Landslide risk reduction measures: A review of practices and challenges for the tropics

Abstract

The overall objective of this review is to gain insights into landslide risk reduction measures that are applied or recommended in tropical landslide-prone countries, and the challenges at play. More specifically, this review aims to (i) presenting an overview of recent studies on landslides and landslide risk reduction in these countries, (ii) exploring the factors controlling the publication output on landslides and landslide risk reduction, (iii) reviewing the various landslide risk reduction measures recommended and implemented, and (iv) identifying the bottlenecks for the implementation of these strategies. A compilation of recommended and implemented landslide risk reduction measures in 99 landslide-prone tropical countries was made, based on an extensive review of scientific literature (382 publications). The documented measures are analysed using a scheme of risk reduction measures that combines classifications of the Hyogo Framework for Action and the SafeLand project. Our literature review shows that the factors influencing the number of publications on landslides and landslide risk reduction per country are (in order of importance) the absolute physical exposure of people to landslides, the population number and the Human Development Index of a country. The ratio of publications on landslide risk reduction versus publications on landslides for landslide-prone tropical countries does not vary much between these countries (average: 0.28). A significant fraction (0.30) of all known landslide hazard reduction measures are neither implemented nor recommended according to our review. The most recommended landslide risk reduction component is ‘risk management and vulnerability reduction’ (0.38). However, the most implemented component is ‘risk assessment’ (0.57). Overall, the ratio of implemented versus recommended landslide risk reduction measures in the tropics is low (<0.50) for most landslide risk reduction components, except for ‘risk assessment’ (3.01). The most cited bottlenecks for implementing landslide risk reduction measures are scientific (0.30) and political (0.29) in nature.

Field-based landslide susceptibility assessment in a data-scarce environment: the populated areas of the Rwenzori Mountains

“…In addition, for many remote regions, reliable landslide susceptibility assessments are not available despite the potentially large impacts of landslides on the local population in these areas. For example, for the African continent, a systematic lack of investigation of landslides and all their facets is particularly pronounced (Maes et al, 2017). Moreover, while recently landslide susceptibility maps for these regions are issued on various scales ranging from continental (e.g.…”

“…Appendix A: InSAR processing to construct the TanDEM-X DEM Over the last two decades, InSAR has been one of the main satellite-based tool used to evaluate ground displacements (Massonnet and Feigl, 1998;Bürgmann et al, 2000;Hanssen, 2001). This technique also allows us to construct DEMs and in particular the DLR (Deutsches Zentrum für Luft-und Raumfahrt -German Aerospace Center) TanDEM-X mission was specifically designed to generate a consistent global DEM (Deo et al, 2013).…”

The Contribution of Physical Geographers to Sustainability Research

“…The point is made that the responsibilities of scientists include the need to effectively communicate their work to policymakers and to populations that may be impacted by landslides. This requires an understanding of social, political, cultural, and economic aspects [74] that are not always considered, except where work is multidisciplinary. Desertification hazards have been investigated by GIS modeling of desertification in Iran, for example, to create a zoning map that can be used for planning [75].…”

“…However, traditional science is increasingly under attack for being out-of-touch with the world. The point has been made, for example, that most papers on landslide disaster risk reduction in the tropics are published in natural science rather than social science journals [74]. However, social scientists have reached out to physical geographers [103] and many physical geographers have responded, albeit in different ways.…”

Enhancing Prediction Performance of Landslide Susceptibility Model Using Hybrid Machine Learning Approach of Bagging Ensemble and Logistic Model Tree

“…The problem of rainfall-induced landslides, which are triggered by high intense and long lasting precipitation, seems to be more serious in recent years in many regions around the world due to the effects of climate changes i.e., extreme rainfall events [1][2][3][4][5][6][7][8]. The rainfall-triggered landslide is especially exacerbated in countries that are located in storm centers of the world, such as Vietnam [9], Philippines [10], and China [11].…”