## 4 Assessing EO Contribution to SDGs Indicators Using a Maturity Matrix Framework (MMF) Approach
There are 14 economic indicators mostly represented by GDP (in its various forms) that can be found in SDG 2, SDG 8, and SDG 10. There are 27 SDG environmental indicators that encompass issues of water scarcity, water resource management (SDG 6), climate change (SDG 13), loss and degradation of biodiversity and ecosystems services (SDG 6, SDG 13, SDG 14, SDG 15), deforestation (SDG 15). Most partnership indicators (14 out of 16) occur in SDG 17, as the goal focuses on progress made in strengtheningglobal partnership and in improving financial governance. The last category, comprehensive SDG indicators, cover 96 indicators, of which 30 have socio-environmental features and 66 include socio-economic dimensions of sustainability. Therefore, the SDG indicator framework has an imbalance across the three pillars of sustainability and is mainly focused on the socio-economic aspects with only 27 environmental and 30 socio-environmental indicators. Based on the MMF 2.0 [15] summarised above, we have re-evaluated all SDG indicators using the latest best practice case studies and approaches available in the literature and reports up to mid-2021 and have applied the categories presented in Figure 2. The results (see Figure S1) suggest that 108 SDG indicators could be populated, at least in part, by using data from EO. These comprise 19 indicators with weak support from EO, 67 with partial support from EO, and 22 with strong EO support. The remaining 139 indicators had no evidence (yet) (see Figure 3) that EO data could be used for their support; however, this is a rapidly evolving field in which future approaches to using EO data for social indicators may be developed. These results have been sorted further in Figure 3, based on the indicator types of Figure 2. The findings suggest that a strong contribution of EO data is predominantly within the environmental type indicators; however, that was not exclusive, as several social-economic indicators (e.g., indicators 1.4.2, 1.5.1, 1.5.2., 2.1.1, 11.5.1, 11.6.2) can be also measured directly by EO data. For instance, indicator 1.5.2. (direct economic loss attributed to disasters in relation to global GDP) can be directly measured by EO datasets; [PERSON] et al. [177] have shown an approach of automatic detection of building damage of an earthquake, and EO optical and radar imagery can be used to gather useful information on the economic loss on other disasters (e.g., flooding, transport infrastructure, fires, landslides, etc.) at different stages. Satellite data of very high spatial and temporal resolutions play a critical role in disaster management. Figure 2: SDG Indicator type based on the three dimensions of sustainability (Authors’ assessment). Figure 3: SDG indicators type and the EO satellite contribution (based on MMF 2.0) (Authors’ assessment). Moreover, indicators with partial support from EO are spread amongst all indicator types, reflecting the potential of EO satellite-derived data to play a role in calculating the SDG indicator via a proxy indicator. For example, SDG indicators 16.1.1 (number of victims of intentional homicide per 100,000 population, by sex and age) cannot be measured directly by satellite data. However, [PERSON] et al. [178] investigated the influence of the urban layout (e.g., impervious surface percentage, type of roofs, land cover types) on homicide rates using VHR image and integrated census data for socio-economic variables; thus, they found associations of higher homicide rates with more heterogeneous and disordered urban layouts. Likewise, EO data have been used to monitor conflicts (bombing, military presence, war) by using historical records of the areas that changed over time and humanitarian efforts, for example, by spotting refugee camps and estimating the number of refugees from space [149]; all these applications can be linked to SDG indicator 16.1.2 (conflict-related deaths per 100,000 population, by sex, age and cause).