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Combined use of statistical and DInSAR data analyses to define the state of activity of slow-moving landslides

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Abstract

Statistical analyses have been often used for landslide susceptibility zoning at small to medium scale when relevant base and thematic maps are available. Since the beginning of the last decade, images remotely acquired by spaceborne Synthetic Aperture Radar (SAR) and processed via Differential SAR Interferometry (DInSAR) proved extremely useful for non-invasive and non-destructive monitoring of displacements of the topographic surface. The present paper proposes an original procedure for the definition of the state of activity of slow-moving landslides via the combined use of multivariate statistical analyses and DInSAR data. The procedure is based on the following essential elements: distinction between terrain units used for computational purposes and the final zoning units; independent statistical and DInSAR analyses and activity models leading to first-level state of activity zoning maps; a consistency model between statistical and DInSAR analyses; two confidence and combination models leading, respectively, to second- or third-level state of activity zoning maps. The application in a test area including 19 municipalities in southern Italy, where slow-moving landslides are widespread and accurately mapped by using geomorphological criteria, allowed the generation of the three above-mentioned levels of zoning maps. The results were successfully crosschecked by exploiting a different DInSAR dataset and the results of previous works based on the use of slow-moving landslide-induced damage to facilities surveys.

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Abbreviations

DInSAR:

Differential SAR Interferometry

H:

High activity

hc:

High confidence

IAD :

DInSAR Index of Activity

IAS :

Statistical Index of Activity

ICM/A :

True positives Consistency Index

ICNM/NA :

True negatives Consistency Index

L:

Low activity

lc:

Low confidence

M:

Medium activity

TCU:

Terrain Computational Unit

TCUa :

Active Terrain Computational Unit

TCUc :

Terrain Computational Unit covered by DINSAR data

TCUcm :

Terrain Computational Unit covered by DINSAR data and moving

TCUM/A :

Terrain Computational Unit moving according to the DInSAR analysis and active according to the statistical analysis

TCUM/NA :

Terrain Computational Unit moving according to the DInSAR analysis and not active according to the statistical analysis

TCUNM/A :

Terrain Computational Unit not moving according to the DInSAR analysis and active according to the statistical analysis

TCUNM/NA :

Terrain Computational Unit not moving according to the DInSAR analysis and not active according to the statistical analysis

TCUtot :

Total number of Terrain Computational Units

TZU:

Terrain Zoning Unit

VL:

Very Low activity

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Acknowledgments

The authors are grateful to the National Basin Authority of Liri-Garigliano and Volturno rivers, and in particular, to the general secretary Vera Corbelli, for furnishing all the thematic maps of the study area. The authors also wish to thank Italian Ministry of the Environment and Protection of Land and Sea, and in particular, Dr. Salvatore Costabile, for providing the PSI data of the study area deriving from the Piano Straordinario di Telerilevamento Ambientale. The present work was partially funded by the PRIN project (Programmi di ricerca scientifica di rilevante interesse nazionale) “La mitigazione del rischio da frana mediante interventi sostenibili” supported by Italian Ministry of Education, University and Research, call 2010–2011.

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  1. Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II 132, 84084, Fisciano, SA, Italy

    Michele Calvello, Dario Peduto & Livia Arena

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  1. Michele Calvello
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Correspondence to Michele Calvello.

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Calvello, M., Peduto, D. & Arena, L. Combined use of statistical and DInSAR data analyses to define the state of activity of slow-moving landslides. Landslides 14, 473–489 (2017). https://doi.org/10.1007/s10346-016-0722-6

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