Development of slope failure spatial model for upper sub-basin of Langat River
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Date
2006
Authors
Wan Ibrahim, Wan Mohd Muhiyuddin
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Abstract
Increasing pressure for development in Malaysia in recent years due to rapid
population growth and urbanization has caused numerous environmental related
problems such as slope failure and soil erosion. Increasing of slope failure event in
Malaysia has caused degradation to properties, life and environment. Statistically, from
26 slope failure cases recorded in press within 1993 – 2002, 150 died, 30 were injured
and thousands were evacuated. This means there are 6 deaths in each case. The
objective of this study is to measure spatial factors and their significance that contribute
to slope failure and then model the slope failure using integrating GIS and RS
technology with statistical logistic regression analysis. 58 slope failure cases and 58
random cases represent 1 and 0 value being used to build the model. Each causative
factor mapped and extracted by slope failure point to get attributes from each map.
Attributes from each map join together to produce slope failure database. 65.5% of the
data was used to develop the model and 34.5% to test the model. From logistic
regression analysis, 10 over 14 spatial causative factors have shown the significant
value under 0.1 such as slope steepness, landuse, aspect, curvature, degradation
zone, annual mean rainfall, shortest distance from slope failure to road, shortest
distance from slope failure to major lineament, river density and Antecedent
Precipitation Index (API). 96.1% cases were predicted correctly compared to previous
study which reached only 82.8%. Model test showed 80% of slope failure cases were
predicted correctly. According to R2 value, the model only explained 83% from overall
factors that contributed to slope failure. Sensitivity analysis explained that predicted
accuracy and test accuracy do not show any significant differences when combination
of location and random sample chosen are different. Statistical logistic regression
model then is converted to probability which range from 0 (not occur) to 1 (occur). The
final product is Slope failure susceptibility zone map.
Description
PhD
Keywords
Humanities , Spatial model , Upper sub-basin