## 3 Potential of Earth Observation (EO) for Supporting SDG Indicators
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Spatial Resolution** & **Examples of Satellites** & **Scale** \\ \hline Coarse resolution (\(>\)1000 m) & e.g., GCOM, Envisat, Aeolus, etc. & Global and regional \\ \hline Medium resolution (100 m to 1000 m) & e.g., MODIS, AVHRR, Sentinel-3 & Global and regional \\ \hline Fine resolution (5 m to 100 m) & e.g., Landsat 5–8 TM, Sentinel-2, & Regional and local \\ \hline Very high resolution (VHR) (\(<\)5 m) & e.g., Rapid Eye, WorldView, & Local \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Spatial resolution of satellites in EO [43]. Free and open access data play a key role in enabling the discovery, retrieval, and manipulation of data to monitor the planet [44]. For instance, NASA and the U.S. Geological Society (USGS) have provided free Landsat imagery since 2008 [45]; ESA has released free data (e.g., ERS, Envisat, Meteosat) since 2010; now, all data from the operational Sentinel missions are freely available via the Copernicus Programme [46]. Open data can be freely used, re-used, and redistributed by anyone, whereas commercial data, such as VHR imagery from commercial satellites, require the user to purchase the data and to follow a license agreement. Commercial satellite imagery can be expensive depending on the size of the area of interest, spatial resolution and number of observation dates required. [PERSON] et al. [47] provided an example of using commercial satellite data for precision agriculture, as this application benefited from higher spatial and temporal resolutions than space agency sensors can provide; however, they considered these data expensive for their application. Comparisons of the cost-effectiveness of EO-derived data versus other sources of data are still relatively rare in the literature; nevertheless, examples are provided by [48; 49; 50; 51; 52]. The findings of these studies suggest that using EO-derived data can be more cost advantageous compared with the use of other data; however, the savings depend on the scale of the project and what other types of data are available. For example, [PERSON] et al. [52] conducted a cost-effectiveness analysis for their approach in detecting the healthcare service buildings for an area in south-eastern Liberia; the computational and data cost involved was USD 12.30; if the method was applied for the entire country, the cost would be approximately USD 141. These low prices show that EO-derived data can provide information at a substantially reduced cost compared to the traditional monitoring costs, which determines SDG indicators accessible for all nations, thus providing an opportunity for _\"leaving no one behind\"_[51]. There are numerous web portals and services that enable the discovery, access, and use of EO data and derived information products. These can be classified into three main categories:  
* EO data portals
* EO processing, visualisation, and cloud computing platforms (where the term 'platform' in this paper refers to those online resources layer which provides the 'back-end' functionality of EO satellite images, rather than the engineering use of \"platform\" used to contrast the \"satellite\" with its \"sensor\")
* EO derived thematic products and services [53; 54]  
There are around 25 EO data portals that provide free (to the user) and open satellite data at medium spatial resolution (e.g., Sentinel and Landsat) and historical VHR data (these are listed in Supplementary Material Table S2) [55; 56; 57; 58; 59; 60]. Free and open access EO data are generally provided by taxpayer-funded national and international space agencies and are provided for the public good. They play a major role in expanding the spectrum of new users and applications [81]. There are numerous commercial suppliers (e.g., PlanetLab, Maxar Technologies, Iceye, Earth-I, EarthBlox, Pixera, Surrey Satellite Technologies, etc.) that offer EO satellite data and/or products for a cost or a subscription plan tailored to the clients' needs.