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Measuring gap fraction, element clumping index and LAI in Sierra Forest stands using a full-waveform ground-based lidar

  • Feng Zhao
  • , Alan H. Strahler
  • , Crystal L. Schaaf
  • , Tian Yao
  • , Xiaoyuan Yang
  • , Zhuosen Wang
  • , Mitchell A. Schull
  • , Miguel O. Román
  • , Curtis E. Woodcock
  • , Pontus Olofsson
  • , Wenge Ni-Meister
  • , David L.B. Jupp
  • , Jenny L. Lovell
  • , Darius S. Culvenor
  • , Glenn J. Newnham
  • Boston University
  • University of Maryland, College Park
  • University of Massachusetts Boston
  • United States Department of Agriculture
  • NASA Goddard Space Flight Center
  • City University of New York
  • CSIRO

Research output: Contribution to journal › Article › peer-review

Abstract

The Echidna Validation Instrument (EVI), a ground-based, near-infrared (1064nm) scanning lidar, provides gap fraction measurements, element clumping index measurements, effective leaf area index (LAI e) and leaf area index (LAI) measurements that are statistically similar to those from hemispherical photos. In this research, a new method integrating the range dimension is presented for retrieving element clumping index using a unique series of images of gap probability (Pgap) with range from EVI. From these images, we identified connected gap components and found the approximate physical, rather than angular, size of connected gap component. We conducted trials at 30 plots within six conifer stands of varying height and stocking densities in the Sierra National Forest, CA, in August 2008. The element clumping index measurements retrieved from EVI Pgap image series for the hinge angle region are highly consistent (R 2=0.866) with those of hemispherical photos. Furthermore, the information contained in connected gap component size profiles does account for the difference between our method and gap-size distribution theory based method, suggesting a new perspective to measure element clumping index with EVI Pgap image series and also a potential advantage of three dimensional Lidar data for element clumping index retrieval. Therefore further exploration is required for better characterization of clumped condition from EVI Pgap image series.

Original languageEnglish
Pages (from-to)73-79
Number of pages7
JournalRemote Sensing of Environment
Volume125
DOIs
StatePublished - Oct 2012

ASJC Scopus Subject Areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences

Keywords

  • Clumping index
  • EVI
  • Hemispherical photo
  • Lidar

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