The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Using satellite radar backscatter to predict above‐ground woody biomass: A consistent relationship across four different African landscapes
Open accessAbstract
Regional‐scale above‐ground biomass (AGB) estimates of tropical savannas and woodlands are highly uncertain, despite their global importance for ecosystems services and as carbon stores. In response, we collated field inventory data from 253 plots at four study sites in Cameroon, Uganda and Mozambique, and examined the relationships between field‐measured AGB and cross‐polarized radar backscatter values derived from ALOS PALSAR, an L‐band satellite sensor. The relationships were highly significant, similar among sites, and displayed high prediction accuracies up to 150 Mg ha−1 (±∼20%). AGB predictions for any given site obtained using equations derived from data from only the other three sites generated only small increases in error. The results suggest that a widely applicable general relationship exists between AGB and L‐band backscatter for lower‐biomass tropical woody vegetation. This relationship allows regional‐scale AGB estimation, required for example by planned REDD (Reducing Emissions from Deforestation and Degradation) schemes.
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Tree allometry and improved estimation of carbon stocks and balance in tropical forests
Chave, J., Andalo, C., Brown, S., Cairns, M. A., Chambers, J. Q., Eamus, D., Fölster, H., Fromard, F., Higuchi, N., Kira, T., et al. (2005) · Oecologia · doi:10.1007/s00442-005-0100-x · Cited by 3,533
Towards a worldwide wood economics spectrum
Chave, J., Coomes, D., Jansen, S., Lewis, S. L., Swenson, N. G., & Zanne, A. E. (2009) · Ecology Letters · doi:10.1111/j.1461-0248.2009.01285.x · Cited by 3,203
Self-citationThe potential and challenge of remote sensing‐based biomass estimation
Lu, D. (2006) · International Journal of Remote Sensing · doi:10.1080/01431160500486732 · Cited by 1,213
Error propagation and scaling for tropical forest biomass estimates
Chave, J., Condit, R., Aguilar, S., Hernandez, A., Lao, S., & Perez, R. (2004) · Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences · doi:10.1098/rstb.2003.1425 · Cited by 863
A new land‐cover map of Africa for the year 2000
Mayaux, P., Bartholomé, E., Fritz, S., & Belward, A. (2004) · Journal of Biogeography · doi:10.1111/j.1365-2699.2004.01073.x · Cited by 523
Carbon sequestration and biodiversity of re-growing miombo woodlands in Mozambique
Williams, M., Ryan, C. M., Rees, R. M., Sambane, E., Fernando, J., & Grace, J. (2008) · Forest Ecology and Management · doi:10.1016/j.foreco.2007.07.033 · Cited by 256
Self-citationEstimating biomass and biomass change of tropical forests
Brown, S. (1997) · Cited by 242
Mitchard, E. T. A., Saatchi, S. S., Lewis, S. L., Feldpausch, T. R., Woodhouse, I. H., Sonké, B., Rowland, C., & Meir, P. (2011) · Remote Sensing of Environment · doi:10.1016/j.rse.2010.02.022 · Cited by 229
Self-citationSaatchi, S. S., & Moghaddam, M. (2000) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/36.841999 · Cited by 156
Self-citationApplying the conservativeness principle to REDD to deal with the uncertainties of the estimates
Grassi, G., Monni, S., Federici, S., Achard, F., & Mollicone, D. (2008) · Environmental Research Letters · doi:10.1088/1748-9326/3/3/035005 · Cited by 143
Cited by
Duncanson, L., Kellner, J. R., Armston, J., Dubayah, R., Minor, D. M., Hancock, S., Healey, S. P., Patterson, P. L., Saarela, S., Marselis, S., et al. (2022) · Remote Sensing of Environment · doi:10.1016/j.rse.2021.112845 · Cited by 495
Self-citationQuantifying Forest Biomass Carbon Stocks From Space
Rodríguez-Veiga, P., Wheeler, J., Louis, V., Tansey, K., & Balzter, H. (2017) · Current Forestry Reports · doi:10.1007/s40725-017-0052-5 · Cited by 177
Metadata
- Authors
- Mitchard, E. T. A., Saatchi, S. S., Woodhouse, I. H., Nangendo, G., Ribeiro, N. S., Williams, M., Ryan, C. M., Lewis, S. L., Feldpausch, T. R., & Meir, P.
- Venue
- Geophysical Research Letters
- Publisher
- American Geophysical Union (AGU)
- Published
- 2009-12
- Volume
- 36
- Issue
- 23
- ISSN
- 0094-8276 (ISSN-L)
- 1944-8007
- OpenAlex
- W2112144785
- Cited by
- 285
- References
- 15
- FWCI
- 30.36
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Mitchard, E. T. A., Saatchi, S. S., Woodhouse, I. H., Nangendo, G., Ribeiro, N. S., Williams, M., Ryan, C. M., Lewis, S. L., Feldpausch, T. R., & Meir, P. (2009). Using satellite radar backscatter to predict above‐ground woody biomass: A consistent relationship across four different African landscapes. Geophysical Research Letters. https://doi.org/10.1029/2009gl040692
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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