Using Sentinel-2 and Stacking Regressors for Forest Height Estimation

João E. Pereira-Pires; João M. N. Silva; André Mora; José M. Fonseca

doi:10.1109/IGARSS52108.2023.10281979

Using Sentinel-2 and Stacking Regressors for Forest Height Estimation

João E. Pereira-Pires, João M. N. Silva, André Mora, José M. Fonseca

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

The climate change impacts can also be seen in the growing number of wildfires. Consequently, forest management and the updating of forest inventories become more important in the wildfires' avoidance. Measuring the Forest Height (FH) is an important activity in forests monitoring, since the FH can serve as a proxy variable of other parameters, as the aboveground biomass. Normally, FH is mapped through field campaigns or airborne laser scanning missions. However, these approaches do not offer the scalability needed and they are expensive. Therefore, multispectral data from Remote Sensing can be used for producing regional maps of FH. Here it is proposed a regionally calibrated Regression Methodology that uses multispectral data from Sentinel-2 and a Stacking Regressor for mapping the FH in Mediterranean forests. For a total of 17 regions across Portugal, Spain, and California, a R2 between 43.71% and 72.85% and a RMSE between 0.85m and 4.03m.

Original language	English
Title of host publication	IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
Subtitle of host publication	Proceedings
Place of Publication	Massachusetts
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1561-1564
Number of pages	4
ISBN (Electronic)	979-8-3503-2010-7
ISBN (Print)	979-8-3503-3174-5
DOIs	https://doi.org/10.1109/IGARSS52108.2023.10281979
Publication status	Published - 2023
Event	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, United States Duration: 16 Jul 2023 → 21 Jul 2023

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Volume	2023-July
ISSN (Print)	2153-6996
ISSN (Electronic)	2153-7003

Conference

Conference	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Country/Territory	United States
City	Pasadena
Period	16/07/23 → 21/07/23

Keywords

Climate Change
Forest Height
Mediterranean Forests
Multispectral
Sentinel-2
Stacking Regressor
Wildfires

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/IGARSS52108.2023.10281979

Cite this

Pereira-Pires, J. E., Silva, J. M. N., Mora, A., & Fonseca, J. M. (2023). Using Sentinel-2 and Stacking Regressors for Forest Height Estimation. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium: Proceedings (pp. 1561-1564). (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2023-July). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IGARSS52108.2023.10281979

Pereira-Pires, João E. ; Silva, João M. N. ; Mora, André et al. / Using Sentinel-2 and Stacking Regressors for Forest Height Estimation. IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium: Proceedings. Massachusetts : Institute of Electrical and Electronics Engineers (IEEE), 2023. pp. 1561-1564 (International Geoscience and Remote Sensing Symposium (IGARSS)).

@inproceedings{c13a2adefa5642e18d32f34782450a97,

title = "Using Sentinel-2 and Stacking Regressors for Forest Height Estimation",

abstract = "The climate change impacts can also be seen in the growing number of wildfires. Consequently, forest management and the updating of forest inventories become more important in the wildfires' avoidance. Measuring the Forest Height (FH) is an important activity in forests monitoring, since the FH can serve as a proxy variable of other parameters, as the aboveground biomass. Normally, FH is mapped through field campaigns or airborne laser scanning missions. However, these approaches do not offer the scalability needed and they are expensive. Therefore, multispectral data from Remote Sensing can be used for producing regional maps of FH. Here it is proposed a regionally calibrated Regression Methodology that uses multispectral data from Sentinel-2 and a Stacking Regressor for mapping the FH in Mediterranean forests. For a total of 17 regions across Portugal, Spain, and California, a R2 between 43.71% and 72.85% and a RMSE between 0.85m and 4.03m.",

keywords = "Climate Change, Forest Height, Mediterranean Forests, Multispectral, Sentinel-2, Stacking Regressor, Wildfires",

author = "Pereira-Pires, {Jo{\~a}o E.} and Silva, {Jo{\~a}o M. N.} and Andr{\'e} Mora and Fonseca, {Jos{\'e} M.}",

note = "Funding Information: Research Units, Centre of Technology and Systems – Uninova (UIDB/00066/2020) and Forest Research Centre (UIDB/00239/2020), and Jo{\~a}o Eduardo Pereira-Pires the Funda{\c c}{\~a}o para a Ci{\^e}ncia e Tecnologia for the Ph.D. Grant 2020.05015.BD. Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 ; Conference date: 16-07-2023 Through 21-07-2023",

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Pereira-Pires, JE, Silva, JMN, Mora, A & Fonseca, JM 2023, Using Sentinel-2 and Stacking Regressors for Forest Height Estimation. in IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium: Proceedings. International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2023-July, Institute of Electrical and Electronics Engineers (IEEE), Massachusetts, pp. 1561-1564, 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023, Pasadena, United States, 16/07/23. https://doi.org/10.1109/IGARSS52108.2023.10281979

Using Sentinel-2 and Stacking Regressors for Forest Height Estimation. / Pereira-Pires, João E.; Silva, João M. N.; Mora, André et al.
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium: Proceedings. Massachusetts: Institute of Electrical and Electronics Engineers (IEEE), 2023. p. 1561-1564 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2023-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Using Sentinel-2 and Stacking Regressors for Forest Height Estimation

AU - Pereira-Pires, João E.

AU - Silva, João M. N.

AU - Mora, André

AU - Fonseca, José M.

N1 - Funding Information: Research Units, Centre of Technology and Systems – Uninova (UIDB/00066/2020) and Forest Research Centre (UIDB/00239/2020), and João Eduardo Pereira-Pires the Fundação para a Ciência e Tecnologia for the Ph.D. Grant 2020.05015.BD. Publisher Copyright: © 2023 IEEE.

PY - 2023

Y1 - 2023

N2 - The climate change impacts can also be seen in the growing number of wildfires. Consequently, forest management and the updating of forest inventories become more important in the wildfires' avoidance. Measuring the Forest Height (FH) is an important activity in forests monitoring, since the FH can serve as a proxy variable of other parameters, as the aboveground biomass. Normally, FH is mapped through field campaigns or airborne laser scanning missions. However, these approaches do not offer the scalability needed and they are expensive. Therefore, multispectral data from Remote Sensing can be used for producing regional maps of FH. Here it is proposed a regionally calibrated Regression Methodology that uses multispectral data from Sentinel-2 and a Stacking Regressor for mapping the FH in Mediterranean forests. For a total of 17 regions across Portugal, Spain, and California, a R2 between 43.71% and 72.85% and a RMSE between 0.85m and 4.03m.

AB - The climate change impacts can also be seen in the growing number of wildfires. Consequently, forest management and the updating of forest inventories become more important in the wildfires' avoidance. Measuring the Forest Height (FH) is an important activity in forests monitoring, since the FH can serve as a proxy variable of other parameters, as the aboveground biomass. Normally, FH is mapped through field campaigns or airborne laser scanning missions. However, these approaches do not offer the scalability needed and they are expensive. Therefore, multispectral data from Remote Sensing can be used for producing regional maps of FH. Here it is proposed a regionally calibrated Regression Methodology that uses multispectral data from Sentinel-2 and a Stacking Regressor for mapping the FH in Mediterranean forests. For a total of 17 regions across Portugal, Spain, and California, a R2 between 43.71% and 72.85% and a RMSE between 0.85m and 4.03m.

KW - Climate Change

KW - Forest Height

KW - Mediterranean Forests

KW - Multispectral

KW - Sentinel-2

KW - Stacking Regressor

KW - Wildfires

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U2 - 10.1109/IGARSS52108.2023.10281979

DO - 10.1109/IGARSS52108.2023.10281979

M3 - Conference contribution

AN - SCOPUS:85178337318

SN - 979-8-3503-3174-5

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 1561

EP - 1564

BT - IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Massachusetts

T2 - 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023

Y2 - 16 July 2023 through 21 July 2023

ER -

Pereira-Pires JE, Silva JMN, Mora A , Fonseca JM. Using Sentinel-2 and Stacking Regressors for Forest Height Estimation. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium: Proceedings. Massachusetts: Institute of Electrical and Electronics Engineers (IEEE). 2023. p. 1561-1564. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS52108.2023.10281979

Using Sentinel-2 and Stacking Regressors for Forest Height Estimation

Abstract

Publication series

Conference

Keywords

UN SDGs

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