Likelihood
(hazard) Consequences to property (Vulnerability)
Very
High High Medium Low Very
Low
Very High VH VH H H M
High VH H H M L-M
Medium H H M L-M VL-L
Low M-H M L-M VL-L VL
Very Low M-L LM VL-L VL VL
Legend:
VH
H =
= Very high risk
High risk
M = Moderate risk
L = Low risk
VL = Very low risk
Table 3.1: Improvised International Standard Risk
Assessment Matrix
landslide cases (Corangamite Catchment
Management Authority, 2012).
• To use when information related to
quantitative landslide risk assessment is
absent (Pellicani et al., 2017).
results of the simulated building and residential
landslide vulnerabilities for best, medium and
worst case scenarios. The best case scenarios
produced a vulnerability value of 0.21, i.e. “low
vulnerability” class. The medium case scenarios
successfully produced vulnerability values of
0.50 that fall into “medium vulnerability” class.
The worst-case scenario successfully achieved
“very high vulnerability” class with a value of
0.93. Based on the results, we conclude that
the indicators and sub-indicators have been
well defined and the weight values have a good
distribution as shown from the vulnerability value.
Landslide Inventory Map
Based on the basic principles and methods of
landslide identification and detection described
above, the resulted landslide inventory map for
Ringlet and Lembah Bertam areas are shown in
Figure 3.3 and Figure 3.4, respectively. In these
maps, the identified landslides are delineated by red
polygons. It is important to note that in this study,
although field verifications were not conducted,
the landslide inventory maps were produced by an
expert with many years of experience in landslide
identification and interpretation.
Focus Group Discussions of Key Findings
Landslide Hazard Map
The Focus Group Discussions (FGDs) identified
important key challenges and best practices
in implementing the landslide vulnerability
and determination of the risk index for critical
infrastructures, as well as recommended ways
to improve implementation going forward. More
FGDs were held to ensure that all weights given
are relevant.
Case Scenarios
In this experiment, the best case scenarios were
expected to produce the lowest vulnerability value
and be classified in the “very low vulnerability”
class. On the other hand, the medium case
scenarios were expected to show the estimated
vulnerability values to be classified in the “medium
vulnerability” class. Finally, the worst case
scenarios were expected to produce the highest
vulnerability value that can be classified as “very
high vulnerability” class. Figure 3.1 describes the
Landslide vulnerability and risk maps require a
hazard map to be generated at a specific level
of detail and quality. For example, vulnerability
assessment methods developed for different types
of landslides may require landslide hazard maps
to be generated for different landslide types in the
same spatial scale. In addition, each landslide type
should be accompanied by detailed information e.g.
depth of landslide, run out area, velocity etc. This
information is required to combine the landslide
hazard map and vulnerability map for landslide
risk production. In this study, the landslide hazard
map was obtained from the Department of Mineral
and Geoscience of Malaysia (JMG). The use of
JMG’s landslide hazard maps is governed by JMG’s
practices, therefore the consultant does not have
any control over how the hazard map was produced.
However, due to the ultimate aim of this project to
produce guidelines rather than a technical report,
this was acceptable.
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