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Notebooks for Yunjun et al. (2019) on the MintPy software

Jupyter Notebooks for:

Yunjun, Z., H. Fattahi, F. Amelung (2019), Small baseline InSAR time series analysis: Unwrapping error correction and noise reduction, Computers & Geosciences, 133, 104331, doi:10.1016/j.cageo.2019.104331, arXiv, code.

Data (zenodo)

Dataset 1: ALOS ascending track 133 frame 7160-7180 for Galápagos volcanoes

Dataset 2: Sentinel-1 descending track 128 frame 593-597 for Galápagos volcanoes

  • Date: 13 Dec 2014 - 19 Jun 2018 (98 acquisitions)
  • Processor: ISCE/topsStack + MintPy
  • Configuration: GalapagosSenDT128.template
  • Interferogram stack (in HDF5/MintPy format): GalapagosSenDT128.tar.xz (21.5 GB)
  • Interferogram stack (in HDF5/MintPy format) with 30 sequential connections: SierraNegraSenDT128.zip (850 MB)
    • Area extent: Sierra Negra caldera rim
    • Dimension: 2475 * 150 * 150
    • Related to Fig. 14
  • Displacement time-series (in HDF-EOS5 format): S1_IW12_128_0593_0597_20141213_20180619.he5 (1.3 GB)
  • Displacement time-series (KMZ): S1_IW12_128_0593_0597_20141213_20180619.kmz (73 MB)
  • Volcanic events covered and relavent literactures:
    • Wolf: May 2015 eruption
    • Fernandina: September 2017 eruption (GVP, 2018) and June 2018 eruption (GVP, 2018)
    • Sierra Negra: inflation prior to the 26 June 2018 eruption (GVP, 2018)
    • Cerro Azul: March 2017 dike intrusion

Useful links

  • HDF-EOS5 file structure is described in https://mintpy.readthedocs.io/en/latest/hdfeos5.
  • HDF5/MintPy file structure is described in https://mintpy.readthedocs.io/en/latest/api/data_structure/.
  • KMZ file is described in https://mintpy.readthedocs.io/en/latest/google_earth/.

Figures (nbviewer)

NOTE: This notebook is based on the released version of MintPy-1.2 and NOT maintained for future development. All figures are plotted using matplotlib.

  • Fig. 1 - Performance of four weight functions.
  • Fig. 2 - Phase-unwrapping error correction with bridging.
  • Fig. 3 - Characteristics of phase-unwrapping error in the closure phase.
  • Fig. 4 - Phase-unwrapping error correction with phase closure.
  • Fig. 5 - Routine workflow.
  • Fig. 6 - Velocity at Isabela, Fernandina and Santiago islands.
  • Fig. 7 - Displacement time-series at Fernandina island.
  • Fig. 8 - Comparing InSAR with GPS.
  • Fig. 9 - Assessment of phase-unwrapping error correction using temporal coherence.
  • Fig. 10 - Impact of network modification using temporal coherence.
  • Fig. 11 - Spatial inspection of the inverted raw phase.
  • Fig. 12 - Impact of noisy acquisitions on velocity estimation.
  • Fig. 13 - Phase corrections in the time-series domain.
  • Fig. 14 - Impact of network redundancy.
  • Fig. 15 - Advantage and limitation of temporal coherence as reliability measure.
  • Fig. 16 - Comparing MintPy with GIAnT.