Abstract
This data set is the first-of-its-kind spatial representation of multi-seasonal, global C-band Synthetic Aperture Radar (SAR) interferometric repeat-pass coherence and backscatter signatures. Coverage comprises land masses and ice sheets from 82° Northern to 79° Southern latitudes. The data set is derived from multi-temporal repeat-pass interferometric processing of about 205,000 Sentinel-1 C-band SAR images acquired in Interferometric Wide-Swath Mode from 1-Dec-2019 to 30-Nov-2020. The data set encompasses three sets of seasonal (December-February, March-May, June-August, September-November) metrics produced with a pixel spacing of three arcseconds: 1) Median 6-, 12-, 18-, 24-, 36-, and 48-days repeat-pass coherence at VV or HH polarizations, 2) Mean radiometrically terrain corrected backscatter (γ0) at VV and VH, or HH and HV polarizations, and 3) Estimated parameters of an exponential coherence decay model. The data set has been produced to obtain global, spatially detailed information on how decorrelation affects interferometric measurements of surface displacement and is rich in spatial and temporal information for a variety of mapping applications.
Highlights
Interferometric Synthetic Aperture Radar (InSAR) measurements of surface deformation and change provide an important tool for understanding the dynamics of earthquakes, volcanoes, landslides, glaciers, groundwater variation, mantle processes, and ecological processes in agriculture, wetland, and vegetation disturbances, among other applications
Where NL is the effective number of SAR looks, γeff the effective coherence between two SAR images, and λ the signal wavelength
Provided appropriate image formation and interferometric processing, the interferometric coherence observed over a target of interest depends on the length of the interferometric baseline, system noise, and temporal decorrelation[1–4] γeff = γbaseline × γnoise × γtemporal
Summary
Interferometric Synthetic Aperture Radar (InSAR) measurements of surface deformation and change provide an important tool for understanding the dynamics of earthquakes, volcanoes, landslides, glaciers, groundwater variation, mantle processes, and ecological processes in agriculture, wetland, and vegetation disturbances, among other applications. To assess the performance of planned satellite missions, NASA JPL developed a Science Performance Model for the upcoming NISAR mission[6] to simulate the line-of-sight error associated with mission plan This model has been extended to support trade studies on NISAR continuity measurements under NASA’s Surface Deformation and Change (SDC) Architecture study[7], which includes constellation concepts at different wavelengths and spacecraft constellation configurations. The primary motivation for producing this rich data set was to support mission design and application development in the context of measuring surface deformation To this end, numerous previous studies have demonstrated the value of C-band interferometric coherence and backscatter time series for various applications, e.g., the mapping of land cover[11–13], biophysical parameters of forests[14–23] or crops[18,24,25], soil moisture[26,27], sea ice, icesheets and glaciers[28–30], or properties of snow[31–33]. This is the first globally consistent data set supporting such applications at regional to global scales
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