Author/Authors :
Zhao، نويسنده , , Feng and Strahler، نويسنده , , Alan H. and Schaaf، نويسنده , , Crystal L. and Yao، نويسنده , , Tian and Yang، نويسنده , , Xiaoyuan and Wang، نويسنده , , Zhuosen and Schull، نويسنده , , Mitchell A. and Romلn-Colَn، نويسنده , , Miguel O. and Woodcock، نويسنده , , Curtis E. and Olofsson، نويسنده , , Pontus and Ni-Meister، نويسنده , , Wenge and Jupp، نويسنده , , David L.B. and Lovell، نويسنده , , Jenny L. and Culvenor، نويسنده , , Darius S. and Newnham، نويسنده , , Glenn J.، نويسنده ,
Abstract :
The Echidna Validation Instrument (EVI), a ground-based, near-infrared (1064 nm) scanning lidar, provides gap fraction measurements, element clumping index measurements, effective leaf area index (LAIe) 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 (R2 = 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.
Keywords :
EVI , Clumping index , Hemispherical photo , LIDAR