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

doi:10.3832/ifor3633-014

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

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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)

Faculty of Agriculture and Natural Resources, Lorestan University, Khorramabad, Lorestan (Iran)

(2)

0000-0002-0696-7090
Department of Forestry, Ahar Faculty of Agriculture and Natural Resources, University of Tabriz (Iran)

(3)

0000-0002-2142-959X
0000-0002-6728-3557
Research Centre for Forestry and Woodland, Council for Agricultural Research and Economics, Arezzo (Italy)

(4)

Department of Geography, Amin Police University, Tehran (Iran)

(5)

0000-0002-9292-2197
Department of Forestry, Faculty of Natural Resources, University of Guilan, Someh Sara (Iraq)

(6)

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

Open Access

This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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