The data, information and knowledge on the tropical forest area and its dynamics in the Brazilian Amazon remain contentious. We use time-series satellite images to quantify annual forest area, loss and gain in the Brazilian Amazon during 2000–2017. We find that forest area was ~15% higher than the estimate by the official Brazilian forest dataset (PRODES), but annual forest-loss rates were twice the PRODES estimates (~0.027 × 106 km2 yr–1 during 2001–2016). Forest-loss rates increased again after 2013. The El Niño and drought year (2015/2016) drove large forest area loss. The cumulative forest-loss area within the protected areas (which include ~50% of forests in the region) was ~11% of the total forest-loss area, which highlights the roles of protected areas in forest conservation.
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The PALSAR/MODIS forest and MOD100 forest data that support the findings of this study are available from the corresponding author upon request and will be made available to the public. The other datasets are publicly available online (Supplementary Table 6).
Ochoa-Quintero, J. M., Gardner, T. A., Rosa, I., Ferraz, S. F. D. & Sutherland, W. J. Thresholds of species loss in Amazonian deforestation frontier landscapes. Conserv. Biol. 29, 440–451 (2015).
Davidson, E. A. et al. The Amazon basin in transition. Nature 481, 321–328 (2012).
Jenkins, C. N., Pimm, S. L. & Joppa, L. N. Global patterns of terrestrial vertebrate diversity and conservation. Proc. Natl Acad. Sci. USA 110, E2602–E2610 (2013).
Fearnside, P. M. Deforestation in Brazilian Amazonia: history, rates, and consequences. Conserv. Biol. 19, 680–688 (2005).
Nepstad, D. et al. Slowing Amazon deforestation through public policy and interventions in beef and soy supply chains. Science 344, 1118–1123 (2014).
Hansen, M. C. & DeFries, R. S. Detecting long-term global forest change using continuous fields of tree-cover maps from 8-km advanced very high resolution radiometer (AVHRR) data for the years 1982–99. Ecosystems 7, 695–716 (2004).
Souza, C., Firestone, L., Silva, L. M. & Roberts, D. Mapping forest degradation in the Eastern Amazon from SPOT 4 through spectral mixture models. Remote Sens. Environ. 87, 494–506 (2003).
Hansen, M. C., Shimabukuro, Y. E., Potapov, P. & Pittman, K. Comparing annual MODIS and PRODES forest cover change data for advancing monitoring of Brazilian forest cover. Remote Sens. Environ. 112, 3784–3793 (2008).
Friedl, M. A. et al. MODIS Collection 5 global land cover: algorithm refinements and characterization of new datasets. Remote Sens. Environ. 114, 168–182 (2010).
Skole, D. & Tucker, C. Tropical deforestation and habitat fragmentation in the Amazon: satellite data from 1978 to 1988. Science 260, 1905–1910 (1993).
Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).
Qin, Y. et al. Annual dynamics of forest areas in South America during 2007–2010 at 50-m spatial resolution. Remote Sens. Environ. 201, 73–87 (2017).
Reiche, J. et al. Combining satellite data for better tropical forest monitoring. Nat. Clim. Change 6, 120–122 (2016).
Rajão, R., Moutinho, P. & Soares, L. The rights and wrongs of Brazil’s forest monitoring systems. Conserv. Lett. 10, 495–496 (2017).
Richards, P., Arima, E., VanWey, L., Cohn, A. & Bhattarai, N. Are Brazil’s deforesters avoiding detection? Conserv. Lett. 10, 470–476 (2017).
Asner, G. P. et al. Selective logging in the Brazilian Amazon. Science 310, 480–482 (2005).
Tyukavina, A. et al. Types and rates of forest disturbance in Brazilian Legal Amazon, 2000–2013. Sci. Adv. 3, e1601047 (2017).
Achard, F. & Hansen, M. C. Global Forest Monitoring from Earth Observation (Taylor & Francis, 2012).
Shimada, M. et al. New global forest/non-forest maps from ALOS PALSAR data (2007–2010). Remote Sens. Environ. 155, 13–31 (2014).
Reiche, J. et al. Feature level fusion of multi-temporal ALOS PALSAR and landsat data for mapping and monitoring of tropical deforestation and forest degradation. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 6, 2159–2173 (2013).
Qin, Y. et al. Quantifying annual changes in built-up area in complex urban-rural landscapes from analyses of PALSAR and Landsat images. ISPRS J. Photogramm. Remote Sens. 124, 89–105 (2017).
McDowell, N. G. et al. Global satellite monitoring of climate-induced vegetation disturbances. Trends Plant Sci. 20, 114–123 (2015).
Wu, J. et al. Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest. New Phytol. 217, 1507–1520 (2018).
Macedo, M. N. et al. Decoupling of deforestation and soy production in the southern Amazon during the late 2000s. Proc. Natl Acad. Sci. USA 109, 1341–1346 (2012).
le Maire, G., Dupuy, S., Nouvellon, Y., Loos, R. A. & Hakarnada, R. Mapping short-rotation plantations at regional scale using MODIS time series: case of eucalypt plantations in Brazil. Remote Sens. Environ. 152, 136–149 (2014).
Xiao, X. M., Biradar, C. M., Czarnecki, C., Alabi, T. & Keller, M. A simple algorithm for large-scale mapping of evergreen forests in tropical America, Africa and Asia. Remote Sens. 1, 355–374 (2009).
Qin, Y. et al. Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010. Sci. Rep. 6, 20880 (2016).
Qin, Y. W. et al. Forest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA and NFI. ISPRS J. Photogramm. Remote Sens. 109, 1–16 (2015).
Land cover CCI Product User Guide v.2 (European Space Agency, 2016).
Nepstad, D. et al. The end of deforestation in the Brazilian Amazon. Science 326, 1350–1351 (2009).
Morton, D. C. et al. Cropland expansion changes deforestation dynamics in the southern Brazilian Amazon. Proc. Natl Acad. Sci. USA 103, 14637–14641 (2006).
McManus, C. et al. Dynamics of cattle production in Brazil. PLoS ONE 11, e0147138 (2016).
Brando, P. M. et al. Abrupt increases in Amazonian tree mortality due to drought–fire interactions. Proc. Natl Acad. Sci. USA 111, 6347–6352 (2014).
Soares, B. et al. Role of Brazilian Amazon protected areas in climate change mitigation. Proc. Natl Acad. Sci. USA 107, 10821–10826 (2010).
Nolte, C., Agrawal, A., Silvius, K. M. & Soares, B. S. Governance regime and location influence avoided deforestation success of protected areas in the Brazilian Amazon. Proc. Natl Acad. Sci. USA 110, 4956–4961 (2013).
Bustamante, M. M. C. et al. Are Brazil deforesters avoiding detection? Reply to Richards et al. 2016. Conserv. Lett. 10, 493–494 (2017).
Rodrigues, A., Marcal, A. R. S., Furlan, D., Ballester, M. V. & Cunha, M. Land cover map production for Brazilian Amazon using NDVI SPOT VEGETATION time series. Can. J. Remote Sens. 39, 277–289 (2013).
Brazil Market Overview: Timber and Forest Products (Hancock Timber Resource Group, 2014).
Barlow, J. et al. Diversity and composition of fruit-feeding butterflies in tropical Eucalyptus plantations. Biodivers. Conserv. 17, 1089–1104 (2008).
Marsden, S. J., Whiffin, M. & Galetti, M. Bird diversity and abundance in forest fragments and Eucalyptus plantations around an Atlantic forest reserve, Brazil. Biodivers. Conserv. 10, 737–751 (2001).
Barlow, J. et al. Quantifying the biodiversity value of tropical primary, secondary, and plantation forests. Proc. Natl Acad. Sci. USA 104, 18555–18560 (2007).
Coelho, M., Juen, L. & Mendes-Oliveira, A. C. The role of remnants of Amazon savanna for the conservation of neotropical mammal communities in eucalyptus plantations. Biodivers. Conserv. 23, 3171–3184 (2014).
Fearnside, P. M. Brazilian politics threaten environmental policies. Science 353, 746–748 (2016).
Freitas, F. L. M. et al. Potential increase of legal deforestation in Brazilian Amazon after Forest Act revision. Nat. Sustain. 1, 665–670 (2018).
Shimada, M., Isoguchi, O., Tadono, T. & Isono, K. PALSAR radiometric and geometric calibration. IEEE Trans. Geosci. Remote Sens. 47, 3915–3932 (2009).
Carreiras, J. M. B., Vasconcelos, M. J. & Lucas, R. M. Understanding the relationship between aboveground biomass and ALOS PALSAR data in the forests of Guinea-Bissau (West Africa). Remote Sens. Environ. 121, 426–442 (2012).
Cartus, O., Santoro, M. & Kellndorfer, J. Mapping forest aboveground biomass in the Northeastern United States with ALOS PALSAR dual-polarization L-band. Remote Sens. Environ. 124, 466–478 (2012).
Ma, J. et al. Estimating aboveground biomass of broadleaf, needleleaf, and mixed forests in Northeastern China through analysis of 25-m ALOS/PALSAR mosaic data. For. Ecol. Manage. 389, 199–210 (2017).
Huete, A. R., Liu, H. Q., Batchily, K. & vanLeeuwen, W. A comparison of vegetation indices over a global set of TM images for EOS-MODIS. Remote Sens. Environ. 59, 440–451 (1997).
Xiao, X. et al. Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data. Int J. Remote Sens. 23, 3009–3022 (2002).
Huffman, G. et al. Integrated Multi-satellitE Retrievals for GPM (IMERG) Version 4.4 (NASA’s Precipitation Processing Center, 2014); ftp://arthurhou.pps.eosdis.nasa.gov/gpmdata/
Swenson, S. C. GRACE monthly land water mass grids NETCDF RELEASE 5.0. CA, USA (NASA Jet Propulsion Laboratory, 2012).
Landerer, F. W. & Swenson, S. C. Accuracy of scaled GRACE terrestrial water storage estimates. Water Resour. Res. 48, 4531 (2012).
Giglio, L. & Justice, C. MOD14A2 MODIS/Terra Thermal Anomalies/Fire 8-Day L3 Global 1km SIN Grid V006 (NASA EOSDIS Land Processes DAAC, 2015); https://doi.org/10.5067/MODIS/MOD14A2.006
Giglio, L., Justice, C., Boschetti, L. & Roy, D. MCD64A1 MODIS/Terra+Aqua Burned Area Monthly L3 Global 500m SIN Grid V006 (NASA EOSDIS Land Processes DAAC, 2015); https://doi.org/10.5067/MODIS/MCD64A1.006
Pengra, B., Long, J., Dahal, D., Stehman, S. V. & Loveland, T. R. A global reference database from very high resolution commercial satellite data and methodology for application to Landsat derived 30 m continuous field tree cover data. Remote Sens. Environ. 165, 234–248 (2015).
Olofsson, P. et al. A global land-cover validation data set. Part I: fundamental design principles. Int. J. Remote Sens. 33, 5768–5788 (2012).
Stehman, S. V., Olofsson, P., Woodcock, C. E., Herold, M. & Friedl, M. A. A global land-cover validation data set. Part II: augmenting a stratified sampling design to estimate accuracy by region and land-cover class. Int. J. Remote Sens. 33, 6975–6993 (2012).
Didan, K. MOD13Q1 MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V006 (NASA EOSDIS Land Processes DAAC, 2015); https://doi.org/10.5067/MODIS/MOD13Q1.006
Vermote, E. MOD09A1 MODIS/Terra Surface Reflectance 8-Day L3 Global 500m SIN Grid V006 (NASA EOSDIS Land Processes DAAC, 2015); https://doi.org/10.5067/MODIS/MOD09A1.006
This study is supported in part by research grants from NASA Land Use and Land Cover Change programme (grant no. NNX14AD78G), NASA Geostationary Carbon Cycle Observatory (GeoCarb) Mission (GeoCarb Contract no. 80LARC17C0001), the Inter-American Institute for Global Change Research (IAI) (grant no. CRN3076), which is supported by the US National Science Foundation (grant no. GEO-1128040) and NSF EPSCoR project (no. IIA-1301789).
The authors declare no competing interests.
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Qin, Y., Xiao, X., Dong, J. et al. Improved estimates of forest cover and loss in the Brazilian Amazon in 2000–2017. Nat Sustain 2, 764–772 (2019). https://doi.org/10.1038/s41893-019-0336-9
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