Abstract

Abstract. A methodology based on Persistent Scatterer Interferometry (PSI) is proposed in order to disentangle the contribution of different processes that act at different spatio-temporal scales in land subsidence (i.e. vadose zone processes as swelling/shrinkage of clay soils, soil consolidation and fluid extraction). The methodology was applied in different Italian geological contexts characterized by natural and anthropic processes (i.e. a Prealpine valley and the Po Plain in northern Italy).

Highlights

  • Persistent Scatterer Interferometry (PSI) technique has significantly upgraded our ability to detect and quantify the land subsidence over wide areas

  • A methodology based on Persistent Scatterer Interferometry (PSI) is proposed in order to disentangle the contribution of different processes that act at different spatio-temporal scales in land subsidence

  • PSI data elaborated by Tele-Rilevamento Europa (T.R.E.) using images acquired by ERS 1-2 (1992–2000) and RADARSAT (2003–2010) satellites were used

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Summary

Introduction

Persistent Scatterer Interferometry (PSI) technique has significantly upgraded our ability to detect and quantify the land subsidence over wide areas. The PSI technique shows two main limitations: (1) the PSI measurements represent the cumulative ground movements (natural plus anthropic and superficial plus deep displacements); the overlapping of several causes may make difficult the interpretation of ground deformation processes; (2) most of the geological processes are non-linear with seasonal and multiyear components, which are difficult to identify only through the use of the average rate of displacements VLOS (velocity along the Line of Sight). This work presents a methodology to analyse the ground deformations in order to disentangle the contribution of different processes that act at different spatio-temporal scales (i.e. swelling/shrinkage of clay soils, soil consolidation and fluid extraction), by the integration of PSI data and ground-based measurements

Study areas
PSI datasets
Methodology
Post-processing elaborations
Characterization of the subsidence areas
Mechanism recognition
Conclusions
Full Text
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