GAMMA Interferometric Point Target Analysis Software (IPTA): Reference Manual


tpf_2d

ANSI-C program: tpf_2d.c

NAME
tpf_2d - Temporal filtering of displacement or other time-series data (fcomplex, scomplex format or float format)

SYNOPSIS
tpf_2d <TS_tab> <MLI_tab> <itab_ts> <TS_out> <TS_tab_out> [dtype] [dtmax] [mode] [np_max] [sigma]

<TS_tab> (input) list of time-series data files (fcomplex, scomplex, or float (default)
<MLI_tab> (input) list MLI images and parameter files that are associated with the entries of the TS_tab
               NOTE: the number of range and azimuth looks must match files in TS_tab
<itab_ts> (input) single-reference itab describing files in the TS_tab time-series stack
<TS_out> root file name of temporally filtered time-series data files
<TS_tab_out> output TS_tab file containing a list of the filtered time-series data files
[dtype] data type (enter - for default)
     0: fcomplex
     1: scomplex
     2: float (default)
[dtmax] maximum time interval considered (t - dtmax, t + dtmax) (days) (-1: all records, default:  70.00000)
[mode] temporal filter mode
    0: uniform average (default for fcomplex and scomplex)
    1: triangular weighted average
    2: linear least-squares (default for float))
[np_max] maximum number of temporal neighbors (enter - for default: all scenes)
[sigma] (input) phase sigma for interferogram in the TS_tab (text)(enter - for all equal)
format: line_number   phase_sigma

EXAMPLE

tpf_2d TS_tab RMLI_tab itab_ts diff_ts_tpf TS_tab_tpf 2 70 2

Conducts a temporal filtering of the stack of data listed in the TS_tab and described by itab_ts and RMLI_tab. Records which are at most +/-70 days away from the current record are included in the filter window. Linear least-squares filtering has been selected.

TS_tab is a list of the time series data and the file itab_ts is the itab with information which entries in the RMLI_tab apply to the entries in the TS_tabdiff2_ts_tpf is the root file name of the output data files and these are listed in the TS_tab_tpf file. The root file name can also contain a full path and directory names, as long as these already exist. 

DESCRIPTION
tpf_2d supports the temporal filtering of stacks of single reference interferograms. The records to be considered in the filtering can be indicated through the maximum difference in record time and maximum number of records considered, or just one of the two criteria by selecting all records in the other criteria.The itab_ts is required to associate the interferograms with pairs of MLI parameter files.

Several options are available for performing the filtering. Filter modes modes 0 and 1 produce output values that are weighted sums of the input data that are within the local temporal window specified by the dtmax parameter. Either constant or triangular weighting can be selected. 

For data that are floating point, filtering using linear least-squares  (LS) estimation is an option. A linear regression of the values with the temporal window is performed. This mode has the advantage of  reducing errors at the beginning and end of the time series and where there is sparse unevenly sampled data. The bias is reduced by predicting the estimate at the desired time using the linear trend. In the case of NULL values in the input point data stack,  the records considered are not redefined. The temporal filtering is correctly done for these fewer points (i.e. considering the missing values in the normalization).

The "delta-time" considered for a record is the time difference (in days) between the slave and master SLC (as listed in the itab file. In the case of a stack with all records having the same SLC reference this corresponds to a temporal filtering considering the time of the slave SLC.

There is the option to provide a text file containing the standard deviation of the phase values in each layer. The variation on the phase of each layer can be attributed to atmospheric noise. When these phase values are provided for float data (unwrapped phase), the standard deviation for each layer  is used to weight the data in the least-squares smoothing. In this way layers with large atmospheric variation have less influence relative to layers with lower levels of atmospheric noise.

The standard deviation of each layer can be calculated by the program stat_pt. The text file output by stat_pt has 3 entries on each line, the first is the layer number followed by the mean and the standard deviation of the point data in that layer.

SEE ALSO
ipta.hstat_pt, tpf_pt


© Copyrights for Documentation, Users Guide and Reference Manual by Gamma Remote Sensing, 2013.
UW, CW, TS, last change 4-Jul-2013.