A recent study used crowdsourced information to generate a dataset on drivers of forest loss with unprecedentedly high spatial resolution.
Understanding the drivers behind forest damage and loss is critical for generating predictive models and designing effective methods for safeguarding natural habitats. In order to develop a clear picture of the reasons behind tropical forest loss, a team of researchers set up a crowdsourcing campaign on geo-wiki, complete with comprehensive instructions and training materials to ensure the quality of the results returned.
The campaign was carried out in December 2020, and lasted two weeks. In this time, 58 participants reviewed almost 115,000 unique locations in the tropics, identifying any drivers of forest loss in those areas between 2008 and 2019. These include agriculture expansion, road building and deforestation. In order to incentivise participation, prizes were offered to those who contributed the highest quantity and quality of results. The resulting dataset was produced at a higher spatial resolution than any previous efforts.
The dataset is open-source and is available to use for researchers, policymakers, and the public. The researchers state the data can be employed to produce updated maps of tropical drivers of forest loss, which in turn can be used to support policy makers in their decision-making and inform the public.
This study is an excellent example of the power of crowdsourcing information, as it enabled the researchers to build a comprehensive and informative dataset in a very short period time. The dataset has already been used for further research efforts, and is likely to be an invaluable resource to researchers and policymakers alike.
Many industries are increasingly incorporating the idea of ‘gamification’ to engage customers, users and members of the public. The prize support aspect of this study is an example of this to some extent, and its success demonstrates that there may be many other interesting applications of gamification in scientific research.
For more information, the original research article can be found here.