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iForest - Biogeosciences and Forestry

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Estimation of forest leaf area index using satellite multispectral and synthetic aperture radar data in Iran

Sasan Vafaei (1), Omid Fathizadeh (2), Nicola Puletti (3), Hadi Fadaei (4), Sabri Baqer Rasooli (5), Gaia Vaglio Laurin (3-6)   

iForest - Biogeosciences and Forestry, Volume 14, Issue 3, Pages 278-284 (2021)
doi: https://doi.org/10.3832/ifor3633-014
Published: May 29, 2021 - Copyright © 2021 SISEF

Research Articles


Different satellite datasets, including multispectral Sentinel 2 and synthetic aperture radar Sentinel 1 and ALOS2, were tested to estimate the Leaf Area Index (LAI) in the Zagros forests, Ilam province, in Iran. Field data were collected in 61 sample plots by hemispherical photographs, to train and validate the LAI estimation models. Different satellite data combinations were used as input in regression models built with the following algorithms: Multiple Linear Regression, Random Forests, and Partial Least Square Regression. The results indicate that Leaf Area Index can be best estimated using integrated ALOS2 and Sentinel 2 data; these inputs generated the model with higher accuracy (R2 = 0.84). The combination of a single band and a vegetation index from Sentinel 2 also led to successful results (R2 = 0.81). Lower accuracy was obtained when using only ALOS 2 (R2 = 0.72), but this dataset is helpful where cloud coverage affects optical data. Sentinel 1 data was not useful for LAI prediction. The optimal model was based on the traditional Multiple Linear Regression algorithm, using a preliminary input selection step to exclude multicollinearity effects. To avoid this step, the use of Partial Least Square Regression may be an alternative, as this algorithm was able to produce estimates similar to those obtained with the best model.

  Keywords


Leaf Area Index, Sentinel 2, ALOS 2, Forest Monitoring

Authors’ address

(1)
Sasan Vafaei
Faculty of Agriculture and Natural Resources, Lorestan University, Khorramabad, Lorestan (Iran)
(2)
Omid Fathizadeh 0000-0002-0696-7090
Department of Forestry, Ahar Faculty of Agriculture and Natural Resources, University of Tabriz (Iran)
(3)
Nicola Puletti 0000-0002-2142-959X
Gaia Vaglio Laurin 0000-0002-6728-3557
Research Centre for Forestry and Woodland, Council for Agricultural Research and Economics, Arezzo (Italy)
(4)
Hadi Fadaei
Department of Geography, Amin Police University, Tehran (Iran)
(5)
Sabri Baqer Rasooli 0000-0002-9292-2197
Department of Forestry, Faculty of Natural Resources, University of Guilan, Someh Sara (Iraq)
(6)
Gaia Vaglio Laurin 0000-0002-6728-3557
Department for Innovation in Biological, Agro-food and Forest systems, Tuscia University, Viterbo (Italy)

Corresponding author

 
Gaia Vaglio Laurin
gaia.vl@unitus.it

Citation

Vafaei S, Fathizadeh O, Puletti N, Fadaei H, Baqer Rasooli S, Vaglio Laurin G (2021). Estimation of forest leaf area index using satellite multispectral and synthetic aperture radar data in Iran. iForest 14: 278-284. - doi: 10.3832/ifor3633-014

Academic Editor

Agostino Ferrara

Paper history

Received: Aug 24, 2020
Accepted: Apr 08, 2021

First online: May 29, 2021
Publication Date: Jun 30, 2021
Publication Time: 1.70 months

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