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Landslide monitoring is a global challenge that can take strong advantage from opportunities offered by Earth Observation (EO). The increasing availability of constellations of small satellites (e.g., CubeSats) is allowing the collection of satellite images at an incredible revisit time (daily) and good spatial resolution. Furthermore, this trend is expected to grow rapidly in the next few years. In order to explore the potential of using a long stack of images for improving the measurement of ground displacement, we developed a new procedure called STMDA (Slide Time Master Digital image correlation Analyses) that we applied to one year long stack of PlanetScope images for back analyzing the displacement pattern of the Rattlesnake Hills landslide occurred between the 2017 and 2018 in the Washington State (USA). Displacement maps and time-series of displacement of different portions of the landslide was derived, measuring velocity up to 0.5 m/week, i.e., very similar to velocities available in literature. Furthermore, STMDA showed also a good potential in denoising the time-series of displacement at the whole scale with respect to the application of standard DIC methods, thus providing displacement precision up to 0.01 pixels.The most common optical satellite missions (e.g., QuickBird, SPOT, LANDSAT, Sentinel-2, WorldView, Pléiades, just to mention few of them) are characterized by spatial resolution ranging between 0.3 and 30 m and a revisit time of some days [25][26][27], therefore, they are not fully adequate to detect landslides at a spatial and temporal scale suitable for continuous monitoring. However, as stated in [4,28], the fusion of images collected by different optical satellite sensors has certainly increased the opportunities for cloud-free surface investigation, thus allowing also a general improvement of the temporal resolution.In the last few years, EO has been affected by an astonishing sensor and platform development and improvement, thanks to small satellites. According to [27,29,30], among the main features of these satellites, properly named CubeSats, there are: (i) the general small size and weight (a single-unit of CubeSat normally measures 10 × 10 × 11 cm and typically weights less than 1.5 kg), (ii) high geometric resolution (~3-5 m/pixel) and (iii) daily/near-daily revisit time. CubeSats represent a cost-effective EO strategy, allowing unique chances for a wide variety of application fields [8,31].Planet Labs Inc. has recently made available a large constellation (> 130 units) of optical 3-U CubeSats (10 × 10 × 30 cm), also called PlanetScope or, more commonly, "Doves" [27,30,[32][33][34]. With an average orbit height of about 475 km a.s.l., the main CCD array sensor is able to collect images of 7000 × 2000 pixels, with a footprint of approximately 24 × 8 km 2 . Each Doves collects one image/second along his orbit with a slight overlapping between consecutive scenes. In this way, taking advantage of the whole constellation, images at a daily sampling rate are achievable, thus allowing to ...

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.

On 19th March 2010, a 4 million m 3 landslide was re-activated in Poggio Baldi. The landslide severely damaged some private houses, a regional road and dammed the Bidente River. The landslide can be classified as a complex movement started as a rotational slide and then evolved into an earthflow. The 2010 event was a re-activation of an ancient landslide, whose previous catastrophic activation is dated back to March 1914. Starting from 2010, the landslide has been monitored by permanent inclinometers, piezometers and extensometers. Then, from 2015 an Experimental Landslide Monitoring Site has been developed mainly for research purposes and several multi-temporal surveys have been performed by using different remote sensing techniques, such as Terrestrial Laser Scanning, Global Positioning System, Unmanned Aerial Vehicles Photogrammetry, Digital Image Correlation, Terrestrial Interferometric SAR. The Experimental Landslide Monitoring site demonstrated to be a great opportunity for both research and training purposes, as well as a place where monitoring instrument can be tested and calibrated.

Montescaglioso village is located in southern Italy (Matera, Basilicata region), on a hill top, at about 350 m a.s.l., along the left bank of the Bradano River. Several landslides involved this area, some of them classified as relict; the latest one occurred on December 3rd, 2013 on the south-western slope of Montescaglioso hill. A review of the geological setting of this slope is presented, aimed at defining the failure mechanism of the slope. Sub-pixel cross-correlation analysis based on SAR images was performed to infer the co-failure displacement pattern and A-DInSAR was carried out to detect the spatial-temporal deformational pattern before and after the failure. The field surveys confirmed the main role played by geological setting in structurally constraining the landslide mechanism and its complex kinematic, featured by three main distinct "kinematic blocks" with different direction of movement. The 3rd December landslide has been recognized as a partial reactivation along a slope affected by a long-lasting sequence of landslides, the last one triggered by a transient action.

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On 19 March 2010, a 4 million m3 landslide occurred at Poggio Baldi, a small village in the Santa Sofia municipality, central Apennines (Forlì-Cesena, Italy). The landslide caused severe damages to some homes and obstructed both the SS310 national road and the Bidente river. The Poggio Baldi landslide arose in the “Marnoso-Arenacea Romagnola” formation composed of a pelitic-arenaceous turbiditic sequence. The landslide was classified as a rotational landslide, evolving into a partially confined flow-like landslide and causing the reactivation of the deposit of a previous landslide that took place in 1914. This paper reports a study of the phenomena currently occurring on the 100-m high main scarp of this landslide complex. The aim of the study was to assess ground changes that occurred on the upper scarp from 2015 to 2018 and to infer a preliminary evolutionary model capable of supporting short-term landslide scenarios. For this purpose, multi-station terrestrial laser scanner surveys were performed in 2015, 2016, 2017, and 2018. Additionally, an unmanned aerial vehicle three-dimensional photogrammetric survey was carried out in 2016. Analyses of the three-dimensional digital models of the main scarp made it possible to carry out several exhaustive multi-temporal investigations and to derive a detailed three-dimensional change detection scheme for it. The results showed an active geomorphological evolution of the rock scarp area due to frequent rockfalls and topples (of the order of a few m3), with significant local volume changes (a few thousand m3/year) and with potential implications for the long-term evolution of the entire slope.

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