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Harvard Forest Symposium Abstract 2016

  • Title: Utilizing Terrestrial Lidar to classify a Hemlock Woolly Adelgid Infestation
  • Primary Author: Edward Saenz (University of Massachusetts - Boston)
  • Additional Authors: Daniel Genest (University of Massachusetts - Boston); David Orwig (Harvard Forest); Ian Paynter (UMass Boston); Francesco Peri (University of Massachusetts - Boston); Crystal Schaaf (Boston University); Alan Strahler (Boston University)
  • Abstract:

    Over the past 50 years, hemlock forest stands in the eastern United States have been under attack by the invasive Hemlock Woolly Adelgid. During the spring through autumn, this insect lays (cotton-like) eggs along the base of needles and limits vital nutrients to the hemlock tree. This infestation is the focus of numerous biological studies. This research utilizes terrestrial laser scanners, as an emerging technology, to characterize the spatial distribution of the HWA in eastern hemlock forests.



    Lidar (light detection and ranging) instruments are increasingly being used to provide information on the fine scale structural characteristics of forest ecosystems. Much of the lidar data collected and analyzed today are being utilized for object-level reconstruction. This means that multiple scans are acquired over a limited area of an ecosystem to generate a three-dimensional representation (from the multiple viewing angles) of the individual objects in that area (such as trees).This three-dimensional reconstruction is used to extract biophysical parameters and gain a better understanding of forest structure, condition, phenological change, and disturbance. Here however, we utilize a novel metaproperty classification model, to take advantage of the enormous amount of structural information that is captured directly by the three-dimensional lidar point clouds (prior to reconstruction).



    This metaproperty method is applied to large amounts of data acquired at Harvard Forest with the hyper-portable, rapid-scanning, University of Massachusetts Boston Compact Biomass Lidar (CBL) to assess the structural variations of hemlock forests undergoing a Woolly Adelgid infestation. By analyzing distributions of various laser pulse properties, meaningful information about the environment is captured. The integration of all of these emergent metaproperties can then be incorporated in a classification model to investigate the diagnostic features of the Hemlock Woolly Adelgid infestation at Harvard Forest.

  • Research Category: Biodiversity Studies