Complementary use of citizen science and EO data for addressing SDG data gaps

The Sustainable Development Goals (SDGs) are a universal agenda to address the world’s most pressing challenges. Robust monitoring mechanisms and timely, accurate and comprehensive data are essential in guiding policies and decisions for successful implementation of the SDGs. Yet current ways of monitoring progress towards the SDGs such as through household surveys cannot address the SDG data gaps and needs. Along with EO data, citizen science offers a solution to complement traditional data sources. The complementarity of citizen science and EO approaches for SDG monitoring has also been acknowledged in the literature. For example, the authors of this contribution carried out a systematic review of all SDG indicators and citizen science initiatives, demonstrating that citizen science data are already contributing and could contribute to the monitoring of 33 per cent of the SDG indicators. As part of this review, they also identified overlap between contributions from citizen science and EO for SDG monitoring. One specific citizen science tool integrating citizen science and EO approaches that could complement and enhance SDG monitoring is Picture Pile. Picture Pile is a web-based and mobile application for ingesting imagery from satellites, orthophotos, unmanned aerial vehicles or geotagged photographs that can then be rapidly classified by volunteers. Picture Pile has the potential to contribute to the monitoring of fifteen SDG indicators covering areas, such as deforestation, post disaster damage assessment and identification of slums, among others, which can provide reference data for the training and validation of products derived from remote sensing. This talk presents the potential offered by Picture Pile and other citizen science tools and initiatives focusing on urban applications to complement and enhance official statistics to monitor several SDGs and targets including SDG 11 Sustainable Cities and Communities. Recommendations will also be provided for how to enable partnerships and collaborations across data communities and ecosystems in order to mainstream citizen science and EO data for SDG monitoring and reporting of urban issues.