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Harnessing the power of crowdsourcing to improve land cover and land-use information

Final Report Summary - CROWDLAND (Harnessing the power of crowdsourcing to improve land cover and land-use information)

The aim of the CrowdLand project has been to demonstrate the potential of crowdsourcing and citizen science to collect data on land use and land cover using mobile phones and through visual interpretation of satellite imagery, disseminating the results in almost 60 papers and book chapters. To achieve this aim, a number of apps were developed and tested through crowdsourcing campaigns.

The FotoQuest Austria app was developed and tested during the summers of 2015 to 2017 and then expanded to all EU countries in 2018 as FotoQuest Go. FotoQuest is a serious game in which players undertake quests. Each quest consisted of photographing the landscape and determining the type of land cover and land use. The protocol for this game is loosely based on the professional LUCAS (Land Use Cover Area Sample frame) survey, which takes place every three years across EU member states. The idea was to see whether citizens could collect data to complement the LUCAS survey by providing data on a more frequent basis. When the crowdsourced data were compared to LUCAS, the results showed that citizens are able to document the landscape in a useful manner. The approach has great potential for enhancing LUCAS and to provide much needed data for the development of future land cover products. Around 6,600 quests were completed during the project.

The Picture Pile tool for the rapid classification of images was also developed within the CrowdLand project. The game was used in numerous crowdsourcing campaigns, e.g. for detection of deforestation, damage assessment after Hurricane Matthew, cloud detection, poverty mapping, etc., and has led to the collection of 15.8 million observations. More recently, Picture Pile has been modified for the Earth Challenge 2020 for crop type detection as part of enhancing food security.

The CrowdLand project has also contributed to strengthening the flagship tool, which has been used in numerous crowdsourcing campaigns and led to the collection of more than 1.28 million observations. Campaigns on cropland and agricultural field size resulted in two publications in the high-level journal Global Change Biology. More recently, campaigns were held to collect information on forest management to aid in biodiversity conservation.

Complementing the tool development and data collection campaigns has been research on the quality of crowdsourced data, methods of data fusion to create improved land cover products, and research into incentives for crowd participation. The results have shown that citizens are able to make meaningful and useful contributions to monitoring land cover and land use, and the data collected have been placed in open access data repositories. The project has investigated a range of innovative data fusion methods, which, in combination with crowdsourced data, have contributed to the production of improved hybrid land cover maps at a global scale. The crowdsourcing campaigns have employed different types of incentives to motivate participation, including co-authorship on a scientific publication, prizes and micro-payments. All the incentives were successful although the research also revealed that participation in humanitarian causes and aiding science were often sufficient motivators to participate.

Finally, the CrowdLand project has engaged with citizen science practitioners around the world and with various United Nations (UN) agencies to examine the potential of citizen science in the monitoring and implementation of the UN Sustainable Development Goals (SDGs), publishing the results in the high profile journal Nature Sustainability. This has led to a systematic review of the potential of citizen science on an SDG indicator basis to quantify the current contributions of citizen science to the SDGs while highlighting those indicators where contributions could be possible in the future.