Ranking drivers of global carbon and energy fluxes over land

Gustau Camps-Valls; Martin Jung; Kazuhito Ichii; Dario Papale; Gianluca Tramontana; Paul Bodesheim; Christopher R Schwalm; Jakob Zscheischler; Miguel Mahecha; Markus Reichstein

doi:10.1109/IGARSS.2015.7326806

Ranking drivers of global carbon and energy fluxes over land

Gustau Camps-Valls, Martin Jung, Kazuhito Ichii, Dario Papale, Gianluca Tramontana, Paul Bodesheim, Christopher R Schwalm, Jakob Zscheischler, Miguel Mahecha, Markus Reichstein

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

8 Scopus citations

Abstract

The accurate estimation of carbon and heat fluxes at global scale is paramount for future policy decisions in the context of global climate change. This paper analyzes the relative relevance of potential remote sensing and meteorological drivers of global carbon and energy fluxes over land. The study is done in an indirect way via upscaling both Gross Primary Production (GPP) and latent energy (LE) using Gaussian Process regression (GPR). In summary, GPR is successfully compared to multivariate linear regression (RMSE gain of +4.17% in GPP and +7.63% in LE) and kernel ridge regression (+2.91% in GPP and +3.07% in LE). The best GP models are then studied in terms of explanatory power based on the analysis of the lengthscales of the anisotropic covariance function, sensitivity maps of the predictive mean, and the robustness to distortions in the input variables. It is concluded that GPP is predominantly mediated by several vegetation indices and land surface temperature (LST), while LE is mostly driven by LST, global radiation and vegetation indices.

Original language	English (US)
Title of host publication	International Geoscience and Remote Sensing Symposium (IGARSS)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4416-4419
Number of pages	4
Volume	2015-November
ISBN (Print)	9781479979295
DOIs	https://doi.org/10.1109/IGARSS.2015.7326806
State	Published - Nov 10 2015
Externally published	Yes
Event	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Milan, Italy Duration: Jul 26 2015 → Jul 31 2015

Other

Other	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
Country	Italy
City	Milan
Period	7/26/15 → 7/31/15

Keywords

carbon
energy
feature ranking
Gaussian process
global monitoring
GPP
regression

ASJC Scopus subject areas

Earth and Planetary Sciences(all)
Computer Science Applications

Access to Document

10.1109/IGARSS.2015.7326806

Fingerprint Dive into the research topics of 'Ranking drivers of global carbon and energy fluxes over land'. Together they form a unique fingerprint.

Cite this

Camps-Valls, G., Jung, M., Ichii, K., Papale, D., Tramontana, G., Bodesheim, P., Schwalm, C. R., Zscheischler, J., Mahecha, M., & Reichstein, M. (2015). Ranking drivers of global carbon and energy fluxes over land. In International Geoscience and Remote Sensing Symposium (IGARSS) (Vol. 2015-November, pp. 4416-4419). [7326806] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2015.7326806

Ranking drivers of global carbon and energy fluxes over land. / Camps-Valls, Gustau; Jung, Martin; Ichii, Kazuhito; Papale, Dario; Tramontana, Gianluca; Bodesheim, Paul; Schwalm, Christopher R; Zscheischler, Jakob; Mahecha, Miguel; Reichstein, Markus.

International Geoscience and Remote Sensing Symposium (IGARSS). Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015. p. 4416-4419 7326806.

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

Camps-Valls, G, Jung, M, Ichii, K, Papale, D, Tramontana, G, Bodesheim, P, Schwalm, CR, Zscheischler, J, Mahecha, M & Reichstein, M 2015, Ranking drivers of global carbon and energy fluxes over land. in International Geoscience and Remote Sensing Symposium (IGARSS). vol. 2015-November, 7326806, Institute of Electrical and Electronics Engineers Inc., pp. 4416-4419, IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015, Milan, Italy, 7/26/15. https://doi.org/10.1109/IGARSS.2015.7326806

Camps-Valls, Gustau ; Jung, Martin ; Ichii, Kazuhito ; Papale, Dario ; Tramontana, Gianluca ; Bodesheim, Paul ; Schwalm, Christopher R ; Zscheischler, Jakob ; Mahecha, Miguel ; Reichstein, Markus. / Ranking drivers of global carbon and energy fluxes over land. International Geoscience and Remote Sensing Symposium (IGARSS). Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015. pp. 4416-4419

@inproceedings{d1086f2098be4505ae75f73380073062,

title = "Ranking drivers of global carbon and energy fluxes over land",

abstract = "The accurate estimation of carbon and heat fluxes at global scale is paramount for future policy decisions in the context of global climate change. This paper analyzes the relative relevance of potential remote sensing and meteorological drivers of global carbon and energy fluxes over land. The study is done in an indirect way via upscaling both Gross Primary Production (GPP) and latent energy (LE) using Gaussian Process regression (GPR). In summary, GPR is successfully compared to multivariate linear regression (RMSE gain of +4.17% in GPP and +7.63% in LE) and kernel ridge regression (+2.91% in GPP and +3.07% in LE). The best GP models are then studied in terms of explanatory power based on the analysis of the lengthscales of the anisotropic covariance function, sensitivity maps of the predictive mean, and the robustness to distortions in the input variables. It is concluded that GPP is predominantly mediated by several vegetation indices and land surface temperature (LST), while LE is mostly driven by LST, global radiation and vegetation indices.",

keywords = "carbon, energy, feature ranking, Gaussian process, global monitoring, GPP, regression",

author = "Gustau Camps-Valls and Martin Jung and Kazuhito Ichii and Dario Papale and Gianluca Tramontana and Paul Bodesheim and Schwalm, {Christopher R} and Jakob Zscheischler and Miguel Mahecha and Markus Reichstein",

year = "2015",

month = nov,

day = "10",

doi = "10.1109/IGARSS.2015.7326806",

language = "English (US)",

isbn = "9781479979295",

volume = "2015-November",

pages = "4416--4419",

booktitle = "International Geoscience and Remote Sensing Symposium (IGARSS)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 ; Conference date: 26-07-2015 Through 31-07-2015",

}

TY - GEN

T1 - Ranking drivers of global carbon and energy fluxes over land

AU - Camps-Valls, Gustau

AU - Jung, Martin

AU - Ichii, Kazuhito

AU - Papale, Dario

AU - Tramontana, Gianluca

AU - Bodesheim, Paul

AU - Schwalm, Christopher R

AU - Zscheischler, Jakob

AU - Mahecha, Miguel

AU - Reichstein, Markus

PY - 2015/11/10

Y1 - 2015/11/10

N2 - The accurate estimation of carbon and heat fluxes at global scale is paramount for future policy decisions in the context of global climate change. This paper analyzes the relative relevance of potential remote sensing and meteorological drivers of global carbon and energy fluxes over land. The study is done in an indirect way via upscaling both Gross Primary Production (GPP) and latent energy (LE) using Gaussian Process regression (GPR). In summary, GPR is successfully compared to multivariate linear regression (RMSE gain of +4.17% in GPP and +7.63% in LE) and kernel ridge regression (+2.91% in GPP and +3.07% in LE). The best GP models are then studied in terms of explanatory power based on the analysis of the lengthscales of the anisotropic covariance function, sensitivity maps of the predictive mean, and the robustness to distortions in the input variables. It is concluded that GPP is predominantly mediated by several vegetation indices and land surface temperature (LST), while LE is mostly driven by LST, global radiation and vegetation indices.

AB - The accurate estimation of carbon and heat fluxes at global scale is paramount for future policy decisions in the context of global climate change. This paper analyzes the relative relevance of potential remote sensing and meteorological drivers of global carbon and energy fluxes over land. The study is done in an indirect way via upscaling both Gross Primary Production (GPP) and latent energy (LE) using Gaussian Process regression (GPR). In summary, GPR is successfully compared to multivariate linear regression (RMSE gain of +4.17% in GPP and +7.63% in LE) and kernel ridge regression (+2.91% in GPP and +3.07% in LE). The best GP models are then studied in terms of explanatory power based on the analysis of the lengthscales of the anisotropic covariance function, sensitivity maps of the predictive mean, and the robustness to distortions in the input variables. It is concluded that GPP is predominantly mediated by several vegetation indices and land surface temperature (LST), while LE is mostly driven by LST, global radiation and vegetation indices.

KW - carbon

KW - energy

KW - feature ranking

KW - Gaussian process

KW - global monitoring

KW - GPP

KW - regression

UR - http://www.scopus.com/inward/record.url?scp=84962486937&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84962486937&partnerID=8YFLogxK

U2 - 10.1109/IGARSS.2015.7326806

DO - 10.1109/IGARSS.2015.7326806

M3 - Conference contribution

AN - SCOPUS:84962486937

SN - 9781479979295

VL - 2015-November

SP - 4416

EP - 4419

BT - International Geoscience and Remote Sensing Symposium (IGARSS)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015

Y2 - 26 July 2015 through 31 July 2015

ER -

Ranking drivers of global carbon and energy fluxes over land

Abstract

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Cite this