December 09, 2013
The study, which involved researchers from the University of Maryland, the State University of New York and Woods Hole Research Center, is based on change in forest cover in the Democratic Republic of Congo (DRC), which accounts for the bulk of the world's second largest tropical rainforest. The researchers used 30-meter Landsat data, visual interpretation of high spatial images from Google Earth, and other NASA satellite data to map forest loss between 2000 and 2010. They found that DRC's forest loss was up to 40 percent higher than estimated by assessments based on medium-resolution satellite data. The reason? Unlike other parts of the world like the Amazon and Indonesia where deforestation is predominantly large-scale for cattle ranches, plantations, and industrial agriculture, the majority of forest conversion in Africa is for subsistence agriculture and therefore small in extent, often limited to two hectares or less. Medium resolution satellite data misses these small clearings.
"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," study lead author Alexandra Tyukavina told environmentalresearchweb, a web site run by IOP Publishing, which publishes Environmental Research Letters. "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."
The study estimates that DRC lost 506,000-670,000 hectares of forest and woodlands annually during the 2000's. About three-fifths of that loss occurred in secondary forests. Primary forests declined at a rate of 113,000-169,000 ha per year.
Forest cover loss (2000–2010) within DRC forest types; error bars are the 95% confidence intervals.
The researchers plan to apply their approach to other African where small-farmers are the primary driver of deforestation.
"We have published an easy-to-follow, step-by-step method so that other groups can use our technique," Tyukavina was quoted as saying by environmentalresearchweb. "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."
Forest type and strata averages, aggregated to a 5-km grid: (a) year 2000 aboveground carbon (AGC); (b) map-scale estimate of 2000–2010 gross AGC loss; (c) sub-grid estimate of 2000–2010 AGC loss; (d) difference between sub-grid and map-scale estimates. Water bodies are shown in gray. Note that AGC values for both (b) and (c) are the same for the respective forest types.
CITATION: A Tyukavina, S V Stehman, P V Potapov, S A Turubanova, A Baccini, S J Goetz, N T Laporte, R A Houghton and M C Hansen (2013). National-scale estimation of gross forest aboveground carbon loss: a case study of the Democratic Republic of the Congo. Environmental Research Letters 8 044039
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