David Kao and Marc Kramer and Alison Luo and Jennifer Dungan and Alex Pang.
"Visualizing Distributions from Multi-Return Lidar Data to Understand Forest Structure".
InThe Cartographic Journal, vol. 42,no. 1, pp. 35--47, 2005.

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Abstract:

Spatially distributed probability density functions (pdfs) are becoming relevant to the Earth scientists and ecologists because of stochastic models and new sensors that provide numerous realizations or data points per unit area. One source of these data is from multi-return airborne lidar, a type of laser that records multiple returns for each pulse of light sent towards the ground. Data from multi-return lidar is a vital tool in helping us understand the structure of forest canopies over large extents. This paper suggests visualization tools to allow scientists to rapidly explore, interpret and discover characteristic distributions within the entire spatial field. The major contribu- tion ot this work is a paradigm shift which allows ecologists to think of and analyze their data in terms of full distributions, not just summary statistics. Information on the modality and shape of the distribution previously not possible. The tools allow the scientists to depart from traditional parametric statistical analyses and to associate multimodal distribution characteristics to forest structures. Examples are given using data from High Island, southeast Alaska.

Summary:

This paper applies techniques from 3 previous papers (Kao 2001, 2002, and Luo 2003) to LIDAR data. To process the data, a density estimator is used to approximate the PDF, peak hunting is preformed, and an operator is decided upon to allow distribution matching. To visualize the data, they use a map tool to show the number of modes for each distribution, an interactive data probe to show individual PDFs, user-guided mode exploration to detect modal characteristics across the data and matching of distributions. Queries can be formed by the user, and these query results are displayed as colormaps across the 2D surface, as boxed pixels of matching PDFs, as graphs of PDFs matching the query, or directly showing a restricted set of PDFs ontop of the 2D surface plot. Clustering can be used to find and show regions with similar distributions and characteristic distribution surfaces show the variations of PDFs that follow along some defined contour line. Such a system allows for general synoptic overviews of the data, as well as localized and detailed queries.

Taxonomy:

Data: 2D     Uncertainty: 1D    Visualization: 2D    Technique: LIDAR, Colormapping, Clustering, Characteristic Distribution Surfaces    

Bibtex:

@Article{        kao:2005:VDML,
  author = 	 {David Kao and Marc Kramer and Alison Luo and Jennifer Dungan and Alex Pang},
  title = 	 {Visualizing Distributions from Multi-Return Lidar
                  Data to Understand Forest Structure},
  journal = 	 {The Cartographic Journal},
  year = 	 {2005},
  volume = 	 {42},
  number = 	 {1},
  pages = 	 {35--47},
}

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References:


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