Alexandra Tyukavina and her colleagues from the University of Maryland, the State University of New York and Woods Hole Research Center, all in the US, looked at forest above-ground carbon loss in the Democratic Republic of Congo (DRC).

To estimate the area of forest loss, they used forest cover and gross forest cover loss data from the Forêts d'Afrique Centrale Evaluées par Télédétection (FACET) product, which has a spatial resolution of 60 m per pixel. To validate this data, the researchers used 30 m Landsat data as well as visual interpretation of very high spatial resolution images from Google Earth and unclassified commercial satellite data from NASA.

The team found that, for the DRC between 2000 and 2010, forest loss was actually 30–40% higher than published estimates.

"Current national-scale estimates use medium-resolution satellite data, but the changes in the DRC are small and dispersed, so this data does not give a true reflection of the changes that are occurring," Tyukavina told environmentalresearchweb. "In another country, such as Brazil for example, where the agro-industrial land conversion results in large forest disturbances, medium-resolution data provides a viable deforestation monitoring approach. But in the DRC where forest change is mainly due to smallholders shifting cultivation, a higher resolution is needed in order to capture these dispersed changes."

Tyukavina and her colleagues also found it was important to note not only the amount of forest being lost, but also the type of forest. "We found above-ground carbon loss in secondary forests to be 140% that of primary forests," said Tyukavina. "This underlines the importance of monitoring other forest dynamics. While reducing primary forest loss is the main focus of strategies such as REDD+, other forest types and even trees outside of forests will be part of national carbon accounting schemes."

The researchers believe their technique for assessing the accuracy of forest loss data could easily be applied to other countries. "We have published an easy-to-follow, step-by-step method so that other groups can use our technique," said Tyukavina. "The work shows how important it is for researchers to know the data they are working with. The technique is mostly applicable to countries like the DRC where change is small and dispersed. We plan to extend this work to cover all the tropical regions in Africa."

The team reported the results in Environmental Research Letters (ERL).

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