Visualizing tree crowns for forest managers: informatics tools enhance natural resource management

ABSTRACT

Ecologists aim to answer fundamental scientific questions regarding the natural world. Resource managers make practical decisions about natural resources, often with incomplete data. Our goal is to make research results more available to managers who decide which trees to leave when a forest stand is harvested. To that end, we work with Washington State resource managers and forest canopy researchers to: 1) determine what information technology might make new ecology research more applicable to managers, 2) articulate ecological values that dictate leave trees, 3) understand how those values are communicated. We have designed a catalog of tree crown structure with visualizations and metrics that help interpret complex research data for practitioners. This work extends prior NSF work to build research tools for ecologists, and addresses information technology issues of data presentation and data quality.

REFERENCES

• 1: Anderson, H-E, Reutebuch, S. E., and McGaughey, R. J. 2006. Active Remote Sensing, Ch. 3 in G. Shao and K. M. Reynolds, Computer Applications in Sustainable Forest Management. Springer, pp. 44--66.
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• 3: Judith Bayard Cushing , Nalini Nadkarni , Michael Finch , Anne Fiala , Emerson Murphy-Hill , Lois Delcambre , David Maier, Component-based end-user database design for ecologists, Journal of Intelligent Information Systems, v.29 n.1, p.7-24, August 2007 [doi>10.1007/s10844-006-0028-6]
• 4: Hallé, F., R. A. Oldeman and P. B. Tomlinson. 1978. Tropical trees and forests: an architectural analysis. Springer-Verlag, New York, NY. American Journal of Botany 71:958--969.
• 5: Van Pelt, R., and N. M. Nadkarni. 2004. Horizontal and vertical distribution of canopy structural elements of Pseudotsuga menziesii forests in the Pacific Northwest. Forest Science 50:326--3.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications

Keywords:
data integration, data quality, data visualization, decision support, ecoinformatics, forest canopy structure, human-computer interaction, knowledge representation, scaling