Uncertainties in tree cover maps of Sub-Saharan Africa and their implications for measuring progress towards CBD Aichi Targets

Dorit Gross*, Frédéric Achard, Grégoire Dubois, Andreas Brink, Herbert H.T. Prins

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)

Abstract

The growing access to Earth Observations and processing capabilities have stimulated the production of global and regional products that are commonly used to assess tree-covered habitats and their changes. The popularity of these products has led to their use for defining baselines and to assess progress in conserving natural habitats, in particular, in the context of the conservation targets to 2020 set by the UN Convention on Biological Diversity. In this paper, we reviewed three tree cover products commonly used over Sub-Saharan Africa: (1) MODIS Vegetation Continuous Field percent tree cover map, (2) Global Forest Change map and (3) TREES product. Over a systematic sample of 2045 map subsets, each having a size of 10 × 10 km2, we calculated the extent and change of tree cover from each product for the period between 2000 and 2010. Our statistical and spatial comparison shows noticeable discrepancies between the three products, which lead to uncertainties when assessing tree cover across varying ecosystems. These differences are highest in habitats where tree cover is fragmented or reaches medium density levels and overlap with areas of high economic development potential, where habitat changes are likely to occur in the near future. We discuss these findings in the context of using these remotely sensed tree cover products to support current global biodiversity conservation policies.

Original languageEnglish
Pages (from-to)94-112
JournalRemote Sensing in Ecology and Conservation
Volume4
Issue number2
Early online date2017
DOIs
Publication statusPublished - Jun 2018

Keywords

  • MODIS
  • Aichi Biodiversity Targets
  • Earth Observation
  • Forest loss
  • Policy-making
  • Remote sensing

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