precipitation during wet pulses is important for vegetation growth and productivity, with this having a key role in carbon uptake [1; 2; 3; 4]. Australia is one of the major dryland areas worldwide. Refs. [5; 6] reported the high sensitivity of extensive Central Australian drylands to hydroclimatic variability and thus the vulnerability to predicted future changes in climate. Semi-arid ecosystems are exposed to sporadic events of intense rainfall. Although rainfall is the main trigger of vegetation response during these events, the water balance in the soil can vary spatio-temporally depending on several factors, such as rainfall intensity, topography, and soil type, among others. Thus, soil moisture (SM) is considered a critical factor in rainfall-driven dryland ecosystems, as a hydrological variable resulting from the water balance in the soil [7; 8; 9; 10]. It is a more comprehensive variable than rainfall; thus, it is related to different processes of the soil-plant-atmosphere interface and can subsequently be considered a variable with fewer errors than different factors separately. For example, [11] showed that the Enhanced Vegetation Index (EVI) and solar-induced chlorophyll fluorescence (SIF) were better correlated with surface SM (0-10 cm depth) than precipitation in semi-arid areas of Central Australia. Given that this is a key surface variable of the evapotranspiration process (ETa), the understanding of soil water effect on vegetation dynamics through satellite data can contribute to spatially predicting the response of vegetation to wet pulses in large drylands with limited field measurements [11]. Although surface SM can be retrieved from well-known methods like microwave retrieval algorithms, it may not be enough to determine water vegetation conditions, given the frequent decoupling with deeper depths and given that plants can extract water from subsurface horizons depending on the development of deep roots [11; 12]. Moreover, the response of vegetation to root-zone soil water availability has not been extensively analyzed, probably due to the lack of estimates of vertical SM distribution and accessibility of vegetation to it [13]. Australia is one of the largest land masses covered by arid and semi-arid ecosystems, with about 70% of the area represented by woodlands, savannas, and grasslands [14]. The importance of Australian semi-arid ecosystems on global land carbon sink related to changes produced by wet rainfall pulses (typically more than 50 mm/week) has been reported [15]. In 2010-2011, almost 60% of the large global carbon sink anomaly occurred in Australia as a consequence of extraordinary rainfall events [1; 3]. In this sense, Mulga (_Acacia_ spp.) covers 20-25% of the Australian land area [16] and was one of the most important semi-arid ecosystems contributing to the 2011 carbon sink anomaly [17]. Although it is clear that vegetation growth is strongly associated with wet rainfall events in these semi-arid systems [5; 18], the study of the temporal response of vegetation is still important for predicting the impact of those events and to evaluate the performance of different indicators. Given that SM has spatial and temporal variability, satellite remote sensing offers an opportunity to monitor its impact on vegetation at different spatio-temporal scales. In this sense, geostationary (GEO) satellites have certain advantages over low-Earth-orbiting (LEO) satellites, given the consistency in viewing geometry (which can produce variability in reflectance data), better temporal coverage, and more chances to conduct cloud-free observations [19]. For example, [20] reported that seasonal changes in viewing and illumination geometry could produce significant variations in vegetation indices over Australian woodland and open forest areas. In these drylands, where vegetation can show sub-fortnightly changes as a consequence of rainfall events [21], GEO satellites, such as the recent Japanese Himawari-8, have the potential to monitor those short-time changes.