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The characterization of landslides located in remote areas poses significant challenges due to the costs of reaching the sites and the lack of reliable subsurface data to constrain geological interpretations. In this paper, the advantages of combining field and remote sensing techniques to investigate the deformation and stability of rock slopes are demonstrated. The characterization of the Fels landslide, a large, slowly deforming rock slope in central Alaska, is described. Historical aerial imagery is used to highlight the relationship between glacier retreat and developing instability. Airborne laser scanning (ALS) and Structure-from-Motion (SfM) datasets are used to investigate the structural geological setting of the landslide, revealing a good agreement between structural discontinuities at the outcrop and slope scales. The magnitude, plunge, and direction of slope surface displacements and their changes over time are studied using a multi-temporal synthetic aperture radar speckle-tracking (SAR ST) dataset. The analyses show an increase in displacement rates (i.e., an acceleration of the movement) between 2010 and 2020. Significant spatial variations of displacement direction and plunge are noted and correlated with the morphology of the failure surface reconstructed using the vector inclination method (VIM). In particular, steeper displacement vectors were reconstructed in the upper slope, compared to the central part, thus suggesting a change in basal surface morphology, which is largely controlled by rock mass foliation. Through this analytical approach, the Fels landslide is shown to be a slow-moving, compound rockslide, the displacement of which is controlled by structural geological features and promoted by glacier retreat. [ABSTRACT FROM AUTHOR]

In fire-prone ecosystems, periodic fires are vital for ecosystem functioning. Fire managers seek to promote the optimal fire regime by managing fire season and frequency requiring detailed information on the extent and date of previous burns. This paper investigates a Normalised Difference α-Angle (NDαI) approach to burn-scar mapping using C-band data. Polarimetric decompositions are used to derive α-angles from pre-burn and post-burn scenes and NDαI is calculated to identify decreases in vegetation between the scenes. The technique was tested in an area affected by a wildfire in January 2016 in theWestern Cape, South Africa. The quad-pol H-A-α decomposition was applied to RADARSAT-2 data and the dual-pol H-α decomposition was applied to Sentinel-1A data. The NDαI results were compared to a burn scar extracted from Sentinel-2A data. High overall accuracies of 97.4% (Kappa = 0.72) and 94.8% (Kappa = 0.57) were obtained for RADARSAT-2 and Sentinel-1A, respectively. However, large omission errors were found and correlated strongly with areas of high local incidence angle for both datasets. The combined use of data from different orbits will likely reduce these errors. Furthermore, commission errors were observed, most notably on Sentinel-1A results. These errors may be due to the inability of the dual-pol H-α decomposition to effectively distinguish between scattering mechanisms. Despite these errors, the results revealed that burnt areas could be extracted and were in good agreement with the results from Sentinel-2A. Therefore, the approach can be considered in areas where persistent cloud cover or smoke prevents the extraction of burnt area information using conventional multispectral approaches. [ABSTRACT FROM AUTHOR]