A first map of tropical Africa's above-ground biomass derived from satellite imagery

A. Baccini; N. Laporte; S. J. Goetz; M. Sun; H. Dong

doi:10.1088/1748-9326/3/4/045011

A first map of tropical Africa's above-ground biomass derived from satellite imagery

A. Baccini, N. Laporte, S. J. Goetz, M. Sun, H. Dong

Research output: Contribution to journal › Article › peer-review

335 Scopus citations

Abstract

Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5Mgha^-1 for a range of biomass between 0 and 454Mgha^-1. Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate that the model successfully captured the regional distribution of AGB. The results showed a strong positive correlation (R² = 0.90) between the GLAS height metrics and predicted AGB.

Original language	English (US)
Article number	045011
Journal	Environmental Research Letters
Volume	3
Issue number	4
DOIs	https://doi.org/10.1088/1748-9326/3/4/045011
State	Published - 2008
Externally published	Yes

Keywords

Biomass
Carbon
GLAS
Lidar
MODIS
REDD
Random Forest
Regression tree

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment
General Environmental Science
Public Health, Environmental and Occupational Health

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10.1088/1748-9326/3/4/045011

Cite this

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title = "A first map of tropical Africa's above-ground biomass derived from satellite imagery",

abstract = "Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5Mgha-1 for a range of biomass between 0 and 454Mgha-1. Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate that the model successfully captured the regional distribution of AGB. The results showed a strong positive correlation (R2 = 0.90) between the GLAS height metrics and predicted AGB.",

keywords = "Biomass, Carbon, GLAS, Lidar, MODIS, REDD, Random Forest, Regression tree",

author = "A. Baccini and N. Laporte and Goetz, {S. J.} and M. Sun and H. Dong",

year = "2008",

doi = "10.1088/1748-9326/3/4/045011",

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volume = "3",

journal = "Environmental Research Letters",

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T1 - A first map of tropical Africa's above-ground biomass derived from satellite imagery

AU - Baccini, A.

AU - Laporte, N.

AU - Goetz, S. J.

AU - Sun, M.

AU - Dong, H.

PY - 2008

Y1 - 2008

N2 - Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5Mgha-1 for a range of biomass between 0 and 454Mgha-1. Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate that the model successfully captured the regional distribution of AGB. The results showed a strong positive correlation (R2 = 0.90) between the GLAS height metrics and predicted AGB.

AB - Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5Mgha-1 for a range of biomass between 0 and 454Mgha-1. Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate that the model successfully captured the regional distribution of AGB. The results showed a strong positive correlation (R2 = 0.90) between the GLAS height metrics and predicted AGB.

KW - Biomass

KW - Carbon

KW - GLAS

KW - Lidar

KW - MODIS

KW - REDD

KW - Random Forest

KW - Regression tree

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DO - 10.1088/1748-9326/3/4/045011

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VL - 3

JO - Environmental Research Letters

JF - Environmental Research Letters

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M1 - 045011

ER -

A first map of tropical Africa's above-ground biomass derived from satellite imagery

Abstract

Keywords

ASJC Scopus subject areas

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