Multidimensional Small Baseline Subset Software

Multidimensional Small Baseline Subset (MSBAS) Software Version 10 enables time series analysis of InSAR and speckle range/azimuth offset data. Based on the input data type, it can compute velocity and displacement time series in 1D, 2D, Surface Parallel Flow (SPF) and Aspect Parallel Flow (APF) constrained 3D, unconstrained 3D, and 4D formats.

Older software versions 3 and 6 (no longer supported):

  • MSBAS Software Version 3 and its user manual are available for download here and here.
  • MSBAS Software Version 6 can be downloaded here. Parameter files included with the test data demonstrate more recent features.

Current MSBAS Software Version 10:

Version 10 is optimized for processing very large datasets (e.g., multi-frame Sentinel-1 InSAR) by efficiently managing computational resources. It employs MPI and OpenMP parallelization technologies, making it suitable for cluster environments. The software supports both fully and partially coherent pixels.

Download the software here and the user manual here.

References

1D and 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. Geophysical Journal International, 191, 1095–1108. https://doi.org/10.1111/j.1365-246X.2012.05669.x
  • Samsonov, S., d’Oreye, N., & 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., & d’Oreye, N. (2013). Spatio-temporal analysis of ground deformation near Rice Lake, Saskatchewan, observed by Radarsat-2 DInSAR (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., & 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., & 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., & 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., & 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., & 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., & Tiampo, K. (2016). Multidimensional Small Baseline Subset (MSBAS) for volcano monitoring in two dimensions: Piton de la Fournaise case study. Journal of Volcanology and Geothermal Research, 344, 121–138. https://doi.org/10.1016/j.jvolgeores.2017.04.01
  • Samsonov, S.V., Lantz, T.C., Kokelj, S.V., & 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., & Feng, W. (2016). Fast subsidence in downtown 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. & d’Oreye, N. (2017). Multidimensional Small Baseline Subset (MSBAS) for Two-Dimensional Deformation Analysis: Case Study of 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 for one- and two-dimensional deformation analysis. Geomatics Canada, Open File 45, 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
  • Samsonov, S., Blais-Stevens, A., 2023. Satellite interferometry for regional assessment of landslide hazard to pipelines in northeastern British Columbia, Canada. International Journal of Applied Earth Observation and Geoinformation, 118, 103273, https://doi.org/10.1016/j.jag.2023.103273
  • Samsonov, S.V., Feng, W., Blais-Stevens, A., & Eaton, D.W. (2024). Ground deformation due to natural resource extraction in the Western Canada Sedimentary Basin. Remote Sensing Applications: Society and Environment, 34, 101159. ISSN 2352-9385. https://doi.org/10.1016/j.rsase.2024.101159

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

4D

  • Samsonov, S., Tiampo, K., & Cassotto, R. (2021). SAR-derived flow velocity and its link to glacier surface elevation change and mass balance. Remote Sensing of Environment, 258, 112343. https://doi.org/10.1016/j.rse.2021.112343
  • Samsonov, S., Tiampo, K., & Cassotto, R. (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
  • Samsonov, S.V., Blais-Stevens, A., 2024. Estimating volume of large slow-moving deep-seated landslides in northern Canada from DInSAR-derived 2D and constrained 3D deformation rates. Remote Sensing of Environment, 305, 114049, https://doi.org/10.1016/j.rse.2024.114049