INGENIEUR
CONCLUSION
Figure 3.11: Landslide Vulnerability Map for
Road, Ringlet, Cameron Highlands
Figure 3.12: Landslide Risk Map for Road,
Ringlet, Cameron Highlands.
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2019
VOL 80
55 OCTOBER-DECEMBER
JUNE 2013
The proposed landslide vulnerability assessment
requires determination of four clusters i.e.
susceptibility of critical infrastructures (C),
the effect of the surrounding environment or
mitigation measures (E), the susceptibility of
people inside the residential buildings (P) and
intensity of landslide hazards (I) (Equation 1).
Based on intensive literature reviews, initial
information on the landslide vulnerability
clusters, indicators, sub-indicators, weights,
vulnerability and risk classes were determined for
further improvement in the FGDs. Several FGDs
were carried out to improve this information.
The FGDs with stakeholders were used to
improve the initial information obtained from the
literature review. The outcomes from this FGDs
were further improved by a series of FGDs with
the internal experts of the consultant project
members. The initial landslide vulnerability
clusters were treated equally in which all the
group of indicators has the same influence
towards the vulnerability value. In this case
each group is given with 25% (or 0.25) weight
value. However, the outcomes of the FGDs with
sensitivity analysis and landslide vulnerability
simulations found that this assumption should be
changed, in which the cluster should be treated
differently. Therefore, the final weight for each
cluster has different values.
In the first FGD, a total of 23 landslide
vulnerability survey forms were successfully
completed by the respondents. The respondents
completed the survey forms and determined
the weightage value for each indicator and sub-
indicator depending on the critical infrastructure
given. The weight value was given differently
among the indicators under each group based on
their level of importance in vulnerability estimation.
The results show that the weight values assigned
by the internal experts were more sensitive to the
variations of vulnerability values compared to the
weight assigned by the stakeholders.
More sensitive cluster/indicator can be
achieved by assigning high weight values for
clusters and indicators with good variation or
distribution of weight of sub-indicators (0.1 to
1.0). Based on the best, medium and worst case
landslide vulnerability scenarios, the set of weights