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Classifying drivers of global forest loss

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Science  14 Sep 2018:
Vol. 361, Issue 6407, pp. 1108-1111
DOI: 10.1126/science.aau3445
  • Fig. 1 Representative examples of Google Earth imagery used to train the forest loss classification model.

    See (9) for more examples of training imagery.

  • Fig. 2 Primary drivers of forest cover loss for the period 2001 to 2015.

    Darker color intensity indicates greater total quantity of forest cover loss.

  • Fig. 3 Annual deforestation rates.

    (A) Annual worldwide tree cover loss from commodity-driven deforestation between 2001 and 2015. (B) Comparison of annual commodity-driven deforestation in Brazil and the rest of the world between 2001 and 2015.

  • Table 1 Disaggregation of global and regional tree cover loss by driver for the period 2001 to 2015.

    Map-based estimates are based on Global Forest Watch data (3) and a driver of tree cover loss from the current study. Sample-based estimates are based on the validation sample of 1565 randomly selected 10 × 10 grid cells from the current study. Uncertainty of sample-based estimates represents a 95% confidence interval.

    Map-based estimatesSample-based estimates
    Hansen et al. (3)Current study: Driver of tree cover lossCurrent study: Driver of tree cover loss
    RegionTree cover
    loss (Mha,
    2001–2015)
    Tree cover loss
    (% of global total,
    2001–2015)
    DeforestationShifting
    agriculture
    ForestryWildfireUrbanizationDeforestationShifting
    agriculture
    ForestryWildfireUrbanization
    North America7021%1%<1%56%40%2%2 ± 1%1 ± 1%48 ± 11%48 ± 11%1 ± 1%
    Latin America7825%56%31%13%1%<1%64 ± 8%24 ± 7%9 ± 3%<1 ± <1%<1 ± <1%
    Europe155%None<1%99%1%NoneNone<1 ± <1%95 ± 5%5 ± 5%None
    Africa3913%4%92%4%<1%<1%2 ± 1%93 ± 3%4 ± 2%<1 ± <1%1 ± 2%
    Russia/China/
    South Asia
    6420%<1%<1%41%58%<1%2 ± 2%1 ± 1%38 ± 12%59 ± 12%<1 ± <1%
    Southeast Asia3913%78%9%13%<1%<1%61 ± 13%20 ± 10%14 ± 6%2 ± 6%<1 ± <1%
    Australia/
    Oceania
    103%7%10%29%53%1%8 ± 6%10 ± 4%19 ± 9%62 ± 14%1 ± <1%
    Global314100%25%21%31%22%<1%27 ± 5%24 ± 3%26 ± 4%23 ± 4%1 ± <1%

Supplementary Materials

  • Classifying drivers of global forest loss

    Philip G. Curtis, Christy M. Slay, Nancy L. Harris, Alexandra Tyukavina, Matthew C. Hansen

    Materials/Methods, Supplementary Text, Tables, Figures, and/or References

    Download Supplement
    • Materials and Methods
    • Figs. S1 to S10
    • Tables S1 to S7
    • Captions for data S1 to S4
    • References
    Data S1
    All model code is available as Supplementary Data 1.
    Data S2
    All classified reference sample cells used for model training and validation are available as Supplementary Data 2.
    Data S3
    Final map output of our global forest classification model is available as Supplementary Data 3 and can also be visualized on the Global Forest Watch website.
    Data S4
    All information of decision tree splits and relied upon datasets is available as Supplementary Data 4.

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