Evaluation of subsidence induced by long-lasting buildings load using InSAR technique and geotechnical data: The case study of a Freight Terminal (Tuscany, Italy)

Ciampalini, Andrea Solari, Lorenzo Giannecchini, Roberto Galanti, Yuri Moretti, Sandro

Evaluation of subsidence induced by long-lasting buildings load using InSAR technique and geotechnical data: The case study of a Freight Terminal (Tuscany, Italy)

Ciampalini, Andrea 1Solari, Lorenzo 2Giannecchini, Roberto 1Galanti, Yuri 1Moretti, Sandro2
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作者信息

  • 1. Univ Pisa, Dipartimento Sci Terra, I-56126 Pisa, Italy
  • 2. Univ Firenze, Dipartimento Sci Terra, Via G La Pira 4, I-50121 Florence, Italy
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Abstract

This paper shows the results of the comparison between Multi-temporal Synthetic Aperture Radar (MTInSAR) products derived from different sensors (C-band ERS 1/2, Envisat, Sentinel-1 and X-band COSMO-SkyMed) and geotechnical data to investigate the driving factors of subsidence which affect a freight terminal located along the a coastal plain of Tuscany (central Italy). MTInSAR data have been acquired in a very long period, between 1992 and 2018 and were analyzed in terms of subsidence rates and deformation time series at building scale. The obtained results show that the oldest buildings are still affected by a deformation rate close to - 5 mm/yr, whereas recent buildings register rates around -40 mm/yr. Time series of deformation suggest that the deformation rates decrease over time following time-dependent trend that approximates the typical consolidation curve for compressible soils. The geotechnical and stratigraphical analysis of the subsurface data (boreholes, cone penetration tests and dilatometer tests) highlights the presence of a 15 m thick layer formed of clay characterized by poor geotechnical characteristics. The comparison among InSAR data, subsurface geological framework and geotechnical reconstruction suggests a possible evaluation of the timing of the primary and secondary consolidation processes.

Key words

Subsidence/InSAR data/Geotechnical data/Compressibility/Consolidation process/Tuscany

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出版年

2019
International journal of applied earth observation and geoinformation

International journal of applied earth observation and geoinformation

SCI
ISSN:0303-2434
被引量12
参考文献量47
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