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.

Highlights

  • The need for standardized and improved in-situ measurements of forest structural and compositional parameters is increasing

  • Our results indicate that the VEGNET In-situ Monitoring Lidar (IML) has great potential for rapid forest structural characterization and for ground validation of Plant Area Index (PAI)/Leaf Area Index (LAI) at a temporal frequency compatible with earth observation satellites

  • There are no previous studies on LAI or PAI for the Aspen Parkland forests located at our study site that could be directly compared with the results of this work

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Summary

Introduction

The need for standardized and improved in-situ measurements of forest structural and compositional parameters is increasing. The use of Leaf Area Index (LAI) as a measurement of forest structure and productivity has been shown to produce satisfactory results for this matter [1,2,3]. Leaf area index (LAI) is a dimensionless variable and was first defined as the total one-sided area of photosynthetic tissue per unit ground surface area [4]. It is a measure of the amount of foliage and can be estimated relatively rapidly with optical instruments. Leaf Area Index is influenced by a range of factors such as seasonal climate, species composition and management practices [1] as well as biotic agents such as disease and insect herbivores [6]

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