# Application of Soil Moisture Active Passive (SMAP) Satellite Data in Seismic Response Assessment
###### Abstract
Satellite image processing using thermal, near-infrared and shortwave infrared indicators as proxies for soil wetness have successfully mapped highly liquefied regions after earthquakes [25; 31]. However, to date, direct observations of space-borne soil moisture data have not been used for seismic response analysis and geotechnical applications, which can be an alternative to the current proxies for soil saturation. The Soil Moisture Active Passive [57] Earth observing satellite mission was launched in 2015 by National Aeronautics and Space Administration. SMAP detects soil moisture content in approximately the top 5 cm of the soil layer [58]. With near-global coverage, SMAP's L-band radiometer measures the brightness temperature of Earth's surface and estimates land surface conditions, such as vegetation water content and soil roughness, and then it derives the land surface soil moisture [59]. SMAP revisits each region around \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Technique** & **Satellite** & & **Challenge** & **Application** & **Literature** \\ \hline \multirow{4}{*}{Optical satellite imagery} & GeoEye & \(\bullet\) & Temporal resolution and availability of pre- and post-earthquake data & Identification of ground failures & [31; 48; 49; 50] \\  & IKONOS & \(\bullet\) & Limitations caused by atmospheric conditions (e.g., cloud cover and sun illumination) & Pixel-based or object-based identification of structural damage & [44; 45] \\  & Landsat & \(\bullet\) & Limited aerial coverage & & \\ \hline \multirow{4}{*}{Synthetic aperture radar} & ALOS & \(\bullet\) & Temporal resolution and availability of pre- and post-earthquake data & Measurement of ground movements and slip across faults & [46; 51; 52] \\  & CSKO & \(\bullet\) & Significant data manipulation and processing & Detection of surface change & [40; 53] \\  & ENVISAT & & processing & Pixel-based identification of structural damage & [47; 54; 55] \\ \cline{1-1} \cline{2-5}  & Sentinel & \(\bullet\) & Limited aerial coverage & Pixel-based identification of structural damage & [47; 54; 55] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Satellite data used in earthquake engineering. the globe every 2-3 days (or sooner) to capture surface soil moisture conditions. Using the Backus-Gilbert optimal interpolation, SMAP retrieves the soil moisture at a resolution of 9 km, and has a finer spatial resolution as well as a higher accuracy than its predecessors, such as the Tropical Rainfall Measuring Mission (TRMM) and Advanced Microwave Scanning Radiometer 2 (AMSR-2) [60]. SMAP microwave observations have been widely validated since the relevant datasets were released in April 2015 [61; 62]. SMAP offers rich scientific datasets that have been used in a range of applications; for example, weather and climate predictions [63], agricultural and food productivity [64], and natural hazard monitoring, such as floods and landslides [65; 66]. However, this product has not been employed by the earthquake engineering community to advance the state of the knowledge and practice. Considering the role of soil moisture content in seismic ground response, the SMAP observations may help the community understand the interaction between soil moisture and earthquakes and evaluate how pre- and post-event soil moisture affects different aspects of earthquake-induced soil response. While earthquake-induced soil moisture responses are well-understood, the soil moisture also changes due to precipitation, infiltration, and evapotranspiration. Thus, observed soil moisture changes must account for these responses in order to determine the net response due to an earthquake. Ancillary datasets are needed at the global scale to isolate earthquake-induced soil moisture changes. The Global Precipitation Measurement (GPM) datasets [67] and Global Land Data Assimilation (GLDAS) product [68] are two products available for this purpose.