Digital image correlation (DIC) analysis of the 3 December 2013 Montescaglioso landslide (Basilicata, Southern Italy). Results from a multi-dataset investigation

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

Revisiting Past Earthquakes and Seismo-Volcanic Crises Using Declassified Optical Satellite Imagery

Recent development of the user-friendly software package “Co-registration of Optically Sensed Images and Correlation” (COSI-Corr), which allows for automatic and precise ortho-rectification, co-registration, and sub-pixel correlation of pushbroom satellite and aerial images, has enabled Earth’s surface dynamics to be accurately monitored using optical imagery [1]. This technique compares two images of the Earth’s surface that were acquired at different times, and estimates any potential pixel shifts between them with an accuracy typically better than 1/10 of the pixel size. Correlation of both satellite and aerial images has been successfully used to identify coseismic ground ruptures and quantify fault offsets during large earthquakes [2]–[4], as well as monitoring sand dune migration, landsliding, ice flow [5] [6], and volcanic activity [7] [8]. In this study, we demonstrate that recently declassified US spy satellite images can be used to measure ground deformation resulting from seismotectonic and volcanic events using optical sub-pixel correlation. KH-9 Hexagon satellite images, with a swath size of 250×125 km, were acquired by the US government between 1971 and 1980, and are available for purchase from the United States Geological Survey (USGS) at small cost ($30 per image). During this period, around 29,000 images were acquired globally [9], providing a comprehensive record of the Earth’s surface at 6–9m resolution

Revisiting Past Earthquakes and Seismo-Volcanic Crises Using Declassified Optical Satellite Imagery

Recent development of the user-friendly software package “Co-registration of Optically Sensed Images and Correlation” (COSI-Corr), which allows for automatic and precise ortho-rectification, co-registration, and sub-pixel correlation of pushbroom satellite and aerial images, has enabled Earth’s surface dynamics to be accurately monitored using optical imagery [1]. This technique compares two images of the Earth’s surface that were acquired at different times, and estimates any potential pixel shifts between them with an accuracy typically better than 1/10 of the pixel size. Correlation of both satellite and aerial images has been successfully used to identify coseismic ground ruptures and quantify fault offsets during large earthquakes [2]–[4], as well as monitoring sand dune migration, landsliding, ice flow [5] [6], and volcanic activity [7] [8]. In this study, we demonstrate that recently declassified US spy satellite images can be used to measure ground deformation resulting from seismotectonic and volcanic events using optical sub-pixel correlation. KH-9 Hexagon satellite images, with a swath size of 250×125 km, were acquired by the US government between 1971 and 1980, and are available for purchase from the United States Geological Survey (USGS) at small cost ($30 per image). During this period, around 29,000 images were acquired globally [9], providing a comprehensive record of the Earth’s surface at 6–9m resolution