Assessment of Sentinel-2 Spectral Features to Estimate Forest Height with the New GEDI Data

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

doi:10.1007/978-3-030-78288-7_12

Assessment of Sentinel-2 Spectral Features to Estimate Forest Height with the New GEDI Data

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

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

14 Citations (Scopus)

Abstract

The unprecedent availability of vertical structure forest data provided by NASA Global Ecosystem Dynamics Investigation (GEDI), allows the validation of new methodologies based on other Remote Sensing (RS) sensors for monitoring forest parameters, such as Forest Height (FH). Previously, studies on FH estimation implied in-situ measurements or acquiring LiDAR data, which was limited and expensive. Opposing to the sampling nature of GEDI mission, Sentinel-2 optical products has a high revisiting frequency and a high spatial resolution favoring the implementation of forest monitoring methodologies. This work presents a study on the correlation and usability of linear and exponential regressions for estimating FH through Sentinel-2 imagery. It was also exploited the advantages of making estimations by study area, or by specific land cover types. Overall, a R² of 0.66 and a RMSE of 2.91 m were achieved, and in case of specifying the vegetation type were 0.83 and 2.40 m, respectively.

Original language	English
Title of host publication	Technological Innovation for Applied AI Systems: 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica, Portugal, July 7–9, 2021, Proceedings
Editors	Luis M. Camarinha-Matos, Pedro Ferreira, Guilherme Brito
Place of Publication	Cham
Publisher	Springer
Pages	123-131
Number of pages	9
ISBN (Electronic)	978-3-030-78288-7
ISBN (Print)	978-3-030-78287-0, 978-3-030-78290-0
DOIs	https://doi.org/10.1007/978-3-030-78288-7_12
Publication status	Published - 2021
Event	12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021 - Costa de Caparica and Online, Portugal Duration: 7 Jul 2021 → 9 Jul 2021

Publication series

Name	IFIP Advances in Information and Communication Technology
Publisher	Springer
Volume	626
ISSN (Print)	1868-4238
ISSN (Electronic)	1868-422X

Conference

Conference	12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021
Country/Territory	Portugal
City	Costa de Caparica and Online
Period	7/07/21 → 9/07/21

UN SDGs

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

SDG 15 Life on Land

Keywords

Forest height
GEDI
LiDAR
Parametric regressions
Remote sensing
Sentinel-2

Access to Document

10.1007/978-3-030-78288-7_12

Cite this

Pereira-Pires, J. E., Mora, A., Aubard, V., Silva, J. M. N., & Fonseca, J. M. (2021). Assessment of Sentinel-2 Spectral Features to Estimate Forest Height with the New GEDI Data. In L. M. Camarinha-Matos, P. Ferreira, & G. Brito (Eds.), Technological Innovation for Applied AI Systems: 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica, Portugal, July 7–9, 2021, Proceedings (pp. 123-131). (IFIP Advances in Information and Communication Technology; Vol. 626). Springer. https://doi.org/10.1007/978-3-030-78288-7_12

Pereira-Pires, João E. ; Mora, André ; Aubard, Valentine et al. / Assessment of Sentinel-2 Spectral Features to Estimate Forest Height with the New GEDI Data. Technological Innovation for Applied AI Systems: 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica, Portugal, July 7–9, 2021, Proceedings. editor / Luis M. Camarinha-Matos ; Pedro Ferreira ; Guilherme Brito. Cham : Springer, 2021. pp. 123-131 (IFIP Advances in Information and Communication Technology).

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title = "Assessment of Sentinel-2 Spectral Features to Estimate Forest Height with the New GEDI Data",

abstract = "The unprecedent availability of vertical structure forest data provided by NASA Global Ecosystem Dynamics Investigation (GEDI), allows the validation of new methodologies based on other Remote Sensing (RS) sensors for monitoring forest parameters, such as Forest Height (FH). Previously, studies on FH estimation implied in-situ measurements or acquiring LiDAR data, which was limited and expensive. Opposing to the sampling nature of GEDI mission, Sentinel-2 optical products has a high revisiting frequency and a high spatial resolution favoring the implementation of forest monitoring methodologies. This work presents a study on the correlation and usability of linear and exponential regressions for estimating FH through Sentinel-2 imagery. It was also exploited the advantages of making estimations by study area, or by specific land cover types. Overall, a R2 of 0.66 and a RMSE of 2.91 m were achieved, and in case of specifying the vegetation type were 0.83 and 2.40 m, respectively.",

keywords = "Forest height, GEDI, LiDAR, Parametric regressions, Remote sensing, Sentinel-2",

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

note = "Funding Information: info:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC\%2FCCI-COM\%2F30344\%2F2017/PT\# info:eu-repo/grantAgreement/FCT/3599-PPCDT/PCIF\%2FSSI\%2F0102\%2F2017/PT\# info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB\%2F00066\%2F2020/PT\# info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB\%2F00239\%2F2020/PT\# Jo?o Eduardo Pereira-Pires thanks the Funda??o para a Ci?ncia e Tecnologia (FCT), Portugal for the Ph.D. Grant 2020.05015.BD. Funding Information: info:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC\%2FCCI-COM\%2F30344\%2F2017/PT\# info:eu-repo/grantAgreement/FCT/3599-PPCDT/PCIF\%2FSSI\%2F0102\%2F2017/PT\# info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB\%2F00066\%2F2020/PT\# info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB\%2F00239\%2F2020/PT\# Publisher Copyright: {\textcopyright} 2021, IFIP International Federation for Information Processing.; 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021 ; Conference date: 07-07-2021 Through 09-07-2021",

year = "2021",

doi = "10.1007/978-3-030-78288-7\_12",

language = "English",

isbn = "978-3-030-78287-0",

series = "IFIP Advances in Information and Communication Technology",

publisher = "Springer",

pages = "123--131",

editor = "Camarinha-Matos, \{Luis M.\} and Pedro Ferreira and Guilherme Brito",

booktitle = "Technological Innovation for Applied AI Systems: 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica, Portugal, July 7–9, 2021, Proceedings",

address = "Netherlands",

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Pereira-Pires, JE , Mora, A, Aubard, V, Silva, JMN & Fonseca, JM 2021, Assessment of Sentinel-2 Spectral Features to Estimate Forest Height with the New GEDI Data. in LM Camarinha-Matos, P Ferreira & G Brito (eds), Technological Innovation for Applied AI Systems: 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica, Portugal, July 7–9, 2021, Proceedings. IFIP Advances in Information and Communication Technology, vol. 626, Springer, Cham, pp. 123-131, 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica and Online, Portugal, 7/07/21. https://doi.org/10.1007/978-3-030-78288-7_12

Assessment of Sentinel-2 Spectral Features to Estimate Forest Height with the New GEDI Data. / Pereira-Pires, João E.; Mora, André; Aubard, Valentine et al.
Technological Innovation for Applied AI Systems: 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica, Portugal, July 7–9, 2021, Proceedings. ed. / Luis M. Camarinha-Matos; Pedro Ferreira; Guilherme Brito. Cham: Springer, 2021. p. 123-131 (IFIP Advances in Information and Communication Technology; Vol. 626).

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

TY - GEN

T1 - Assessment of Sentinel-2 Spectral Features to Estimate Forest Height with the New GEDI Data

AU - Pereira-Pires, João E.

AU - Mora, André

AU - Aubard, Valentine

AU - Silva, João M. N.

AU - Fonseca, José M.

N1 - Funding Information: info:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FCCI-COM%2F30344%2F2017/PT# info:eu-repo/grantAgreement/FCT/3599-PPCDT/PCIF%2FSSI%2F0102%2F2017/PT# info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00066%2F2020/PT# info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00239%2F2020/PT# Jo?o Eduardo Pereira-Pires thanks the Funda??o para a Ci?ncia e Tecnologia (FCT), Portugal for the Ph.D. Grant 2020.05015.BD. Funding Information: info:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FCCI-COM%2F30344%2F2017/PT# info:eu-repo/grantAgreement/FCT/3599-PPCDT/PCIF%2FSSI%2F0102%2F2017/PT# info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00066%2F2020/PT# info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00239%2F2020/PT# Publisher Copyright: © 2021, IFIP International Federation for Information Processing.

PY - 2021

Y1 - 2021

N2 - The unprecedent availability of vertical structure forest data provided by NASA Global Ecosystem Dynamics Investigation (GEDI), allows the validation of new methodologies based on other Remote Sensing (RS) sensors for monitoring forest parameters, such as Forest Height (FH). Previously, studies on FH estimation implied in-situ measurements or acquiring LiDAR data, which was limited and expensive. Opposing to the sampling nature of GEDI mission, Sentinel-2 optical products has a high revisiting frequency and a high spatial resolution favoring the implementation of forest monitoring methodologies. This work presents a study on the correlation and usability of linear and exponential regressions for estimating FH through Sentinel-2 imagery. It was also exploited the advantages of making estimations by study area, or by specific land cover types. Overall, a R2 of 0.66 and a RMSE of 2.91 m were achieved, and in case of specifying the vegetation type were 0.83 and 2.40 m, respectively.

AB - The unprecedent availability of vertical structure forest data provided by NASA Global Ecosystem Dynamics Investigation (GEDI), allows the validation of new methodologies based on other Remote Sensing (RS) sensors for monitoring forest parameters, such as Forest Height (FH). Previously, studies on FH estimation implied in-situ measurements or acquiring LiDAR data, which was limited and expensive. Opposing to the sampling nature of GEDI mission, Sentinel-2 optical products has a high revisiting frequency and a high spatial resolution favoring the implementation of forest monitoring methodologies. This work presents a study on the correlation and usability of linear and exponential regressions for estimating FH through Sentinel-2 imagery. It was also exploited the advantages of making estimations by study area, or by specific land cover types. Overall, a R2 of 0.66 and a RMSE of 2.91 m were achieved, and in case of specifying the vegetation type were 0.83 and 2.40 m, respectively.

KW - Forest height

KW - GEDI

KW - LiDAR

KW - Parametric regressions

KW - Remote sensing

KW - Sentinel-2

UR - https://www.scopus.com/pages/publications/85111972571

U2 - 10.1007/978-3-030-78288-7_12

DO - 10.1007/978-3-030-78288-7_12

M3 - Conference contribution

AN - SCOPUS:85111972571

SN - 978-3-030-78287-0

SN - 978-3-030-78290-0

T3 - IFIP Advances in Information and Communication Technology

SP - 123

EP - 131

BT - Technological Innovation for Applied AI Systems: 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica, Portugal, July 7–9, 2021, Proceedings

A2 - Camarinha-Matos, Luis M.

A2 - Ferreira, Pedro

A2 - Brito, Guilherme

PB - Springer

CY - Cham

T2 - 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021

Y2 - 7 July 2021 through 9 July 2021

ER -

Pereira-Pires JE , Mora A, Aubard V, Silva JMN, Fonseca JM. Assessment of Sentinel-2 Spectral Features to Estimate Forest Height with the New GEDI Data. In Camarinha-Matos LM, Ferreira P, Brito G, editors, Technological Innovation for Applied AI Systems: 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica, Portugal, July 7–9, 2021, Proceedings. Cham: Springer. 2021. p. 123-131. (IFIP Advances in Information and Communication Technology). doi: 10.1007/978-3-030-78288-7_12

Assessment of Sentinel-2 Spectral Features to Estimate Forest Height with the New GEDI Data

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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