# Application of Soil Moisture Active Passive (SMAP) Satellite Data in Seismic Response Assessment
## 4 Discussion  
SMAP soil moisture data with support from soil moisture modeled by GLDAS were examined during eleven strong seismic events. Despite the limitations of the spatial and temporal resolutions of microwave remote sensing data, this study provides qualitative evidence that SMAP can detect the soil moisture increase caused by earthquakes, especially for earthquakes with one of the following conditions: (1) extensive and large surface manifestations of liquefaction, (2) a 24 h SMAP event window (Croatia, 2020, Greece, 2020, Indonesia, 2018, Taiwan 2016, Italy 2016, Nepal 2015), (3) no rainfall during the SMAP event window (Greece, 2020, Taiwan, 2016, Italy 2016), and (4) high values of _MDI_ (\(MDI>0.04\) cm\({}^{3}\)/cm\({}^{3}\)). Further research needs to be conducted to categorize the effects of hydrogeological conditions on these seismic-induced soil moisture changes. In this study, a comparison between soil moisture obtained from SMAP and GLDAS was used to identify regions with high soil moisture increase after earthquakes, but there still exist areas for the continued development of more meticulous systems for separating climate-induced soil moisture changes from seismic-induced ones with higher spatial resolution for _MDI_, especially for those with a 48 or 72 h SMAP data time interval. Moreover, although the temporal resolution of SMAP data is significant in comparison with other satellite data used by the earthquake engineering community for other purposes such as damage proxy maps, the perishability of earthquake-induced soil moisture changes highlights the need for more complex systems to filter climate-induced soil moisture changes. Another challenge is that earthquake-induced soil moisture response occurs at much finer scales than SMAP's 9 km. Passive microwave radiometers, such as SMAP, provide a high temporal resolution but a coarse spatial resolution when compared to active microwave sensors and SARs. Over the last few years, many downscaling approaches, including satellite- and model-based methods, have been employed to downscale the coarse resolution of different satellite soil moisture products [23; 88; 89; 90]. Previous studies provided opportunities to improve the spatial resolution of SMAP soil moisture data products to 1 km [90; 91]. As the remote sensing technologies are advanced and the next generation of radars are lunched [92], better spatial resolution with global coverage will be expected. Future works would likely benefit from using well-established satellite soil moisture downscaling approaches to address the issue of SMAP's coarse spatial resolution and to isolate seismic-induced soil moisture changes at a higher resolution; specifically, by taking advantage of both radiometer and radar measurements through the integration of both data [88]. Furthermore, the encouraging relationships between \(\Delta SM_{SMAP}\) and seismic records suggest that the earthquake community could employ SMAP as a comprehensive dataset for investigations that seek to leverage interactions between land surface soil moisture and seismic events. In the majority of the target earthquakes, including Croatia 2020, Greece 2020, Indonesia 2018, Taiwan 2016, Ecuador 2016, and Nepal 2015, a relationship between land surface soil moisture and seismic events was evident. For these events, the earthquake-induced soil moisture response occurred in liquefaction-prone seismic zones. In the Italy 2016 and Chile 2015 earthquakes, though no serious liquefaction features were reported by the GEER teams, there were still SMAP grids with a notable soil moisture increase (\(MDI>0.04\) cm\({}^{3}\)/cm\({}^{3}\)) that may have caused other types of ground deformations, such as seismic compression. However, there is not adequate mapped evidence to confirm this theory. In Italy 2016, damage proxy maps identified ground failures at some grids with a positive _MDI_. New Zealand 2016 is the only study region for which there is a clear inconsistency between \(\Delta SM_{SMAP}\) and the seismic records.