Relationship between LAI of Quercus persica and Pistacia atlantica with Field Spectroscopy
Author(s):
Abstract:
Leaf area index (LAI) is a key variable in primary production and carbon cycling in ecosystems. It is used as an important predictor to explain the processes of forest ecology, forest management, and remote sensing studies. Most of the remote sensing instruments such as LAI-2000 and Fisheye photography are based on three-dimensional space and they consider the geometry of the crown to estimate LAI. The aim of this study was to investigate the relationship between spectral behaviour of Quercus persica and Pistacia atlantica with two-dimensional and three-dimensional LAI. To estimate LAI, a box (0.5× 0.5× 0.5 meters) was placed in the four directions of the crown and all the leaves were harvested. In situ spectral measurements of leaves were done with ASD Fieldspec spectroradiometer. The results of partial least squares regression to model LAI form spectral data of Quercus persica showed maximum regression coefficient at visible and near infrared wavelengths for both LAI3D and LAI2D. The coefficient of determination (R2) between the measured and estimated LAI2D and LAI3D values for Quercus persica was 0.16 and 0.23 respectively, and for Pistacia atlantica was 0.15 and to 0.42, respectively. Generally, LAI3D showed better relationship with spectral reflectance for both species.
Language:
Persian
Published:
Iranian Journal of Applied Ecology, Volume:5 Issue:16, 2016
Pages:
55 - 67
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