Contribution of Earth observation data to support SDG indicators: An analytical framework and related case studies

In 2015, member countries of the United Nations adopted the 17 Sustainable Development Goals (SDGs) at the Sustainable Development Summit in New York. These global goals have 169 targets and 232 indicators that are based on the three pillars of sustainable development: economic, social, and environmental. Substantial challenges remain in obtaining data of the required quality to inform the indicators, especially in developing countries, given the often limited resources that are available. One promising and relatively innovative way of addressing this issue is to use Earth Observation (EO) satellite data. This research aimed to critically analyse the potential of EO approaches to data collection for populating SDG indicators, with the particular focus on those covering the social and economic dimensions of sustainable development, as these are relatively unexplored in the EO context. Additionally, this research aimed to explore the use of EO technologies linked to monitoring, reporting and verification within policy. Firstly, a novel analytical framework entitled Maturity Matrix Framework (MMF) was developed for assessing the potential of EO to populate all 232 SDG indicators. This framework was further consolidated by using a wide consultation with 38 experts in sustainability and EO, thus obtaining the advanced MMF 2.0 framework. Both frameworks have been applied to all SDG indicators and the results demonstrated that the potential of EO‐derived data do vary among the SDG indicators, but overall, EO can have a direct contribution to make towards populating environmental indicators and an indirect (proxy) measure or weakcontribution for socio-economic indicators. Therefore, the evaluation of the potential of EO satellite data against MMF 2.0 and the literature available shown that 19 indicators have weak support from EO, 67 partial support from EO, and 22 strong EO support. The results that emerged from both frameworks (MMF and MMF 2.0) led towards exploring a more conventional application of satellite data and its implications in the policy context but also towards, developing an EO approach that measures socio-economic indicators. Therefore, this research presents three case studies. The first case study shows how EO satellite data can be used for assessing the habitat of five key species in Surrey Hills. In the second case study available published literature was assessed to understand the potential of estimating SOC using EO technologies. This review was complemented by a series of semistructuredinterviews with specialists in the soil health and policy sector. Both case studies can help the current Environmental Land Management Scheme in the context of the monitoring, reporting and verification (MRV) process. In the third case study, 1900 rural primary schools across 19 Nigerian states were measured using satellite images and teaching area per pupil was calculated. The approach identified 81.4 % of the schools as being overcrowded