Empirical Prediction of Leaf Area Index (LAI) of Endangered Tree Species in Intact and Fragmented Indigenous Forests Ecosystems Using WorldView-2 Data and Two Robust Machine Learning Algorithms

Empirical Prediction of Leaf Area Index (LAI) of Endangered Tree Species in Intact and Fragmented Indigenous Forests Ecosystems Using WorldView-2 Data and Two Robust Machine Learning Algorithms

Leaf area index (LAI) is an important biophysical trait for forest ecosystem and ecological modeling, as it plays a key role for the forest productivity and structural characteristics. The ground-based methods like the handheld optical instruments for predicting LAI are subjective, pricy and time-co...

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Bibliographic Details
Main Authors: Galal Omer, Onisimo Mutanga, Elfatih M. Abdel-Rahman, Elhadi Adam
Format: Article
Language:English
Published: MDPI AG 2016-04-01
Series:Remote Sensing
Subjects:
leaf area index
tree species
indigenous forest
WorldView-2
support vector machines
artificial neural networks
Online Access:http://www.mdpi.com/2072-4292/8/4/324

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