间格局之间存在显着的关系。数据融合的性能与单独的Landsat TM相同或更好，并且优于单独的SIR-C。这些比较是基于每种方法实现的重要关联的数量和强度。香农的多样性指数是最一致且获得最大数量显着相关性的景观指标。研究结果也与基于野外的研究相一致，该研究将较高的火灾频率与景观多样性和斑块性增加联系在一起。另一个发现是，融合数据似乎可以在一定范围内检测与火灾相关的空间格局。

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  • 作者

    Henry, Mary Catherine.;

  • 作者单位

    The University of Arizona.;

  • 授予单位 The University of Arizona.;
  • 学科 Geography.; Physical Geography.; Remote Sensing.; Agriculture Forestry and Wildlife.
  • 学位 Ph.D.
  • 年度 2002
  • 页码 p.1947
  • 总页数 163
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自然地理学;
  • 关键词

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