ERS Track 98 SAR Data and InSAR Pairs Used in the Analysis

Transcription

1 ERS Track 98 SAR Data and InSAR Pairs Used in the Analysis Date 1 Date 2 Date 1 Date 2 Date 1 Date 2 Date 1 Date 2 7/17/1992 6/19/2000 7/17/1992 7/2/1993 9/10/ /28/1996 9/3/ /18/1999 9/25/1992 6/19/2000 9/25/1992 7/2/1993 5/5/ /28/ /13/ /18/ /13/1995 6/19/2000 1/8/1993 7/2/1993 8/21/1992 1/6/1997 1/21/ /18/1999 1/21/1996 6/19/2000 6/12/1992 9/10/1993 9/25/1992 1/6/1997 3/31/ /18/1999 1/22/1996 6/19/2000 4/23/1993 9/10/1993 1/8/1993 1/6/1997 4/1/ /18/1999 3/31/1996 6/19/2000 7/17/1992 9/3/ /12/1995 1/6/1997 6/10/ /18/1999 4/1/1996 6/19/2000 9/25/1992 9/3/ /13/1995 1/6/1997 1/6/ /18/1999 1/6/1997 6/19/2000 1/8/1993 9/3/1995 1/21/1996 1/6/1997 2/10/ /18/1999 3/17/1997 6/19/2000 7/2/1993 9/3/1995 1/22/1996 1/6/1997 3/17/ /18/ /18/1999 6/19/2000 6/12/ /12/1995 3/31/1996 1/6/1997 3/2/ /18/ /22/1999 6/19/2000 8/21/ /12/1995 4/1/1996 1/6/1997 7/17/ /22/1999 6/19/2000 7/24/2000 7/17/ /13/1995 9/3/1995 2/10/1997 8/21/ /22/1999 7/17/1992 7/24/2000 8/21/ /13/1995 3/31/1996 2/10/1997 9/25/ /22/ /13/1995 7/24/2000 9/25/ /13/1995 4/1/1996 2/10/1997 9/3/ /22/1999 1/21/1996 7/24/2000 1/8/ /13/1995 6/10/1996 2/10/ /12/ /22/1999 1/22/1996 7/24/2000 7/2/ /13/1995 7/17/1992 3/17/ /13/ /22/1999 3/31/1996 7/24/2000 9/3/ /13/1995 8/21/1992 3/17/1997 1/21/ /22/1999 4/1/1996 7/24/2000 7/17/1992 1/21/1996 9/25/1992 3/17/1997 1/22/ /22/1999 1/6/1997 7/24/2000 8/21/1992 1/21/1996 1/8/1993 3/17/1997 3/31/ /22/1999 3/17/1997 7/24/2000 9/25/1992 1/21/1996 7/2/1993 3/17/1997 4/1/ /22/ /18/1999 7/24/2000 1/8/1993 1/21/1996 9/3/1995 3/17/1997 1/6/ /22/ /22/1999 7/24/2000 7/2/1993 1/21/ /12/1995 3/17/1997 3/17/ /22/1999 4/23/1993 8/28/2000 9/3/1995 1/21/1996 1/22/1996 3/17/ /17/ /22/1999 9/10/1993 8/28/ /12/1995 1/21/1996 3/31/1996 3/17/ /18/ /22/1999 5/5/1996 8/28/ /13/1995 1/21/1996 4/1/1996 3/17/ /6/2000 2/13/2006 4/21/1997 8/28/2000 7/17/1992 1/22/1996 1/6/1997 3/17/1997 7/24/2000 9/11/2006 2/15/1999 8/28/2000 8/21/1992 1/22/1996 6/12/1992 4/21/ /2/ /20/2006 6/19/ /2/2000 9/25/1992 1/22/1996 8/21/1992 4/21/1997 7/24/ /2/ /12/1995 1/22/1996 4/23/1993 4/21/1997 7/2/ /2/ /13/1995 1/22/1996 9/10/1993 4/21/1997 9/3/ /2/2000 9/25/1992 3/31/ /12/1995 4/21/1997 3/31/ /2/2000 1/8/1993 3/31/1996 8/21/ /17/1997 4/1/ /2/2000 7/2/1993 3/31/ /12/ /17/1997 6/10/ /2/2000 9/3/1995 3/31/ /13/ /17/1997 1/6/ /2/ /13/1995 3/31/1996 1/21/ /17/1997 2/10/ /2/2000 1/21/1996 3/31/1996 1/22/ /17/1997 3/2/ /2/2000 1/22/1996 3/31/1996 1/6/ /17/1997 9/13/ /2/2000 7/17/1992 4/1/1996 3/17/ /17/ /18/ /2/2000 9/25/1992 4/1/1996 4/21/ /17/ /22/ /2/2000 1/8/1993 4/1/1996 9/3/1995 3/2/1998 8/28/ /6/2000 7/2/1993 4/1/1996 4/1/1996 3/2/1998 1/22/ /6/2000 9/3/1995 4/1/1996 6/10/1996 3/2/1998 4/21/ /6/ /13/1995 4/1/1996 2/10/1997 3/2/ /17/ /6/2000 1/21/1996 4/1/1996 9/10/1993 2/15/1999 6/12/1992 8/21/1992 4/23/1993 5/5/1996 5/5/1996 2/15/1999 7/17/1992 8/21/1992 9/10/1993 5/5/ /28/1996 2/15/1999 7/17/1992 9/25/1992 1/8/1993 6/10/1996 4/1/1996 9/13/1999 8/21/1992 9/25/1992 7/2/1993 6/10/1996 6/10/1996 9/13/1999 7/17/1992 1/8/1993 9/3/1995 6/10/1996 2/10/1997 9/13/1999 9/25/1992 1/8/1993 3/31/1996 6/10/1996 3/2/1998 9/13/1999 6/12/1992 4/23/1993 4/1/1996 6/10/1996 9/25/ /18/1999

2 Data Repository Table 1: Track 98 SAR acquisitions (frames ) and InSAR pairs used in the time series inversion. InSAR Data Processing To process the ERS 1/2 data, we use the Caltech/JPL ROI_PAC software package (Rosen et al., 2004) with precise satellite orbits from Scharroo and Visser (1998). Interferograms were filtered using ROI_PAC s non-linear spectral filter (Goldstein and Werner, 1998). We use 1 arc-second (approximately 30 m-resolution) Shuttle Radar Topography Mission (SRTM) digital elevation models (DEMs) to remove the topographic signal embedded within the InSAR phase (Farr and Kobrick, 2000). Processed interferograms were unwrapped using SNAPHU (Chen and Zebker, 2002) and then converted to geographic coordinates using the SRTM DEM. Because of the large number of interferograms used in our analysis, there are multiple constraints on deformation for many time intervals. Therefore, after all of the interferograms from a particular satellite track are co-registered to a single master scene, we apply a linear least squares inversion scheme to each set of interferograms (e.g., Lundgren et al., 2001), solving for the deformation history that best fits the entire set of temporally overlapping interferograms. The implicit assumption of the inversion is that deformation measured in any one interferogram is the sum of the deformation within each of the time intervals encompassed by that interferogram. By minimizing the misfit between the modeled deformation and the actual deformation for each interferogram, we solve for the deformation over every time interval spanning time-adjacent SAR acquisitions. By weighting the inversion with the overall phase variance of each unwrapped interferogram (e.g., Kwoun et al., 2006), we compensate for the fact that some interferograms are inherently noisier than others. We note that Finnegan et al. (2008) found that time series-derived velocities averaged over 8+ years of SAR data can reduce atmospheric errors to within ~ 0.5 mm/yr. Hence, we are confident in our ability to define uplift patterns and rates at Socorro, where surface uplift is a few millimeters per year. GPS Data Our time series velocities are lower in magnitude than velocities computed from 1-year of campaign GPS data collected between (Newman et al., 2004). However, our modeled deformation is consistent with the observed motion of the continuous GPS station SC01, which is moving to the south with respect to stable North America at 1-2 mm/year (Calais et al., 2006; pboweb.unavco.org). Measurement of Terrace Elevations For the northern ~2/3 of the study area, we define the Llano de Manzano based on Connell et al. s (2007) map. South of Connell et al. s (2007) map, we extend the location of the Llano de Manzano via a combination of Google Earth imagery and SRTM 1-arcsec digital elevation data (Fig. 1A). We trace the elevation of the Llano de Manzano along the inside edge of the terrace, thereby obtaining terrace elevations as close to the

3 modern Rio Grande as possible. By tracing the inside edge of the terrace, we also attempted to minimize the effects on the terrace profile of active normal faults, which although parallel to the terrace edge may nevertheless result in some longitudinal disruption of the surface. Finally, noting that the modern Rio Grande is sinuous, whereas our sampling of the Llano de Manzano occurs on a much straighter line, we also apply a correction to the terrace data so that they are sampled along an equally sinuous path as the modern Rio Grande. We note that the relative elevation accuracy of ~30 m SRTM data over North America is 4 m for long-wavelength features such as the Llano de Manzano (Rodriguez, 2005), so we should be able to resolve easily surface uplift of m in magnitude Profile Modeling For figure 3, we measured the concavity of each river outside of the region of volcanic uplift using channel slopes averaged over 1 km and drainage areas derived from the 1 arc-sec (~ 30 m resolution) SRTM DEM. We then projected the elevation profile across the region of volcanic uplift using the measuredconcavity. References Chen, C.W. and Zebker, H.A., 2002, Phase unwrapping for large SAR interferograms: statistical segmentation and generalized network models, IEEE Transactions on geosciences and remote sensing, v. 40, p Connell, S.D., Love, D.W., and Dunbar, N.W., 2007, Geomorphology and stratigraphy of inset fluvial deposits along the Rio Grande valley in the central Albuquerque basin, New Mexico: New Mexico Geology, v. 29, p Farr, T.G. and Kobrick, M., 2000, Shuttle Radar Topography Mission produces a wealth of data, EOS, Transactions, American Geophysical Union, v. 81, p Finnegan, N.J., Pritchard, M.E., Lohman, R.B., and Lundgren, P.R., 2008, Constraints on surface deformation in the Seattle, WA urban corridor from satellite radar interferometry time series analysis, Geophysical Journal International, v. 174, p Goldstein, R. M. and Werner, C.L., 1998, Radar interferogram filtering for geophysical applications, Geophysical Research Letters, v. 25, p Kwoun, O.-l., Lu, Z., Neal, C., and Wicks Jr., C., 2006, Quiescent deformation of Aniakchak Caldera, Alaska, mapped by InSAR, Geology, v. 34, p Lundgren, P., Usai, S., Sansosti, E., Lanari, R., Tesauro, M., Fornaro, G., and Berardino, P., 2001, Modeling surface deformation observed with synthetic aperture radar interferometry at Campi Flegrei caldera, Journal of Geophysical Research, v. 106, p. 19,355-19,366.

4 Rodriguez, E., 2005, A global assessment of the SRTM accuracy, 2005, abstracts with programs, The Shuttle Radar Topography Mission Data Validation and Applications Workshop, June 14 16, 2005, Reston, VA, p. 13. Rosen, P. A., Hensley, S., Peltzer, G., and Simons, M., 2004, Updated repeat orbit interferometry package released, EOS, Transactions, American Geophysical Union, v. 85, p. 35. Scharroo, R. and Visser, P.N.A.M., 1998, Precise orbit determination and gravity field improvement for the ERS satellites, Journal of Geophysical Research, v. 103, p

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