Multidimensional Small Baseline Subset (MSBAS)

Multidimensional Small Baseline Subset (MSBAS) is used for time series analysis of InSAR and speckle range/azimuth offset data. Depending on the input data, it can be used to compute 1D, 2D, constrained 3D, unconstrained 3D, and 4D velocity and/or displacement time series. The free version of the software can be downloaded from here. The software’s manual can be downloaded from here and here. More recent features can be observed in the parameter files supplied with the test data. The professional version is designed to process very large datasets (e.g. multi-frame Sentinel-1 InSAR) by intelligently managing processing resources. It utilizes MPI and OpenMP parallelization technologies and can be run on clusters. It also works on fully and partially coherent pixels.

References

1D-2D

  • Samsonov, S. and d‘Oreye, N., 2012. Multidimensional time series analysis of ground deformation from multiple InSAR data sets applied to Virunga Volcanic Province, Geophys. J. Int., 191, 1095–1108, https://doi.org/10.1111/j.1365-246X.2012.05669.x
  • Samsonov, S., d’Oreye, N., and Smets, B. 2013. Ground deformation associated with post-mining activity at the French-German border revealed by novel InSAR time series method. International Journal of Applied Earth Observation and Geoinformation, 23, 142–154, https://doi.org/10.1016/j.jag.2012.12.008
  • Samsonov, S., Gonzalez, P., Tiampo, K., and d’Oreye, N. 2013. Spatio-temporal analysis of ground deformation occurring near Rice Lake, Saskatchewan, and observed by Radarsat-2 DInSAR during 2008–2011. Canadian Journal of Remote Sensing, 39(1), 27–33, https://doi.org/10.5589/m13-005
  • Samsonov, S.V., Tiampo, K.F., Camacho, A.G., Fernández, J., and González, P.J. 2014. Spatiotemporal analysis and interpretation of 1993–2013 ground deformation at Campi Flegrei, Italy, observed by advanced DInSAR. Geophysical Research Letters, 41(17), 6101–6108, https://doi.org/10.1002/2014GL060595
  • Samsonov, S., d’Oreye, N., González, P., Tiampo, K., Ertolahti, L., and Clague, J. 2014. Rapidly accelerating subsidence in the Greater Vancouver region from two decades of ERS-ENVISAT- RADARSAT-2 DInSAR measurements. Remote Sensing of Environment, 143(5), 180–191, https://doi.org/10.1016/j.rse.2013.12.017
  • Samsonov, S., Gonzalez, P., Tiampo, K., and d’Oreye, N. 2014. Modeling of fast ground subsidence observed in southern Saskatchewan (Canada) during 2008–2011. Natural Hazards and Earth System Sciences, 14, 247–257, https://doi.org/10.5194/nhess-14-247-2014
  • Samsonov, S.V., Trishchenko, A.P., Tiampo, K., González, P.J., Zhang, Y., and Fernández, J. 2014. Removal of systematic seasonal atmospheric signal from interferometric synthetic aperture radar ground deformation time series. Geophysical Research Letters, 41(17), 6123–6130, https://doi.org/10.1002/2014GL061307
  • Samsonov, S., Czarnogorska, M., and White, D. 2015. Satellite interferometry for high-precision detection of ground deformation at a carbon dioxide storage site. International Journal of Greenhouse Gas Control, 42, 188–199, https://doi.org/10.1016/j.ijggc.2015.07.034
  • Samsonov, S., Feng, W., Peltier, P., Geirsson, H., d’Oreye, N., and Tiampo, K. 2016. Multidimensional small baseline subset (MSBAS) for volcano monitoring in two dimensions: Opportunities and challenges. Case study Piton de la Fournaise volcano. Journal of Volcanology and Geothermal Research, 344, 121-138, https://doi.org/10.1016/j.jvolgeores.2017.04.017
  • Samsonov, S.V., Lantz, T.C., Kokelj, S.V., and Zhang, Y. 2016. Growth of a young pingo in the Canadian Arctic observed by RADARSAT-2 interferometric satellite radar. The Cryosphere, 10(2), 799–810, https://doi.org/10.5194/tc-10-799-2016
  • Samsonov, S.V., Tiampo, K.F., and Feng, W. 2016. Fast subsidence in downtown of Seattle observed with satellite radar. Remote Sensing Applications: Society and Environment, 4, 179–187, https://doi.org/10.1016/j.rsase.2016.10.001
  • Samsonov, S. and d‘Oreye, N. 2017. Multidimensional Small Baseline Subset (MSBAS) for Two-Dimensional Deformation Analysis: Case Study Mexico City. Canadian Journal of Remote Sensing, 43, 318–329, https://doi.org/10.1080/07038992.2017.1344926
  • Samsonov S. 2017. Short- and long-term ground deformation due to cyclic steam stimulation in Alberta, Canada, measured with interferometric radar. The Leading Edge, 36(1), 36-42, https://doi.org/10.1190/tle36010036.1
  • Samsonov, S. 2019, User manual, source code, and test set for MSBASv3 (Multidimensional Small Baseline Subset version 3) for one- and two-dimensional deformation analysis. Geomatics Canada, Open File 45, 2019, 13 pages, https://doi.org/10.4095/313749
  • Samsonov, S., Baryakh, A. 2020. Estimation of Deformation Intensity above a Flooded Potash Mine Near Berezniki (Perm Krai, Russia) with SAR Interferometry. Remote Sensing, 12, 3215, https://doi.org/10.3390/rs12193215

3D (SPF-constrained)

  • Samsonov, S. 2019. Three-dimensional deformation time series of glacier motion from multiple-aperture DInSAR observation. Journal of Geodesy, 93, 2651–2660, https://doi.org/10.1007/s00190-019-01325-y
  • Samsonov, S., Dille, A., Dewitte, O., Kervyn, F., and d‘Oreye, N. 2020. Satellite interferometry for mapping surface deformation time series in one, two and three dimensions: A new method illustrated on a slow-moving landslide. Engineering Geology, 266, 105471, https://doi.org/10.1016/j.enggeo.2019.105471

3D

  • Samsonov, S., Tiampo, K., and Cassotto, R. 2021.Measuring the state and temporal evolution of glaciers in Alaska and Yukon using synthetic-aperture-radar-derived (SAR-derived) 3D time series of glacier surface flow. The Cryosphere, 15, 4221–4239, https://doi.org/10.5194/tc-15-4221-2021
  • Samsonov, Sergey; Tiampo, Kristy; Cassotto, Ryan 2021. Data for: Measuring the state and temporal evolution of glaciers in Alaska and Yukon using SAR-derived 3D time series of glacier surface flow. Mendeley Data, V1, https://doi.org/10.17632/zf67rsgydv.1

4D

  • Samsonov, S., Tiampo, K., and Cassotto, R. 2021. SAR-derived flow velocity and its link to glacier surface elevation change and mass balance. Remote Sensensing of Environment, 258, 112343, https://doi.org/10.1016/j.rse.2021.112343
  • Samsonov, Sergey; Tiampo, Kristy; Cassotto, Ryan 2020, Data for: SAR-derived flow velocity and its link to glacier surface elevation change and mass balance. Mendeley Data, V1, https://doi.org/10.17632/9d96c5bddm.1