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Estimating Tropical Forest Structure Using a Terrestrial Lidar.

Michael Palace1,2, Franklin B Sullivan1, Mark Ducey3

  • 1Earth System Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, New Hampshire, United States of America.

Plos One
|April 29, 2016
PubMed
Summary
This summary is machine-generated.

Terrestrial lidar scanning effectively estimates tropical forest structure, providing valuable data on tree geometry and stand architecture. This technology aids in understanding complex forest ecosystems and biomass estimation.

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Area of Science:

  • Forestry
  • Ecology
  • Remote Sensing

Background:

  • Tropical forests are highly complex and poorly understood ecosystems.
  • Quantifying forest structure is crucial for understanding biome dynamics.
  • New technologies like lidar offer novel ways to measure forest properties.

Purpose of the Study:

  • To assess the effectiveness of terrestrial lidar scanner (TLS) systems for estimating tropical forest structure.
  • To develop statistical models relating TLS-derived metrics to field-measured forest attributes.
  • To explore the utility of lidar data for biomass estimation in tropical forests.

Main Methods:

  • Field measurements of biometric attributes were collected at 20 locations in La Selva, Costa Rica.
  • Terrestrial lidar scanner (TLS) data was collected from the center of each plot.
  • Relative vegetation profiles (RVPs) were created, and parameters like entropy, FFT, and plant area index were calculated.
  • Multiple linear regression models were used to establish relationships between lidar metrics and field data.

Main Results:

  • Strong statistical relationships were found between lidar metrics and field-measured forest structure, with mean crown depth showing the highest correlation (r² = 0.88).
  • Significant relationships were observed for basal area (r² = 0.75) and tree density (r² = 0.50).
  • Models for biomass estimation incorporated structural canopy variables and height metrics, indicating the comprehensive nature of lidar data.

Conclusions:

  • Vegetation profiles derived from TLS data provide valuable insights into tropical forest structure.
  • TLS is a promising technology for quantifying complex forest ecosystems.
  • Lidar-derived metrics can enhance biomass estimation models.