Literature DB >> 31524858

Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands.

Jakub Černý1, Radek Pokorný2, Pavel Haninec3, Pavel Bednář4.   

Abstract

Accurate estimations of leaf area index (LAI), defined as half of the total leaf surface area per unit of horizontal ground surface area, are crucial for describing the vegetation structure in the fields of ecology, forestry, and agriculture. Therefore, procedures of three commercially used methods (litter traps, needle technique, and a plant canopy analyzer) for performing LAI estimation were presented step-by-step. Specific methodological approaches were compared, and their current advantages, controversies, challenges, and future perspectives were discussed in this protocol. Litter traps are usually deemed as the reference level. Both the needle technique and the plant canopy analyzer (e.g., LAI-2000) frequently underestimate LAI values in comparison with the reference. The needle technique is easy to use in deciduous stands where the litter completely decomposes each year (e.g., oak and beech stands). However, calibration based on litter traps or direct destructive methods is necessary. The plant canopy analyzer is a commonly used device for performing LAI estimation in ecology, forestry, and agriculture, but is subject to potential error due to foliage clumping and the contribution of woody elements in the field of view (FOV) of the sensor. Eliminating these potential error sources was discussed. The plant canopy analyzer is a very suitable device for performing LAI estimations at the high spatial level, observing a seasonal LAI dynamic, and for long-term monitoring of LAI.

Mesh:

Year:  2019        PMID: 31524858     DOI: 10.3791/59757

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  1 in total

1.  Estimating Leaf Area Index in Row Crops Using Wheel-Based and Airborne Discrete Return Light Detection and Ranging Data.

Authors:  Behrokh Nazeri; Melba M Crawford; Mitchell R Tuinstra
Journal:  Front Plant Sci       Date:  2021-11-29       Impact factor: 5.753

  1 in total

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