Abstract
We present elements of technology for spatio-temporal data mining aimed at studying natural processes by temporal sequences. The methods considered are applied to the analysis of Earth’s surface deformations by GPS and InSAR measurements of ground displacements. Often, the study of earth deformation is limited to the analysis of average strain rates only. It is shown that inclusion of the temporal component of GPS data allows one to find the relationship between seismicity and dynamics of the fields of horizontal surface deformations. Accounting for the temporal component of InSAR data allows identifying urban areas of land, which differ not only in the intensity of deformations process, but also in the type of their dynamics. The methods considered are realized in GIS GeoTime 3 (http://www.geo.iitp.ru/GT3/).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Manso Callejo, M., Moldonado Ibanez, A., Hernandez Rey, R., Ballari, D., Moya Honduvilla, J.: GEOSISMO: Visualization of events and seismologic characteristics in the internet. Internet-Based Cartographic Teaching and Learning: Atlases, Map Use and Visual Analytics. Madrid Spain International Cartographic Association/Association Cartographique Internationale (2005)
Derendyaev, A., Gitis, V., Metrikov, P.: Detection of Earthquake Precursors in GIS GeoTime. In: 13th AGILE International Conference on Geographic Information Science, Guimaraes, Portugal (2010), http://plone.itc.nl/agile_old/Conference/2010-guimaraes/PosterAbstracts_PDF%5C116_DOC.pdf
Andrienko, N., Andrienko, G.: Exploratory analysis of spatial and temporal data. Springer, Berlin (2006)
Pultar, E., Cova, T.J., Yuan, M., Goodchild, M.F.: EDGIS: a dynamic GIS based on space time points. International Journal of Geographical Information Science 24(3), 329–346 (2010)
Gitis, V.G., Ermakov, B.V.: Fundamentals of spatio-temporal forecasting in geoinformatics, Moscow, Fizmatgis. p. 256 (2004) (In Russian)
Metrikov, P., Derendyaev, A., Gitis, V.: Web-GIS technology for dynamic data analysis. In: Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Querying and Mining Uncertain Spatio-Temporal Data, pp. 29–36. ACM (November 2011)
Ge, L., Chang, H.C., Janssen, V., Rizos, C.: Integration of GPS, radar interferometry and GIS for ground deformation monitoring. In: Proc. 2003 Int. Symp. on GPS/GNSS, Toyko, Japan, November 15-18, pp. 465–472 (2003)
Webster, T.L., Dias, G.: An automated GIS procedure for comparing GPS and proximal LiDAR elevations. Computers & Geosciences 32(6), 713–726 (2006)
Gitis, V.G., Derendyaev, A.B.: Geoinformation technology for spatio-temporal processes research. In: Proc. ISPRS Workshop on Dynamic and Multi-Dimensional GIS, Shanghai, China, pp. 111–115 (October 2011)
Gitis, V.G., Osher, B.V., Pirogov, S.A., Ponomarev, A.V., Sobolev, G.A., Jurkov, E.F.: A System for Analysis of Geological Catastrophe Precursors. Journal of Earthquake Prediction Research 3, 540–555 (1994)
Sobolev, G.A., Zakrzhevskaya, N.A., Akatova, K.N., Gitis, V.G., Derendyaev, A.B., Bragin, V.D., Sycheva, N.A., Kuzikov, S.I.: Dynamics of Interaction between Fields of Seismicity and Surface Deformations (Bishkek Geodynamic Test Area). Izvestiya Physics of the Solid Earth 46(10), 817–838 (2010)
Sobolev, G.A., Tyupkin, Y.S.: New method of intermediate-term earthquake prediction. European Seismological Commission XXV General Assembly Seismology in Europe, Reykjavik, Iceland, pp. 229–234 (1996)
Lanari, R., Zeni, G., Manunta, M., Guarino, S., Berardino, P., Sansosti, E.: An integrated SAR/GIS approach for investigating urban deformation phenomena: a case study of the city of Naples, Italy. International Journal of Remote Sensing 25(14), 2855–2867 (2004)
Yerro, A., Corominas, J., Mallorquí, J.J., Monells, D.: Analysis of the evolution of ground movements in a low densely urban area by means of DInSAR technique. Engineering Geology (2013)
Anderssohn, J., Motagh, M., Walter, T.R., Rosenau, M., Kaufmann, H., Oncken, O.: Surface deformation time series and source modeling for a volcanic complex system based on satellite wide swath and image mode interferometry: The Lazufre system, central Andes. Remote Sensing of Environment 113(10), 2062–2075 (2009)
Van Westen, C.J., Van Asch, T.W., Soeters, R.: Landslide hazard and risk zonation—why is it still so difficult? Bulletin of Engineering Geology and the Environment 65(2), 167–184 (2006)
Likhachev, B.: Clustering method of spatio-temporal sequences of satellite SAR interferometry. In: 2011 (ITaS 2011): 34 Conference of Young Scientists and Specialists of IITP RAS, pp. 151–155 (2011) (in Russian), http://itas2011.iitp.ru/pdf/1569460147.pdf
Dmitriev, P.N., Golubev, V.I., Isaev, Y.S., Kiseleva, E.A., Mikhailov, V.O., Smolianinova, E.I.: Some problems of InSAR data processing and interpretation for the monitoring of landslide process. Modern Problems of Remote Sensing of the Earth from Space 9(2), 130–144 (2012)
Kadlečík, P., Schenk, V., Seidlova, Z., Schenková, Z.: Analysis of vertical movements detected by radar interferometry in urban areas. Acta Geodyn. Geomater. 7(3(159)), 371–380 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Gitis, V., Derendyaev, A. (2014). Spatio-temporal Analysis of Earth’s Surface Deformation by GPS and InSAR Data. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8579. Springer, Cham. https://doi.org/10.1007/978-3-319-09144-0_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-09144-0_17
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09143-3
Online ISBN: 978-3-319-09144-0
eBook Packages: Computer ScienceComputer Science (R0)