Defining a Trade-off Between Spatial and Temporal Resolution of a Geosynchronous SAR Mission for Soil Moisture Monitoring

Remote Sensing

Luca Pulvirenti¹  Giorgio Boni¹  Luca Cenci²  Nazzareno Pierdicca² 

[1] CIMA Research Foundation, 17100 Savona, Italy;Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00184 Rome, Italy;

关键词: geosynchronous synthetic aperture radar (GEO SAR);    Geosynchronous—Continental Land-Atmosphere Sensing System (G-CLASS);    soil moisture;    data assimilation;    hydrology;    space mission design;    spatial resolution;    temporal resolution;   

DOI  :  10.3390/rs10121950

来源: DOAJ

【 摘 要 】

The next generation of synthetic aperture radar (SAR) systems could foresee satellite missions based on a geosynchronous orbit (GEO SAR). These systems are able to provide radar images with an unprecedented combination of spatial (≤1 km) and temporal (≤12 h) resolutions. This paper investigates the GEO SAR potentialities for soil moisture (SM) mapping finalized to hydrological applications, and defines the best compromise, in terms of image spatio-temporal resolution, for SM monitoring. A synthetic soil moisture⁻data assimilation (SM-DA) experiment was thus set up to evaluate the impact of the hydrological assimilation of different GEO SAR-like SM products, characterized by diverse spatio-temporal resolutions. The experiment was also designed to understand if GEO SAR-like SM maps could provide an added value with respect to SM products retrieved from SAR images acquired from satellites flying on a quasi-polar orbit, like Sentinel-1 (POLAR SAR). Findings showed that GEO SAR systems provide a valuable contribution for hydrological applications, especially if the possibility to generate many sub-daily observations is sacrificed in favor of higher spatial resolution. In the experiment, it was found that the assimilation of two GEO SAR-like observations a day, with a spatial resolution of 100 m, maximized the performances of the hydrological predictions, for both streamflow and SM state forecasts. Such improvements of the model performances were found to be 45% higher than the ones obtained by assimilating POLAR SAR-like SM maps.

【 授权许可】

Unknown