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Two critical limitations for hyperspatial imagery are higher imagery variances and large data sizes. Although object-based analyses with a multi-scale framework for diverse object sizes are the solution, more data

Two critical limitations for hyperspatial imagery are higher imagery variances and large data sizes. Although object-based analyses with a multi-scale framework for diverse object sizes are the solution, more data sources and large amounts of testing at high costs are required. In this study, I used tree density segmentation as the key element of a three-level hierarchical vegetation framework for reducing those costs, and a three-step procedure was used to evaluate its effects.

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    Date Created
    • 2013
    Resource Type
  • Text
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    Note
    • Partial requirement for: M.A., Arizona State University, 2013
      Note type
      thesis
    • Includes bibliographical references (p. 30-38)
      Note type
      bibliography
    • Field of study: Geography

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    by Yan-ting Liau

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