Comparison of LiDAR-based Models for True Leaf Area Index and Effective Leaf Area Index Estimation in Young Beech Forests
نویسندگان
چکیده
منابع مشابه
Usage of Lidar Data for Leaf Area Index Estimation
Leaf area index (LAI) can be measured either directly, using destructive methods, or indirectly using optical methods that are based on the tight relationship between LAI and canopy light transmittance. Third, innovative approach for LAI measuring is usage of remote sensing data, especially airborne laser scanning (ALS) data shows itself as a advisable source for purposes of LAI modelling in la...
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Leaf area index (LAI) is an important parameter of vegetation ecosystems, which can reflect the growth status of vegetation, and its inversion result has important significance on forestry system. The inversion values of forest LAI exists a certain deviation using traditional method. The airborne LiDAR technology adopts a new type of aerial earth observation method and makes it possible to esti...
متن کاملLeaf area index measurements
Leaf area index (LAI) is a key structural characteristic of forest ecosystems because of the role of green leaves in controlling many biological and physical processes in plant canopies. Accurate LA1 estimates are required in studies of ecophysiology, atmosphere-ecosystem interactions, and global change. The objective of this paper is to evaluate LA1 values obtained by several research teams us...
متن کاملLeaf Area Index in Earth System Models
The amount of leaves in a plant canopy (measured as leaf area index, LAI) modulates key land–atmosphere interactions, including the exchange of energy, moisture, carbon dioxide (CO 2), and other trace gases, and is therefore an essential variable in predicting terrestrial carbon, water, and energy fluxes. The latest generation of Earth system 5 models (ESMs) simulate LAI, as well as provide pro...
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Article history: Leaf area index (LAI) is a ke Received 20 February 2008 Received in revised form 17 June 2008 Accepted 3 July 2008
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ژورنال
عنوان ژورنال: Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
سال: 2020
ISSN: 1211-8516,1211-8516
DOI: 10.11118/actaun202068030559