Published May 2019 | Version v1
Journal article

A new method to estimate clumping index integrating gap fraction averaging with the analysis of gap size distribution

  • 1. Research Centre for Forestry and Wood, Arezzo (Italy)
  • 2. Research Centre for Agriculture and Environment, Rome (Italy)
  • 3. Fuzhou Univ., Ministry of Education, Spatial Information Research Center of Fujian Province, Key Laboratory of Data Mining and Information Sharing, Fuzhou (China)

Description

Estimates of clumping index (Ω) are required to improve the indirect estimation of leaf area index (L) from optical field-based instruments such as digital hemispherical photography (DHP). A widely used method allows estimation of Ω from DHP using simple gap fraction averaging formulas (LX). This method is simple and effective but has the disadvantage of being sensitive to the spatial scale (i.e., the azimuth segment size in DHP) used for averaging and canopy density. In this study, we propose a new method to estimate Ω (LXG) based on ordered weighted gap fraction averaging (OWA) formulas, which addresses the disadvantages of LX and also accounts for gap size distribution. The new method was tested in 11 broadleaved forest stands in Italy; Ω estimated from LXG was compared with other commonly used clumping correction methods (LX, CC, and CLX). Results showed that LXG yielded more accurate Ω estimates, which were also more correlated with the values obtained from the gap size distribution methods (CC and CLX) than Ω obtained from LX. Leaf area index estimates, adjusted by LXG, are only 5%–6% lower than direct measurements obtained from litter traps, while other commonly used clumping correction methods yielded more underestimation. (author)

Availability note (English)

Available from DOI: https://doi.org/10.1139/cjfr-2018-0213

Additional details

Identifiers

Publishing Information

Journal Title
Canadian Journal of Forest Research
Journal Volume
49
Journal Issue
5
Journal Page Range
p. 471-479
ISSN
0045-5067

INIS

Country of Publication
Canada
Country of Input or Organization
Canada
INIS RN
52111624
Subject category
S60: APPLIED LIFE SCIENCES;
Descriptors DEI
BIOLOGICAL MATERIALS; CANOPIES; FOREST LITTER; FORESTS; LEAVES
Descriptors DEC
BIOLOGICAL MATERIALS; MATERIALS

Optional Information

Notes
45 refs.