Leaf area index mapping with optical methods and allometric models in SMEAR flux tower footprint at Järvselja, Estonia
Published Online: Jun 08, 2016
Page range: 85 - 99
Received: Jul 16, 2015
Accepted: Nov 11, 2015
DOI: https://doi.org/10.1515/fsmu-2015-0010
Keywords
© 2015 Marta Mõistus et al., published by De Gruyter Open
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Leaf area index (LAI) characterizes the amount of photosynthetically active tissue in plant canopies. LAI is one of the key factors determining ecosystem net primary production and gas and energy exchange between the canopy and the atmosphere. The aim of the present study was to test different methods for LAI and effective plant area index (PAIe) estimation in mixed hemiboreal forests in Järvselja SMEAR Estonia (Station for Measuring Ecosystem-Atmosphere Relations) flux tower footprint. We used digital hemispherical images from sample plots, forest management inventory data, allometric foliage mass models, airborne discrete-return recording laser scanner (ALS) data and multispectral satellite images. The free ware program HemiSpherical Project Manager (HSP) was used to calculate canopy gap fraction from digital hemispherical photographs taken in 25 sample plots. PAIe was calculated from the gap fraction for up-scaling based on ALS point cloud metrics. The all ALS pulse returns-based canopy transmission was found to be the most suitable lidar metric to estimate PAIe in Järvselja forests. The 95-percentile (