Abstract
Multisensor data-fusion corresponds to the combination and analysis of data from different sources, to provide a more reliable and accurate response. Although in the recent years several developments have occurred in the field of multisensor data-fusion, this concept is hardly new. What has evolved in the past years is the emergence and proliferation of new sensors, data availability and the advances in processing techniques, which have made the real-time fusion of data increasingly possible. In this paper, InSar and Lidar height measurements are used in combination with geological scenarios and CPTs to discover areas along dike-infrastructure which are at risk for instability. It will be shown that data-fusion can be used on line infrastructure to identify geotechnical threats and their significance, in time and in space.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Ardalan, A., Jafari, M.: Multi-sensor approach to settlement analysis of earth dams. Comput. Geosci. 16(1), 123–138 (2012)
Bellsky, T., Kostelich, E., Mahalov, A.: Kalman filter data assimilation: targeting observations and parameter estimation. Chaos: Interdisc. J. Nonlinear Sci. 24(2), 024,406 (2014). https://doi.org/10.1063/1.4871916
Cressie, N.: The origins of kriging. Math. Geol. 22(3), 239–252 (1991)
Deltares: Geen partij kan dit alleen oplossen (in dutch). Deltalife (2017). https://media.deltares.nl/deltalife/8/nl/10/
Florea, M.C., Jousselme, A.L., Bossé, É.: Fusion of imperfect information in the unified framework of random sets theory: application to target identification. Technical report, Defence Research and Development Canada Valcartier (2007)
Forsberg, R., Skourup, H.: Arctic ocean gravity, geoid and sea-ice freeboard heights from icesat and grace. Geophys. Res. Lett. 32(21), 1–4 (2005). https://doi.org/10.1029/2005GL023711
Hall, D.L., Llinas, J.: Introduction to multisensor data fusion. Proc. IEEE 85, 6–23 (1997)
Hijma, M., Lam, K.S.: Globale stochastische ondergrondschematisatie (WTI-SOS) voor de primaire waterkeringen (in dutch). Technical report, Joint Directors of Labs Washington DC (1991)
Hung, W.C., Hwang, C., Chen, Y.A., Chang, C.P., Yen, J.Y., Hooper, A., Yang, C.Y.: Surface deformation from persistent scatterers SAR interferometry and fusion with leveling data: a case study over the Choushui River Alluvial Fan, Taiwan. Remote Sens. Environ. 115(4), 957–967 (2011). https://doi.org/10.1016/j.rse.2010.11.007
Kalman, R.E.: A new approach to linear filtering and prediction problems. Trans. ASME–J. Basic Eng. 82(Series D), 35–45 (1960)
Llinas, J., Hall, D.L.: Multisensor data fusion. In: Handbook of Multisensor Data Fusion, pp. 21–34. CRC Press (2008)
Luo, R.C., Yih, C.C., Su, K.L.: Multisensor fusion and integration: approaches, applications, and future research directions. IEEE Sens. J. 2(2), 107–119 (2002). https://doi.org/10.1109/JSEN.2002.1000251
McKenna, S.A., Poeter, E.P.: Field example of data fusion in site characterization. Water Resour. Res. 31(12), 3229–3240 (1995). https://doi.org/10.1029/95WR02573
Porter, D.W., Gibbs, B.P., Jones, W.F., Huyakorn, P.S., Hamm, L., Flach, G.P.: Data fusion modeling for groundwater systems. J. Contam. Hydrol. 42(2), 303–335 (2000). https://doi.org/10.1016/S0169-7722(99)00081-9
Robertson, P.: Soil classification using the cone penetration test. Can. Geotech. J. 27(1), 151–158 (1990)
Smith, D., Singh, S.: Approaches to multisensor data fusion in target tracking: a survey. IEEE Trans. Knowl. Data Eng. 18(12), 1696–1710 (2006). https://doi.org/10.1109/TKDE.2006.183
White, F.E.: Data fusion lexicon. Technical report, Joint Directors of Labs Washington DC (1991)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Noordam, A., Zuada Coelho, B., Teixeira, A., Venmans, A. (2020). Data-Fusion in Geotechnical Applications. In: Correia, A., Tinoco, J., Cortez, P., Lamas, L. (eds) Information Technology in Geo-Engineering. ICITG 2019. Springer Series in Geomechanics and Geoengineering. Springer, Cham. https://doi.org/10.1007/978-3-030-32029-4_31
Download citation
DOI: https://doi.org/10.1007/978-3-030-32029-4_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-32028-7
Online ISBN: 978-3-030-32029-4
eBook Packages: EngineeringEngineering (R0)