## 2 Earth Observation Data for Capacity Building  
For decades, Earth observation satellites have produced a comprehensive archive of data covering the entire globe. Specifically, satellites such as the Advanced Very High-Resolution Radiometer(AVHRR), MERIS, MSG Geostationary satellite, and Moderate Resolution Imaging Spectroradiometer (MODIS) provide wide coverage, allowing daily image acquisitions at a coarse spatial resolution of between 250 m and 1 km. These course resolution datasets have been invaluable in developing global land cover products such as GlobCover [9; 10], Global Land Cover 2000 [11], DISCover [12] and MODIS Land Cover [13; 14], among others. In addition, the datasets have been used for mapping, monitoring and assessment of wildfires [15; 16; 17], surface water [18; 19; 20], floods [21; 22], agricultural activities [23; 24; 25], biodiversity [26; 27; 28], and drought [29; 30]. These datasets provide unparalleled, temporally detailed information that is useful for rapid detection of surface changes due to various natural and anthropogenic phenomena such as disasters and land-use changes; thus, they are suitable for addressing information needs at national to regional scales, to support implementation, monitoring and reporting at these levels. However, detailed analysis and monitoring for decision making at a local scale require high spatial resolution. The availability of long-term, medium-resolution data records and almost continuous coverage since 1972 from the Landsat program have unequivocally advanced research, products and applications development in an unprecedented manner. Alarmingly, studies show that research outputs from African institutions are still low, which is attributable to insufficient internet bandwidth for downloading satellite data and a lack of hardware for processing, analyzing and storing the data. Landsat's wealth of data is sustained by the availability of new-generation advanced sensors such as Landsat 8 Operational Land Imager (OLI), CBERS-4B and Sentinel 2 Multispectral Imager (MSI), with better spatial, temporal and spectral resolutions, accessible from various data catalogues (Figure 2). These offer profound opportunities for capacity building in Earth observations and the development of innovative commercial solutions and applications in various thematic areas that are relevant for addressing AU-A2063 aspirations. In addition to being the greatest asset to global change studies, data from Landsat and Sentinel 2 are valuable for monitoring and assessment at a landscape scale to support on-the-ground decisions and enhancing service delivery. The increase in free and open data presents new challenges that require new techniques to fuse multiple datasets to take advantage of their unique characteristics related to spatial and temporal resolutions, and to overcome challenges related to clouds and associated cloud shadows common in EO data. Fortunately, data infrastructures such as Data Cube (also known as Digital Earth) offer prospects for sustainable development in Africa. This is evidenced by initiatives focusing on Africa such as African Regional Data Cube [31] (ARDC) and Digital Earth Africa [32]. In addition, commercial data from sensors such as from SPOT 6/7, Rapid Eye and Worldview are increasingly becoming affordable, with the capability for user-defined tasking plans, which are useful for repeated and on-demand image acquisitions at a specific area of interest such as disaster-stricken areas. These sensors are instrumental in deriving and maintaining most geospatial baseline datasets, such as road and railway networks [33; 34], forest inventory [35; 36], wetland delineation [37; 38], digital elevation models [39; 40; 41], river and stream networks [42], building structures [43], agricultural field boundaries [44; 45], and powerlines [46]. Innovative agreements such as the Single License-Multi-User Agreement (SLMA) for negotiating cheaper high-resolution data for multiple countries need to be explored in Africa.