Intercomparison of Earth Observation Data and Methods for Forest Mapping in the Context of Forest Carbon Monitoring

Oleg Antropov; Jukka Miettinen; Tuomas Hame; Rauste Yrjo; Lauri Seitsonen; Ronald E. McRoberts; Maurizio Santoro; Oliver Cartus; Natalia Malaga Duran; Martin Herold; Matteo Pardini; Kostas Papathanassiou; Irena Hajnsek

doi:10.1109/IGARSS46834.2022.9884618

Intercomparison of Earth Observation Data and Methods for Forest Mapping in the Context of Forest Carbon Monitoring

Oleg Antropov, Jukka Miettinen, Tuomas Hame, Rauste Yrjo, Lauri Seitsonen, Ronald E. McRoberts, Maurizio Santoro, Oliver Cartus, Natalia Malaga Duran, Martin Herold, Matteo Pardini, Kostas Papathanassiou, Irena Hajnsek

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

2 Citations (Scopus)

Abstract

ESA Forest Carbon Monitoring project (FCM) is developing Earth Observation based, user-centric approaches for forest carbon monitoring. Forest carbon accounting based on forest inventory requires precise and timely estimation of forest variables at various spatial levels accompanied by verifiable uncertainty information. In this paper, we present the algorithm trade-off and selection approach and preliminary results of the algorithm intercomparison exercise in the FCM project. The studies were performed over 7 European test sites located in Finland, Ireland, Romania, Spain and Switzerland, and one tropical forest site in Peru. EO datasets were represented by Sentinel-1, Sentinel-2, TanDEM-X and ALOS-2 PALSAR-2 imagery. Examined approaches include popular parametric and SAR/InSAR scattering physics based approaches, and nonparametric and machine learning approaches such as k-NN, random forests, support vector regression.

Original language	English
Title of host publication	IGARSS 2022
Subtitle of host publication	2022 IEEE International Geoscience and Remote Sensing Symposium
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	5777-5780
ISBN (Electronic)	978-1-6654-2792-0, 978-1-6654-2791-3
ISBN (Print)	978-1-6654-2793-7
DOIs	https://doi.org/10.1109/IGARSS46834.2022.9884618
Publication status	Published - 28 Sept 2022
MoE publication type	A4 Article in a conference publication
Event	2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 - Kuala Lumpur, Malaysia Duration: 17 Jul 2022 → 22 Jul 2022

Publication series

Series	IEEE International Geoscience and Remote Sensing Symposium Proceedings
Volume	2022-July
ISSN	2153-6996

Conference

Conference	2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022
Country/Territory	Malaysia
City	Kuala Lumpur
Period	17/07/22 → 22/07/22

Keywords

ALOS-2 PALSAR-2
clustering
forest carbon
forest management
interferometry
Sentinel-1
Sentinel-2
synthetic aperture radar
TanDEM-X

UN SDGs

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

Access to Document

10.1109/IGARSS46834.2022.9884618

Cite this

Antropov, O., Miettinen, J., Hame, T., Yrjo, R., Seitsonen, L., McRoberts, R. E., Santoro, M., Cartus, O., Duran, N. M., Herold, M., Pardini, M., Papathanassiou, K., & Hajnsek, I. (2022). Intercomparison of Earth Observation Data and Methods for Forest Mapping in the Context of Forest Carbon Monitoring. In IGARSS 2022: 2022 IEEE International Geoscience and Remote Sensing Symposium (pp. 5777-5780). IEEE Institute of Electrical and Electronic Engineers. https://doi.org/10.1109/IGARSS46834.2022.9884618

Antropov, Oleg ; Miettinen, Jukka ; Hame, Tuomas et al. / Intercomparison of Earth Observation Data and Methods for Forest Mapping in the Context of Forest Carbon Monitoring. IGARSS 2022: 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE Institute of Electrical and Electronic Engineers, 2022. pp. 5777-5780 (IEEE International Geoscience and Remote Sensing Symposium Proceedings, Vol. 2022-July).

@inproceedings{d9650bbd4ad84c84adfdb62ef3c86d8a,

title = "Intercomparison of Earth Observation Data and Methods for Forest Mapping in the Context of Forest Carbon Monitoring",

abstract = "ESA Forest Carbon Monitoring project (FCM) is developing Earth Observation based, user-centric approaches for forest carbon monitoring. Forest carbon accounting based on forest inventory requires precise and timely estimation of forest variables at various spatial levels accompanied by verifiable uncertainty information. In this paper, we present the algorithm trade-off and selection approach and preliminary results of the algorithm intercomparison exercise in the FCM project. The studies were performed over 7 European test sites located in Finland, Ireland, Romania, Spain and Switzerland, and one tropical forest site in Peru. EO datasets were represented by Sentinel-1, Sentinel-2, TanDEM-X and ALOS-2 PALSAR-2 imagery. Examined approaches include popular parametric and SAR/InSAR scattering physics based approaches, and nonparametric and machine learning approaches such as k-NN, random forests, support vector regression.",

keywords = "ALOS-2 PALSAR-2, clustering, forest carbon, forest management, interferometry, Sentinel-1, Sentinel-2, synthetic aperture radar, TanDEM-X",

author = "Oleg Antropov and Jukka Miettinen and Tuomas Hame and Rauste Yrjo and Lauri Seitsonen and McRoberts, {Ronald E.} and Maurizio Santoro and Oliver Cartus and Duran, {Natalia Malaga} and Martin Herold and Matteo Pardini and Kostas Papathanassiou and Irena Hajnsek",

note = "Funding Information: The research was funded by ESA within Forest Carbon Monitoring project. Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 ; Conference date: 17-07-2022 Through 22-07-2022",

year = "2022",

month = sep,

day = "28",

doi = "10.1109/IGARSS46834.2022.9884618",

language = "English",

isbn = "978-1-6654-2793-7",

series = "IEEE International Geoscience and Remote Sensing Symposium Proceedings",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

pages = "5777--5780",

booktitle = "IGARSS 2022",

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}

Antropov, O , Miettinen, J, Hame, T, Yrjo, R, Seitsonen, L, McRoberts, RE, Santoro, M, Cartus, O, Duran, NM, Herold, M, Pardini, M, Papathanassiou, K & Hajnsek, I 2022, Intercomparison of Earth Observation Data and Methods for Forest Mapping in the Context of Forest Carbon Monitoring. in IGARSS 2022: 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE Institute of Electrical and Electronic Engineers, IEEE International Geoscience and Remote Sensing Symposium Proceedings, vol. 2022-July, pp. 5777-5780, 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022, Kuala Lumpur, Malaysia, 17/07/22. https://doi.org/10.1109/IGARSS46834.2022.9884618

Intercomparison of Earth Observation Data and Methods for Forest Mapping in the Context of Forest Carbon Monitoring. / Antropov, Oleg ; Miettinen, Jukka; Hame, Tuomas et al.
IGARSS 2022: 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE Institute of Electrical and Electronic Engineers, 2022. p. 5777-5780 (IEEE International Geoscience and Remote Sensing Symposium Proceedings, Vol. 2022-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Intercomparison of Earth Observation Data and Methods for Forest Mapping in the Context of Forest Carbon Monitoring

AU - Antropov, Oleg

AU - Miettinen, Jukka

AU - Hame, Tuomas

AU - Yrjo, Rauste

AU - Seitsonen, Lauri

AU - McRoberts, Ronald E.

AU - Santoro, Maurizio

AU - Cartus, Oliver

AU - Duran, Natalia Malaga

AU - Herold, Martin

AU - Pardini, Matteo

AU - Papathanassiou, Kostas

AU - Hajnsek, Irena

PY - 2022/9/28

Y1 - 2022/9/28

N2 - ESA Forest Carbon Monitoring project (FCM) is developing Earth Observation based, user-centric approaches for forest carbon monitoring. Forest carbon accounting based on forest inventory requires precise and timely estimation of forest variables at various spatial levels accompanied by verifiable uncertainty information. In this paper, we present the algorithm trade-off and selection approach and preliminary results of the algorithm intercomparison exercise in the FCM project. The studies were performed over 7 European test sites located in Finland, Ireland, Romania, Spain and Switzerland, and one tropical forest site in Peru. EO datasets were represented by Sentinel-1, Sentinel-2, TanDEM-X and ALOS-2 PALSAR-2 imagery. Examined approaches include popular parametric and SAR/InSAR scattering physics based approaches, and nonparametric and machine learning approaches such as k-NN, random forests, support vector regression.

AB - ESA Forest Carbon Monitoring project (FCM) is developing Earth Observation based, user-centric approaches for forest carbon monitoring. Forest carbon accounting based on forest inventory requires precise and timely estimation of forest variables at various spatial levels accompanied by verifiable uncertainty information. In this paper, we present the algorithm trade-off and selection approach and preliminary results of the algorithm intercomparison exercise in the FCM project. The studies were performed over 7 European test sites located in Finland, Ireland, Romania, Spain and Switzerland, and one tropical forest site in Peru. EO datasets were represented by Sentinel-1, Sentinel-2, TanDEM-X and ALOS-2 PALSAR-2 imagery. Examined approaches include popular parametric and SAR/InSAR scattering physics based approaches, and nonparametric and machine learning approaches such as k-NN, random forests, support vector regression.

KW - ALOS-2 PALSAR-2

KW - clustering

KW - forest carbon

KW - forest management

KW - interferometry

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KW - Sentinel-2

KW - synthetic aperture radar

KW - TanDEM-X

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DO - 10.1109/IGARSS46834.2022.9884618

M3 - Conference article in proceedings

AN - SCOPUS:85140400944

SN - 978-1-6654-2793-7

T3 - IEEE International Geoscience and Remote Sensing Symposium Proceedings

SP - 5777

EP - 5780

BT - IGARSS 2022

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022

Y2 - 17 July 2022 through 22 July 2022

ER -

Antropov O , Miettinen J, Hame T, Yrjo R, Seitsonen L, McRoberts RE et al. Intercomparison of Earth Observation Data and Methods for Forest Mapping in the Context of Forest Carbon Monitoring. In IGARSS 2022: 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE Institute of Electrical and Electronic Engineers. 2022. p. 5777-5780. (IEEE International Geoscience and Remote Sensing Symposium Proceedings, Vol. 2022-July). doi: 10.1109/IGARSS46834.2022.9884618

Intercomparison of Earth Observation Data and Methods for Forest Mapping in the Context of Forest Carbon Monitoring

Abstract

Publication series

Conference

Keywords

UN SDGs

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