SBAS Network with gaps #966
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What is the recommended approach if data coverage has gaps? Assuming we have a network like something below what are the effects of gaps in the network? Should we process the data separately instead of one big timeseries? The area I'm looking at does not have consistent Sentinel-1 coverage. Please disregard the low coherence, I'm just running some tests with the data and subsets. |
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The gaps in the network will introduce bias in the estimated time-series, as the design matrix does not have full rank anymore, the phase velocity objective function (as introduced in Berardino et al., 2002) helps with this situation, but could not eliminate it. Process each subset separately works if the time coverage still suits your purpose. I want to ask: why there are gaps in the first place? Although the temporal baseline there is large, we could still generate interferograms to connect them, such as in isce2/topsStack, the nearest 3 connection network will give a fully connected network, regardless of 36-day or 108-day. |
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The gaps in the network will introduce bias in the estimated time-series, as the design matrix does not have full rank anymore, the phase velocity objective function (as introduced in Berardino et al., 2002) helps with this situation, but could not eliminate it.
Process each subset separately works if the time coverage still suits your purpose.
I want to ask: why there are gaps in the first place? Although the temporal baseline there is large, we could still generate interferograms to connect them, such as in isce2/topsStack, the nearest 3 connection network will give a fully connected network, regardless of 36-day or 108-day.