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      Airborne combined photogrammetry—infrared thermography applied to landslide remote monitoring

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          Abstract

          The combination between two remote surveying methods is presented herein as a pioneering approach for landslide airborne monitoring. The survey of an active landslide by UAV-based RGB photogrammetry and infrared thermography, sided by the knowledge of the field condition, allowed increasing the scientific experience on the remote sensing of slope instability phenomena by analyzing multiple aspects related to the evolution of key slope features. In this research, the state and distribution of activity of a landslide was monitored by matching data arising from three-dimensional models of the slope, built by exploiting the aerial RGB photogrammetric technology, and thermal outcomes, resulting from the airborne application of infrared thermography principles. In this frame, thermal anomalies detected during different monitoring campaigns allowed recognizing peculiar features along the unstable slope that could be related to specific kinematic elements involved in the landslide activity. Forming cracks, developing scarps, wet terrain portions, and loose material are some of the elements that could be located by integrating thermal outcomes with Digital Surface Models of the slope. Thanks to the different thermal behavior of such elements, strengthened herein by a novel approach of thermal data processing (i.e. the study of thermal slope profiles), the lateral and retrogressive evolution of the studied movement was first hypothesized and then verified in field. Achieved results show that the location of thermal anomalies well corresponds to field structures, which sometimes are hardly detectable by in situ or RGB surveys, thus suggesting the high potential of the methodological approach developed for this study. The scientific validity of presented data gains relevance thanks to the positive field validation. This paves the way to further studies aimed at implementing the infrared aerial survey of landslides, which surely could bring benefits to practical applications in terms of survey speed and spatial coverage, especially in areas characterized by bad field logistics.

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          Most cited references69

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          Unmanned aerial systems for photogrammetry and remote sensing: A review

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            Global fatal landslide occurrence from 2004 to 2016

            Abstract. Landslides are a ubiquitous hazard in terrestrial environments with slopes, incurring human fatalities in urban settlements, along transport corridors and at sites of rural industry. Assessment of landslide risk requires high-quality landslide databases. Recently, global landslide databases have shown the extent to which landslides impact on society and identified areas most at risk. Previous global analysis has focused on rainfall-triggered landslides over short ∼ 5-year observation periods. This paper presents spatiotemporal analysis of a global dataset of fatal non-seismic landslides, covering the period from January 2004 to December 2016. The data show that in total 55 997 people were killed in 4862 distinct landslide events. The spatial distribution of landslides is heterogeneous, with Asia representing the dominant geographical area. There are high levels of interannual variation in the occurrence of landslides. Although more active years coincide with recognised patterns of regional rainfall driven by climate anomalies, climate modes (such as El Niño–Southern Oscillation) cannot yet be related to landsliding, requiring a landslide dataset of 30+ years. Our analysis demonstrates that landslide occurrence triggered by human activity is increasing, in particular in relation to construction, illegal mining and hill cutting. This supports notions that human disturbance may be more detrimental to future landslide incidence than climate.
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              ‘Structure-from-Motion’ photogrammetry: A low-cost, effective tool for geoscience applications

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                Author and article information

                Contributors
                Journal
                Landslides
                Landslides
                Springer Science and Business Media LLC
                1612-510X
                1612-5118
                February 2023
                September 15 2022
                February 2023
                : 20
                : 2
                : 297-313
                Article
                10.1007/s10346-022-01970-z
                c360dad7-d38c-4322-8cc3-cfc4ec364343
                © 2023

                https://creativecommons.org/licenses/by/4.0

                https://creativecommons.org/licenses/by/4.0

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