Provided by: gmtsar-core_6.5+ds-2_amd64 bug

NAME

       sbas - sbas

DESCRIPTION

       This program is part of GMTSAR.

              USAGE:  sbas  intf.tab  scene.tab N S xdim ydim [-atm ni] [-smooth sf] [-wavelength
              wl] [-incidence inc] [-range -rng] [-rms] [-dem]

              input:

       intf.tab
              --  list of unwrapped (filtered) interferograms:

       format:
              unwrap.grd  corr.grd  ref_id  rep_id  B_perp

       scene.tab
              --  list of the SAR scenes in chronological order

       format:
              scene_id   number_of_days

       note:  the number_of_days is relative to a reference date

       N      --  number of the interferograms

       S      --  number of the SAR scenes

       xdim and ydim
              --  dimension of the interferograms

       -smooth sf           --
              smoothing factors, default=0

       -atm ni              --
              number of iterations for atmospheric correction, default=0(skip atm correction)

       -wavelength wl       --
              wavelength of the radar wave (m) default=0.236

       -incidence theta     --
              incidence angle of the radar wave (degree) default=37

       -range rng           --
              range distance from the radar to the center of the interferogram (m) default=866000

       -rms                 --
              output velocity uncertainty grids (mm/yr): rms.grd

       -dem                 --
              output DEM error (m): dem_err.grd

       -mmap                --
              use mmap to allocate disk space for less use of memory

       -robust              --
              only work with -atm turnned  on,  estimate  velocity  with  records  that  has  atm
              correction

              output:

       disp_##.grd
              --  cumulative displacement time series (mm) grids

       vel.grd
              --  linear regressed velocity (mm/yr) grids

              example:

              sbas intf.tab scene.tab 88 28 700 1000

       REFERENCES:  Berardino  P., G. Fornaro, R. Lanari, and E. Sansosti, ???A new algorithm for
       surface deformation monitoring based on small baseline differential SAR interferograms,???
       IEEE Trans. Geosci. Remote Sensing, vol. 40, pp. 2375???2383, Nov. 2002.

       Schmidt,  D.  A.,  and R. B??rgmann 2003, Time-dependent land uplift and subsidence in the
       Santa Clara valley, California, from a large interferometric synthetic aperture radar data
       set, J. Geophys. Res., 108, 2416, doi:10.1029/2002JB002267, B9.

       Tong,  X.  and  Schmidt,  D.,  2016.  Active  movement of the Cascade landslide complex in
       Washington from a coherence-based InSAR time series method. Remote Sensing of Environment,
       186, pp.405-415.

       Tymofyeyeva,  E.  and  Fialko,  Y.,  2015. Mitigation of atmospheric phase delays in InSAR
       data, with application to the  eastern  California  shear  zone.  Journal  of  Geophysical
       Research: Solid Earth, 120(8), pp.5952-5963.

       Xu, X., Sandwell, D. T., Tymofyeyeva, E., Gonz??lez-Ortega, A., & Tong, X.(2017). Tectonic
       and  anthropogenic  deformation  at  the  Cerro  Prietogeothermal  step-over  revealed  by
       Sentinel-1A InSAR. IEEE Transactions onGeoscience and Remote Sensing, 55(9), 5284-5292.

              USAGE:  sbas  intf.tab  scene.tab N S xdim ydim [-atm ni] [-smooth sf] [-wavelength
              wl] [-incidence inc] [-range -rng] [-rms] [-dem]

              input:

       intf.tab
              --  list of unwrapped (filtered) interferograms:

       format:
              unwrap.grd  corr.grd  ref_id  rep_id  B_perp

       scene.tab
              --  list of the SAR scenes in chronological order

       format:
              scene_id   number_of_days

       note:  the number_of_days is relative to a reference date

       N      --  number of the interferograms

       S      --  number of the SAR scenes

       xdim and ydim
              --  dimension of the interferograms

       -smooth sf           --
              smoothing factors, default=0

       -atm ni              --
              number of iterations for atmospheric correction, default=0(skip atm correction)

       -wavelength wl       --
              wavelength of the radar wave (m) default=0.236

       -incidence theta     --
              incidence angle of the radar wave (degree) default=37

       -range rng           --
              range distance from the radar to the center of the interferogram (m) default=866000

       -rms                 --
              output velocity uncertainty grids (mm/yr): rms.grd

       -dem                 --
              output DEM error (m): dem_err.grd

       -mmap                --
              use mmap to allocate disk space for less use of memory

       -robust              --
              only work with -atm turnned  on,  estimate  velocity  with  records  that  has  atm
              correction

              output:

       disp_##.grd
              --  cumulative displacement time series (mm) grids

       vel.grd
              --  linear regressed velocity (mm/yr) grids

              example:

              sbas intf.tab scene.tab 88 28 700 1000

       REFERENCES:  Berardino  P., G. Fornaro, R. Lanari, and E. Sansosti, ???A new algorithm for
       surface deformation monitoring based on small baseline differential SAR interferograms,???
       IEEE Trans. Geosci. Remote Sensing, vol. 40, pp. 2375???2383, Nov. 2002.

       Schmidt,  D.  A.,  and R. B??rgmann 2003, Time-dependent land uplift and subsidence in the
       Santa Clara valley, California, from a large interferometric synthetic aperture radar data
       set, J. Geophys. Res., 108, 2416, doi:10.1029/2002JB002267, B9.

       Tong,  X.  and  Schmidt,  D.,  2016.  Active  movement of the Cascade landslide complex in
       Washington from a coherence-based InSAR time series method. Remote Sensing of Environment,
       186, pp.405-415.

       Tymofyeyeva,  E.  and  Fialko,  Y.,  2015. Mitigation of atmospheric phase delays in InSAR
       data, with application to the  eastern  California  shear  zone.  Journal  of  Geophysical
       Research: Solid Earth, 120(8), pp.5952-5963.

       Xu, X., Sandwell, D. T., Tymofyeyeva, E., Gonz??lez-Ortega, A., & Tong, X.(2017). Tectonic
       and  anthropogenic  deformation  at  the  Cerro  Prietogeothermal  step-over  revealed  by
       Sentinel-1A InSAR. IEEE Transactions onGeoscience and Remote Sensing, 55(9), 5284-5292.