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Mapping Snow for Area Where was Detected Ground Deplacement: A Case Studi of Iaşi County

Paul Macarof
  • ”Gheorghe Asachi” Technical University of Iasi, Faculty of Hydrotechnical Engineering, Geodesy and Environmental Engineering
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/ Cezarina Georgiana Bartic Lazăr
  • ”Gheorghe Asachi” Technical University of Iasi, Faculty of Hydrotechnical Engineering, Geodesy and Environmental Engineering
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/ Florian Statescu
Published Online: 2018-11-14 | DOI: https://doi.org/10.2478/pesd-2018-0038


The main goal of this paper is to detect snow in areas where was detecting and mapping, using Differential Radar Interferometry (DInSAR) technique, ground displacement. DInSAR is a powerful tool to detect and monitor ground deformation. Iaşi county is considered as study area in this research. Study area is geographically situated on latitude 46°48’N to 47°35’N and longitude 26°29’E to 28°07’E. For this paper, to detect and mapping grond displacement, was used Sentinel – 1 images, provided free by The European Space Agency (ESA), for January 2018, with vertical polarization (VV), ascending orbit and Interferometric Wide swath (IW) mode operated. SNAP was used to process the Sentinel – 1 images. Landsat-8 OLI was taken to detect areas cover with snow using Normalized Difference Snow Index (NDSI) - a numerical indicator that shows snow cover over land areas. ArcMap was used to create NDSI map after Landsat-8 data was preprocessed. The presence of snow has been observed both in the areas where it exists vertical displacement positive and negative.

Keywords: detected ground displacement; Sentinel; NDSI; Landsat


  • Bell JW., Amelung F., Novali F., Ferretti A., Bianchi M., 2008, Permanent scatterer (PS) InSAR reveals seasonal and long - term aquifer-system response to groundwater pumping and artificial recharge, Water Resources Research, vol. 44(2).Google Scholar

  • Berardino P., Fornaro Gf., Lanari R., Sansosti E., 2002, A new algorithm for surface deformation monitoring based on SBAS - small baseline differential SAR interferograms, IEEE Geoscience and Remote Sensing Society, vol. 40(11), pp: 2375 – 2383.Google Scholar

  • Borgia A., Tizzani P., Solaro G., Manzo M., Casu F., Luongo G., Pepe A., Berardino P., Fornaro G., Sansosti E., Ricciardi G.P., Fusi N., Di Donna G., Lanari R., 2005, Volcanic spreading of Vesuvius, a new paradigm for interpreting its volcanic activity G. Re. Letters, vol. 32, [L03303], doi:10.1029/2004GL022155.Google Scholar

  • Bovenga F., Wasowski J., Nitti D. O., Nutricato R., Chiaradia M.T., 2012, sing COSMO/SkyMed X-band and ENVISAT C-band SAR interferometry for landslides analysis, Remote Sensing of Environment, vol. 119, pp: 272-285.Google Scholar

  • Cascini L., Fornaro G., Peduto D., 2009, Analysis at medium scale of low-resolution DInSAR data in slow-moving landslide-affected areas, ISPRS Journal of Photogrammetry and Remote Sensing, vol. 64(6), pp: 598-611.Google Scholar

  • Cascini L., Fornaro G., Peduto D., 2010, Advanced low and full-resolution DInSAR map generation for slow-moving landslide analysis at different scales. In press on Engineering Geology, vol. 112(1-4), pp: 29-42.Google Scholar

  • Crosetto M., Monserrat O., Cuevas-González M., Devanthéry N., Crippa B., 2016, Persistent Scatterer Interferometry: A review, ISPRS Journal of Photogrammetry and Remote Sensing, vol. 115, pp: 78–89.Google Scholar

  • Dixon T.H., Amelung F., Ferretti A., Novali F., Rocca F., Dokka R., Sella G., Kim S.W., Wdowinski S., Whitman D., 2006, Space geodesy: Subsidence and flooding in New Orleans, Nature, vol. 441, pp: 587–588.Google Scholar

  • Ferretti A., Prati, Rocca F., 2000, Analysis of Permanent Scatterers (PS) in SAR interferometry, IEEE Transactions on Geoscience and Remote Sensing vol.2, 39(1) pp: 761 – 763.Google Scholar

  • Ferretti A., Prati C., Rocca F., 2001, Permanent scatterers (PS) in SAR interferometry, IEEE Geoscience and Remote Sensing Soc., vol. 39(1), pp: 8 – 20.Google Scholar

  • Guzzetti F., Ardizzone F., Cardinali M., Rossi M., Valigi D., 2009, Landslide Volumes and Landslide Mobilization Rates in Umbria, Central Italy, Earth and Planetary Science Letters, vol. 279. Pp: 222-229.Google Scholar

  • Hanssen R.F., 2001, Doctoral thesis: Radar interferometry: Data interpretation and error analysis.Google Scholar

  • Hilley G.E,, Bürgmann R., Ferretti A., F Novali, Rocca F., 2004, Dynamics of slow moving-landslides from PS analysis, Science, vol. 304 (5679), pp: 1952-1955.Google Scholar

  • Hooper D., Coughlan J., Mullen M., 2008, Structural Equation Modelling: Guidelines for Determining Model Fit, Electronic Journal of Business Research Methods, vol. 6(1), pp: 53-60.Google Scholar

  • Lanari R., Berardin, P., Bonano M., Casu F., Manconi A., Manunta M., Manzo M., Pepe A., Pepe S., Sansosti E., Solaro G., Tizzani P., Zeni G., 2010, Surface displacements associated with the L’Aquila 2009 Mw6.3 earthquake (Central Italy): New evidence from SBAS - DInSAR time series analysis Geophysical Research Letters, 37, L20309.Google Scholar

  • Massonnet D., Briole P., Arnaud A., 1995, Deflation of Mount Etna monitored by spaceborne radar interferometry, Nature, 375, pp: 567–570.Google Scholar

  • Massonnet D., Feigl K., 1998, Radar interferometry and its application to changes in the Earth’s surface. Reviews of Geophysics. vol. 36, pp: 441-500Google Scholar

  • Massonnet D., Rossi M., Carmona C., Adragna F., Peltzer G., Feigl K., Rabaute T., 1993, The displacement field of the Landers earthquake mapped by radar interferometry, Nature, vol. 364, pp:138–142.Google Scholar

  • Margarit M.C., Niculita M., Local stakeholders’ perception of natural risks. Case study of Iaşi County, NE Romania, Analysis and Management of Changing Risks for Natural Hazard, 2014.Google Scholar

  • Mora O., Mallorqui J.J., Broquetas A., 2003, Linear and nonlinear terrain deformation maps from a reduced set of interferometric SAR images, IEEE Geoscience and Remote Sensing Society, vol. 41(10), pp: 2243 – 2253.Google Scholar

  • Werner C., Wegmuller U., Wiesmann A., Strozzi T., 2003, Interferometric point target analysis for deformation mapping, Proceedings, IEEE Int 7:4362, 4364, pp: 21-25.Google Scholar

  • Zebker H.A., Rosen P.A., Hensley S., 1997, Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps, Journal of Geophysical Research, 102(B4), pp: 7547-7563.Google Scholar

  • * * * miningeology.blogspotGoogle Scholar

  • * * * eos.com/ndsi/Google Scholar

  • * * * www.nasa.gov

About the article

Published Online: 2018-11-14

Published in Print: 2018-10-01

Citation Information: Present Environment and Sustainable Development, Volume 12, Issue 2, Pages 167–174, ISSN (Online) 2284-7820, DOI: https://doi.org/10.2478/pesd-2018-0038.

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© 2018 Paul Macarof et al., published by Sciendo. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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