Landslide expression in C-band SAR backscatter change images: a physically- and empirically-based conceptual model

Using synthetic aperture radar (SAR) backscatter imagery can enable faster detection of landslides compared to optical images, particularly where there is persistent cloud cover or shadows. However, SAR images are underutilised for this purpose. This is partly due to the more complicated pre-processing requirements, and also due to the less intuitive interpretation of landslide signatures in SAR, relative to optical images. The problem of landslide identification in SAR backscatter imagery is complex. Landslides can occur in almost any land cover type and their expression in the environment can vary significantly depending on the material type and failure mechanisms. How this affects the expression of landslides in SAR backscatter data has so far not been well understood. In this study, we attempt to reduce this knowledge gap by investigating the physical basis for the expression of landslides in SAR backscatter data.

This involved identifying trends in the spatial and temporal signatures of landslides in 30 case studies around the world, representing diverse physiographical and landslide types. Morphometric features of landslides (scarp, transport and deposition zone) were mapped separately, and quantitative analysis of their pixel values in multi-temporal Sentinel-1 SAR backscatter images was performed. The role of environmental factors including the orientation of the landslide with respect to the sensor (local incidence angle), land cover, seasonal variations, and water content were also analysed.

The terrain influenced whether or not landslides were detectable, while the presence or absence of woody vegetation determined if there would be an increase or decrease in backscatter intensity. Landslides in non-forested areas that produce an increase in surface roughness, are best observed using VV polarisation and show increased backscatter intensity. Deposit zones also tend to show increased backscatter intensity, unless very fine material was deposited as a smooth flat surface (e.g. from non-turbulent mudflows). Removal of the forest is best viewed in VH polarisation, and produces a recognisable pattern of both decreased (due to radar shadow, and change from volumetric to surface scattering) and increased (due to direct and double bounce reflection from vertical tree trunks and scarp surface) backscatter intensity. Landslides that occur in mixed vegetation types, and those that do not significantly change the scattering properties of the ground surface, did not produce a detectable change in the C-band SAR images.  

The findings were summarised in a conceptual model, based on SAR theory and empirical evidence. This can be used to help interpret landslides in SAR backscatter change images, and to design representative or synthetic datasets for training automatic landslide detection models.