High-resolution soil moisture data are essential for numerous geophysical applications,enabling improved decision-making in environmental and resource management.However,current satellite-derived global soil moisture ...High-resolution soil moisture data are essential for numerous geophysical applications,enabling improved decision-making in environmental and resource management.However,current satellite-derived global soil moisture products suffer from coarse spatial resolution,limiting their utility.The upcoming NASA-ISRO SAR(NISAR)mission,set for launch in July 2025,aims to overcome this limitation by providing high-resolution soil moisture data at 200[m].One of the mission’s key approaches is the multi-scale algorithm,which enhances coarse-resolution data by incorporating fine-scale synthetic aperture radar(SAR)observations.While initial validation of this algorithm has been conducted over cropland,a broader evaluation is needed across various land covers and climates to ensure its robustness.This study investigates the performance of soil moisture retrieval across 5 diverse test sites,covering forest,shrubland,cropland,and grassland environments,as well as hydrometeorological conditions ranging from arid to polar.The algorithm was assessed at 100[m]and 200[m]resolutions,revealing consistent moisture patterns,with the finer resolution offering greater detail.Validation using in situ measurements showed that the unbiased root mean square error was less than 0.06[m^(3)/m^(3)]for most sites,matching NISAR’s accuracy requirements.A wet bias was observed,and challenges emerged at a polar site due to organic soil.A minimum performance test was conducted to evaluate the impact of SAR backscatter measurements.The results demonstrate that these measurements contribute to improving the accuracy of high-resolution soil moisture retrieval using a multi-scale algorithm.Overall,the study highlights the algorithm’s capability to retrieve soil moisture at high resolution,reinforcing its suitability for the NISAR mission.展开更多
基金supported by NASA Grant 80NSSC21K1181(NISAR Science Team funding).
文摘High-resolution soil moisture data are essential for numerous geophysical applications,enabling improved decision-making in environmental and resource management.However,current satellite-derived global soil moisture products suffer from coarse spatial resolution,limiting their utility.The upcoming NASA-ISRO SAR(NISAR)mission,set for launch in July 2025,aims to overcome this limitation by providing high-resolution soil moisture data at 200[m].One of the mission’s key approaches is the multi-scale algorithm,which enhances coarse-resolution data by incorporating fine-scale synthetic aperture radar(SAR)observations.While initial validation of this algorithm has been conducted over cropland,a broader evaluation is needed across various land covers and climates to ensure its robustness.This study investigates the performance of soil moisture retrieval across 5 diverse test sites,covering forest,shrubland,cropland,and grassland environments,as well as hydrometeorological conditions ranging from arid to polar.The algorithm was assessed at 100[m]and 200[m]resolutions,revealing consistent moisture patterns,with the finer resolution offering greater detail.Validation using in situ measurements showed that the unbiased root mean square error was less than 0.06[m^(3)/m^(3)]for most sites,matching NISAR’s accuracy requirements.A wet bias was observed,and challenges emerged at a polar site due to organic soil.A minimum performance test was conducted to evaluate the impact of SAR backscatter measurements.The results demonstrate that these measurements contribute to improving the accuracy of high-resolution soil moisture retrieval using a multi-scale algorithm.Overall,the study highlights the algorithm’s capability to retrieve soil moisture at high resolution,reinforcing its suitability for the NISAR mission.
