Using VEGNET In-Situ monitoring LiDAR (IML) to capture dynamics of plant area index, structure and phenology in Aspen Parkland Forests in Alberta, Canada

Carlos Portillo-Quintero, Arturo Sanchez-Azofeifa, Darius Culvenor

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

The use of ceptometers and digital hemispherical photographs to estimate Plant Area Index (PAI) often include biases and errors from instrument positioning, orientation and data analysis. As an alternative to these methods, we used an In-Situ Monitoring LiDAR system that provides indirect measures of PAI and Plant Area Volume Density (PAVD) at a fixed angle, based on optimized principles and algorithms for PAI retrieval. The instrument was installed for 22 nights continuously from September 26 to October 17, 2013 during leaf-fall in an Aspen Parkland Forest. A total of 85 scans were performed (̃4 scans per night). PAI measured decreased from 1.27 to 0.67 during leaf-fall, which is consistent with values reported in the literature. PAVD profiles allowed differentiating the contribution of PAI per forest strata. Phenological changes were captured in four ways: number of hits, maximum cumulative and absolute PAI values, time series of PAVD profiles and PAI values per forest strata. We also found that VEGNET IML Canopy PAI and MODIS LAI values showed a similar decreasing trend and differed by 2%-15%. Our results indicate that the VEGNET IML has great potential for rapid forest structural characterization and for ground validation of PAI/LAI at a temporal frequency compatible with earth observation satellites.

Original languageEnglish
Pages (from-to)1053-1068
Number of pages16
JournalForests
Volume5
Issue number5
DOIs
StatePublished - 2014

Keywords

  • Ecosystem monitoring
  • Ground LiDAR
  • Hypertemporal
  • Leaf area index
  • Vertical profile

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