Articles | Volume 13, issue 2
https://doi.org/10.5194/bg-13-609-2016
https://doi.org/10.5194/bg-13-609-2016
Research article
 | 
02 Feb 2016
Research article |  | 02 Feb 2016

Annual South American forest loss estimates based on passive microwave remote sensing (1990–2010)

M. J. E. van Marle, G. R. van der Werf, R. A. M. de Jeu, and Y. Y. Liu

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Achard, F., Beuchle, R., Mayaux, P., Stibig, H.-J., Bodart, C., Brink, A., Carboni, S., Desclée, B., Donnay, F., Eva, H. D., Lupi, A., Raši, R., Seliger, R. and Simonetti, D.: Determination of tropical deforestation rates and related carbon losses from 1990 to 2010, Glob. Change Biol., 20, 2540–2554, https://doi.org/10.1111/gcb.12605, 2014.
Andela, N., Liu, Y. Y., van Dijk, A. I. J. M., de Jeu, R. A. M., and McVicar, T. R.: Global changes in dryland vegetation dynamics (1988–2008) assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data, Biogeosciences, 10, 6657–6676, https://doi.org/10.5194/bg-10-6657-2013, 2013.
Anyamba, A. and Tucker, C. J.: Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981–2003, J. Arid Environ., 63, 596–614, 2005.
Asner, G. P.: Cloud cover in Landsat observations of the Brazilian Amazon, Int. J. Remote Sens., 22, 3855–3862, https://doi.org/10.1080/01431160010006926, 2001.
Baccini, A., Goetz, S. J., Walker, W. S., Laporte, N. T., Sun, M., Sulla-Menashe, D., Hackler, J., Beck, P. S. A., Dubayah, R., Friedl, M. A., Samanta, S. and Houghton, R. A.: Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps, Nat. Clim. Chang., 2, 182–185, https://doi.org/10.1038/nclimate1354, 2012.
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Short summary
We have quantified large-scale forest loss over a 21-year period (1990–2010) in the tropical biomes of South America using a new satellite-based data set. We found that South American forest exhibited interannual variability without a clear trend during the 1990s, but increased from 2000 to 2004. After 2004, forest loss decreased again, mainly as a result of a decrease in the Brazilian Amazon, whereas at the same time regions south of the arc of deforestation showed an increase in forest loss.
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