Acta Univ. Agric. Silvic. Mendelianae Brun. 2020, 68, 559-566

https://doi.org/10.11118/actaun202068030559
Published online 2020-07-01

Comparison of LiDAR-based Models for True Leaf Area Index and Effective Leaf Area Index Estimation in Young Beech Forests

Zdeněk Patočka1, Kateřina Novosadová2, Pavel Haninec3, Radek Pokorný2, Tomáš Mikita1, Martin Klimánek1

1Department of Forest Management and Applied Geoinformatics, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic
2Department of Silviculture, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic
3Department of Forest Botany, Dendrology and Geobiocoenology, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic

Received March 9, 2020
Accepted May 31, 2020

The leaf area index (LAI) is one of the most common leaf area and canopy structure quantifiers. Direct LAI measurement and determination of canopy characteristics in larger areas is unrealistic due to the large number of measurements required to create the distribution model. This study compares the regression models for the ALS-based calculation of LAI, where the effective leaf area index (eLAI) determined by optical methods and the LAI determined by the direct destructive method and developed by allometric equations were used as response variables. LiDAR metrics and the laser penetration index (LPI) were used as predictor variables. The regression models of LPI and eLAI dependency and the LiDAR metrics and eLAI dependency showed coefficients of determination (R2) of 0.75 and 0.92, respectively; the advantage of using LiDAR metrics for more accurate modelling is demonstrated. The model for true LAI estimation reached a R2 of 0.88.

Funding

This work was supported by the Internal Grant Agency of Faculty of Forestry and Wood Technology, Mendel University in Brno. The paper was worked out as a part of research project reg. No. LDF_VP_2016015, “Use of point clouds derived by unmanned aerial vehicle imagery and airborne laser scanning for leaf area index estimation”. The paper publishing was also financed by the National Agency of Agricultural Research in the Czech Republic, research project reg. No. QK1810415, “Influence of forest stands species composition and structure on the microclimate and landscape hydrology”.

References

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