Digital Image Correlation (DIC) Analysis of the 3 December 2013 Montescaglioso Landslide (Basilicata, Southern Italy): Results from a Multi-Dataset Investigation

Paolo Caporossi,Francesca Bozzano,Paolo Mazzanti

doi:10.3390/ijgi7090372

Paolo Caporossi, Francesca Bozzano + Show 1 more

Open Access

https://doi.org/10.3390/ijgi7090372

Copy DOI

Abstract

Image correlation remote sensing monitoring techniques are becoming key tools for providing effective qualitative and quantitative information suitable for natural hazard assessments, specifically for landslide investigation and monitoring. In recent years, these techniques have been successfully integrated and shown to be complementary and competitive with more standard remote sensing techniques, such as satellite or terrestrial Synthetic Aperture Radar interferometry. The objective of this article is to apply the proposed in-depth calibration and validation analysis, referred to as the Digital Image Correlation technique, to measure landslide displacement. The availability of a multi-dataset for the 3 December 2013 Montescaglioso landslide, characterized by different types of imagery, such as LANDSAT 8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor), high-resolution airborne optical orthophotos, Digital Terrain Models and COSMO-SkyMed Synthetic Aperture Radar, allows for the retrieval of the actual landslide displacement field at values ranging from a few meters (2–3 m in the north-eastern sector of the landslide) to 20–21 m (local peaks on the central body of the landslide). Furthermore, comprehensive sensitivity analyses and statistics-based processing approaches are used to identify the role of the background noise that affects the whole dataset. This noise has a directly proportional relationship to the different geometric and temporal resolutions of the processed imagery. Moreover, the accuracy of the environmental-instrumental background noise evaluation allowed the actual displacement measurements to be correctly calibrated and validated, thereby leading to a better definition of the threshold values of the maximum Digital Image Correlation sub-pixel accuracy and reliability (ranging from 1/10 to 8/10 pixel) for each processed dataset.

Highlights

Landslides are among the most diffuse natural hazards, and each year, they lead to significant human, economic and societal losses [1,2,3,4,5]
- DTRMeg; aarnddin, g the Digital Image Correlation (DIC) analyses performed on the pre-post digital terrain models (DTMs), a number of surface operations - weHreigphe-rrfeosromluetdioinn AtheeriGalISOepntivciarol nImmaegnet,s.and eight shaded reliefs were generated
To better calibrate and validate the DIC analyses performed on the absolute Synthetic Aperture Radar (SAR) amplitude images, a temporal average filtering process was applied to the available ascending and descending CSK datasets (Figures 4 and 5)

Summary

Introduction

Landslides are among the most diffuse natural hazards, and each year, they lead to significant human, economic and societal losses [1,2,3,4,5]. Remote sensing techniques have become key tools that can provide qualitative and quantitative information suitable for landslide investigations and monitoring, even in emergency situations [6,7,8,9,10,11,12,13,14,15,16,17]. Image correlation techniques have been used to measure ground deformation [24], volcanic slope spreading [25], glacier-flow tracking [26,27,28] and earthquake-induced displacement [29,30], and for landslide monitoring [31,32,33,34]

Objectives

Methods

Results

Conclusion