The Landslide Blog is written by Dave Petley, who is widely recognized as a world leader in the study and management of landslides.
Over the course of my career, I have read many papers (and indeed, written a few) that have tried to explain the distribution of landslides based upon combinations of factors that we consider might be important in their causation (for example, slope angle and lithology). There is utility in this type of approach, and it has informed planning guidelines in some countries, for example. However, it also has severe limitations and, even with the advent of artificial intelligence, there have been few major advances in this area for a while.
However, there is a very interesting and thought-provoking paper (Zhang et al. 2025) in the Bulletin of Engineering Geology and the Environment that might stimulate considerable interest. One reason for highlighting it here is that it might drop below the radar – this is not a well-read journal in my experience, and the paper is behind a paywall. That would be a shame, but the link in this post should allow you to read the paper.
The authors argue that we tend to treat geological factors in a rather over-simplified way in susceptibility analyses:-
“The types, triggers, and spatial distribution of landslides are closely related to the spatial complexity of geological conditions, which are indispensable factors in landslide susceptibility assessment. However, geological conditions often consider only a single index, leading to under-utilisation of geological information in assessing landslide hazards.”
Instead, they propose the use of an index of “geological complexity”. This index combines four major geological components:
- Structural complexity – capturing dip direction, dip angle, slope and aspect;
- Lithologic complexity – this essentially uses a geological map to capture the number of lithologic types per unit area;
- Tectonic complexity – this is representing the density of mapped faults;
- Seismicity – this captures the distribution of the probability of peak ground accelerations.
Zhang et al. (2025) use an analytical approach to weight each of these factors to produce an index of geological complexity across the landscape. In this piece of work, they then compare the results with the distribution of mapped landslides in a study area in the Eastern Himalayan Syntaxis in Tibet (centred on about [29.5, 95.25]. This is the broad area studied:-
Now this is a fascinating study area – the Google Earth image below shows a small part of it – note the many landslides:-
Zhang et al. (2025) are able to show that, for this area at least, the spatial distribution of their index of geological complexity correlates well with the mapped distribution of landslides (there are 366 mapped landslides in the 16,606 km2 of the study area).
The authors are clear that this is not the final word on this approach. There is little doubt that this part of Tibet is a highly dynamic area in terms of both climate and tectonics, which probably favours structurally controlled landslides. To what degree would this approach work in a different setting? In addition, acquiring reliable data that represents the components could be a real challenge (e.g. structural data and reliable estimates of probability of peak ground accelerations), and of course the relative weighting of the different components of the index is an open question.
But, it introduces a fresh and really interesting approach that is worth exploring more widely. Zhang et al. (2025) note that there is the potential to combine this index with other indices that measure factors in landslide causation (e.g. topography, climate and human activity) to produce an enhanced susceptibility assessment.
And finally, of course, this approach is providing insights into the ways in which different geological factors aggregate at a landscape scale to generate landslides. That feels like a fundamental insight that is also worth developing.
Thus, this work potentially forms the basis of a range of new studies, which is tremendously exciting.
Reference
Zhang, Y., et al. 2025. Geological Complexity: a novel index for measuring the relationship between landslide occurrences and geological conditions. Bulletin of Engineering Geology and the Environment, 84, 301. https://doi.org/10.1007/s10064-025-04333-9.
