Femke Dekker via web
Following the recently published report of the World Resources Institute (WRI) on global deforestation, we have been seeing a lot of discussions on the high deforestation numbers worldwide and in Ghana in particular.
Numerous media reports stated that Ghana is losing its rainforest faster than any other country in the world and that the 60% increase in deforestation during 2017-2018 is mainly associated with cocoa expansion.
We received a lot of questions related to the report. So we made a quick comparison of the WRI Global Forest Watch data, used in their report, with our own data for 2017-2018.
Our main takeaways:
Comparing data: what is forest?
To understand deforestation, it is important to first define what forests are. For the first time, the 2019 WRI report does not use the University of Maryland ‘tree cover’ layer of the year 2000 as a benchmark. This tree cover layer also includes agricultural tree crops such as cocoa, cashew, rubber, etc. in addition to natural forests. Using this layer would have led to mistakes when clearing of agricultural tree crops, for example for replanting, is flagged as deforestation. This time, however, WRI used the new University of Maryland ‘primary humid tropical forests map’ of year 2001 as a baseline to detect deforestation.
Importantly, the use of this map as a benchmark, excludes all agricultural tree crops. In Ghana, it is almost entirely limited to natural forest remaining in forest reserves and parks in the high forest zone.
Comparing data: what is deforestation?
So, we’re clear on the baseline used, but what about the deforestation related to it? To determine forest loss, WRI works with two different products from University of Maryland based on imagery from one satellite (Landsat):
Satelligence uses imagery from multiple satellites (Sentinel-1 radar, Sentinel-2 optical, Landsat-7,8) and we used: * Satelligence’s weekly Rapid Response data
To compare deforestation from all 3 abovementioned change products, we used the aforementioned 2001 primary humid tropical forests layer as a common benchmark.
Conclusion: adding critical context by reporting on drivers of deforestation
Satelligence’s deforestation findings agree with WRI, but by using more frequent and higher detailed Sentinel satellite imagery we can add critical context by also reporting on the drivers of deforestation and providing fast response.
We conclude that over the past two years, clearing for cocoa farming is not the leading cause of primary forest clearing in Ghana.
Importantly, the WRI analysis did not focus on the detection of forest regrowth outside of primary forest areas, as was also stated by the Forestry Commission of Ghana. This means that the forest increase as a result of the government of Ghana’s hard work on its REDD+ and other interventions, which FC Ghana referred to in their response to the WRI report, is not accounted for.
Better monitoring for compliance
Although the GLAD system fails to provide timely information in the cocoa landscapes of West Africa, it is still a valuable addition that should not be dismissed and can be integrated in an overall global multi-sensor monitoring approach.
We agree with WRI’s emphasis on the need for improved data for compliance/full cocoa monitoring in their recent blog, and think the addition of Sentinel imagery, as we have shown here, can make the difference. We look forward to working on further verification and joint action with all stakeholders.